# Exfoliation of 2D van der Waals crystals in ultrahigh vacuum for interface
engineering

Zhenyu Sun1,4, Xu Han1,2, Zhihao Cai1,4, Shaosheng Yue1,4 Daiyu Geng1,4,
Dongke Rong1,3, Lin Zhao1,4, Yi-Qi Zhang1,4 Peng Cheng1,4, Lan Chen1,4,5,
Xingjiang Zhou1,4, Yuan Huang2∗ Kehui Wu1,4,5,6∗, and Baojie Feng1,4,6∗

1Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
2Advanced Research Institute of Multidisciplinary Science,
Beijing Institute of Technology, Beijing 100081, China
3School of Science, China University of Geosciences, Beijing 100083, China
4School of Physical Sciences, University of Chinese Academy of Sciences,
Beijing 100049, China
5Songshan Lake Materials Laboratory, Dongguan, Guangdong 523808, China
6Interdisciplinary Institute of Light-Element Quantum Materials and Research
Center
for Light-Element Advanced Materials, Peking University, Beijing, 100871,
China

∗Corresponding author. E-mail: yhuang<EMAIL_ADDRESS>
<EMAIL_ADDRESS>

Two-dimensional (2D) materials and their heterostructures have been
intensively studied in recent years due to their potential applications in
electronic, optoelectronic, and spintronic devices. Nonetheless, the
realization of 2D heterostructures with atomically flat and clean interfaces
remains challenging, especially for air-sensitive materials, which hinders the
in-depth investigation of interface-induced phenomena and the fabrication of
high-quality devices. Here, we circumvented this challenge by exfoliating 2D
materials in an ultrahigh vacuum. Remarkably, ultraflat and clean substrate
surfaces can assist the exfoliation of 2D materials, regardless of the
substrate and 2D material, thus providing a universal method for the
preparation of heterostructures with ideal interfaces. In addition, we studied
the properties of two prototypical systems that cannot be achieved previously,
including the electronic structure of monolayer phospherene and optical
responses of transition metal dichalcogenides on different metal substrates.
Our work paves the way to engineer rich interface-induced phenomena, such as
proximity effects and moiré superlattices.

Keywords: ultrahigh vacuum, mechanical exfoliation, interface engineering,
universal method

##  1 Introduction

Since the discovery of graphene in 2004, the study of two-dimensional (2D)
materials and heterostructures has become one of the most active fields, as
they hold great promise for next-generation quantum devices [1, 2]. To date, a
wide variety of 2D materials have been realized, including transition metal
dichalcogenides (TMDCs) [3], hexagonal boron nitride [4], and black phosphorus
[5]. Compared with bulk materials, 2D materials have a much higher surface-
area-to-volume ratio. Therefore, the interfaces between 2D materials and
substrates or other 2D materials can induce various exotic properties, which
provides an effective method for manipulating the properties of 2D
heterostructures through interface engineering. One example is proximity
effects, including proximity-induced superconductivity [6, 7], magnetism [8],
and topology [9]. When a topological insulator or ferromagnetic atomic chain
is placed on a superconductor, the coexisting superconducting and topological
orders can give rise to topological superconductivity, which hosts the long-
sought Majorana fermions [10, 11]. Another example is interface-enhanced long-
range order, such as superconductivity [12], magnetism [8], and charge density
waves [13]. In addition, the moiré superlattices generated by stacking 2D
materials with specific twist angles have attracted much attention in recent
years. Periodic moiré potentials can lead to strong electron correlation
effects, such as superconductivity [14] and Wigner crystal states [15, 16].

The rapid development of 2D materials requires the preparation of high-quality
ultrathin samples, which has spawned a variety of fabrication techniques
ranging from bottom-up approaches such as molecular beam epitaxy (MBE) and
chemical vapor deposition (CVD) to top-down approaches such as mechanical
exfoliation. For bottom-up approaches, the growth parameters of each system
need to be optimized, which is time-consuming and inefficient. In addition,
only a limited number of substrates can be used to grow specific 2D materials,
and only specific twist angles with the substrates can be obtained depending
on the growth dynamics. These facts greatly limit the ability to manipulate
the properties of 2D materials via interface engineering. Top-down approaches
provide greater flexibility than bottom-up approaches. For layered van der
Waals crystals, in principle, ultrathin flakes can be obtained on arbitrary
substrates with controlled twist angles by liquid-phase or dry exfoliation.

However, traditional mechanical exfoliation is performed in air or glove
boxes, and contaminants are inevitable compared to the ultrahigh vacuum (UHV)
MBE technique. These contaminants are detrimental to the intrinsic properties
of 2D materials, especially for air-sensitive materials, including black
phosphorus [17], transition metal tellurides [18], and metal iodides [19].
This indicates the existence of large amounts of adsorbates, which questions
the reliability of ex situ measurements of the intrinsic properties of 2D
materials. The preparation of 2D materials and heterostructures with high-
quality interfaces requires direct exfoliation of 2D materials in UHV to avoid
possible contaminants. To this end, several methods have been developed. For
example, the dry contact transfer method can be used to fabricate graphene
nanoribbons and quantum dots [20, 21]; direct exfoliation of graphene has been
realized on Si(111)-7$\times$7 reconstructed surfaces [22] and epitaxial
graphene [23]. However, in-depth research on this technique, including the
universality of other 2D materials and substrates, is still lacking.

Here, we demonstrate that vacuum exfoliation is a universal technique to
obtain ultrathin 2D materials. The substrates for exfoliating 2D materials
were obtained by standard surface preparation methods in UHV, such as
annealing, ion sputtering, plasma treatment, and MBE growth. Assisted by
ultraflat and clean surfaces, various 2D materials can be directly exfoliated
by a simple “stamp and peel-off” procedure, forming an ideal interface with
the substrates. The improved interface quality makes it possible to
investigate their intrinsic properties by surface-sensitive techniques. In
addition, this technique enables the investigation of interface-induced
phenomena, such as the different optical responses of monolayer TMDCs on metal
substrates. Our work not only enriches the diversity of realizable 2D
heterostructures but also highlights the possibility of realizing rich exotic
properties through interface engineering.

##  2 Methods

2.1. Preparation of the substrates
Single-crystal oxide substrates, including MgO, SrTiO3, and Al2O3, were
annealed at $>$1000 ∘C for 6 hours in a tube furnace with appropriate oxygen
flux. The as-prepared substrates show atomically flat surfaces, which were
confirmed by atomic force microscope (AFM) measurements. The substrates were
then transferred to the UHV exfoliation system ($\sim$10-10 mbar), and
annealed at $\sim$600 ∘C to remove the surface adsorbates. The Si(111)
substrates were annealed at $\sim$600∘C for 1 hour and then flashed to 1250 ∘C
several times to form the 7$\times$7 surface reconstruction. The cleanliness
of the substrate surfaces was confirmed by in-situ low-energy electron
diffraction (LEED) measurements. Polycrystalline metal films, including Au,
Ag, Fe, and Cr, were prepared by growing high-purity metals onto the SiO2/Si
substrates in UHV. For Au and Ag films, Cr buffer layers are required to
strengthen the adhesion with the substrates. Before growth, the SiO2/Si
substrates were annealed at 300 ∘C to remove surface adsorbates. During
growth, the substrate temperature was kept at room temperature. The
thicknesses of the metal films were calibrated by a thickness monitor, and all
metal films for UHV exfoliation were approximately 10-nm thick.

2.2. Mechanical exfoliation in UHV
Two vertically aligned sample stages were designed for the UHV exfoliation, as
shown in Fig. 1(b). One stage is used to fix the substrates, and the other one
is used to fix the freshly cleaved 2D van der Waals crystals. During the whole
mechanical exfoliation process, the vacuum was kept at $\sim$10-10 mbar. The
exfoliation is typically conducted $\sim$10 min after the preparation of
substrates.

2.3. In-situ characterization
After UHV mechanical exfoliation, the sample surface was checked by an optical
microscope mounted outside the vacuum chamber. The surface quality was checked
by in-situ LEED (OCI Microengineering Incorporation). The angle-resolved
photoemission spectroscopy (ARPES) measurements were performed at room
temperature with a SPECS PHOIBOS 150 analyzer and helium discharge lamp
($\sim$21.2 eV). Before ARPES measurements, the samples were transferred to
the ARPES chambers without breaking the UHV. The energy resolution of ARPES
was $\sim$15 meV.

2.4. Ex-situ characterization
AFM measurements were performed with a commercial facility (Oxford, Asylum
Research Cypher S) in the tapping mode. X-ray photoelectron spectroscopy (XPS)
measurements were performed using the Al K line (Thermo Scientific ESCALAB
Xi+) with a base pressure $<$2$\times$10-9 mbar. The XPS peaks were calibrated
using the carbon 1s peak (284.8 eV). The Raman and photoluminescence (PL)
measurements were carried out with an excitation wavelength of 532 nm (WITec
alpha300R). The Raman peak of Si at 520.7 cm-1 was used to calibrate each
spectrum. The samples for optical characterizations were transferred from the
UHV chamber to a glove box without exposure to air and then spin-coated with
PMMA capping layers before taking out for optical characterizations. All AFM,
XPS, Raman, and PL measurements were carried out at room temperature.

##  3 Results and Discussion

###  3.1 Exfoliation of ultrathin 2D materials in UHV

A schematic diagram of our method is illustrated in Fig. 1a-c. The system
consists of three parts: preparation, exfoliation, and characterization. In
the preparation chamber, ultraflat and clean substrates are prepared using
standard surface preparation techniques. Freshly cleaved van der Waals
crystals are then pressed onto the as-prepared substrates. The substrate
temperature varies from room temperature to approximately 500 K, depending on
the type of material. After several minutes, the crystals are quickly
separated from the substrates, leaving ultrathin flakes on the substrates. The
quality of the exfoliated samples is examined by an optical microscope through
a viewport, as shown in Fig. 1c. The as-prepared ultrathin 2D materials can be
transferred to other UHV measurement systems, such as LEED, ARPES, and
scanning tunneling microscopy (STM), without breaking the vacuum.

Figure 1: Mechanical exfoliation of 2D materials in UHV. (a-c) Schematic
drawing of the UHV exfoliation process, including preparation of ultraflat and
clean substrate surfaces (a), mechanical exfoliation (b), and in situ
characterization (c). (d) Optical images of large-scale 2D materials on
polycrystalline Au obtained by the UHV mechanical exfoliation technique: MoS2,
WSe2, RuCl3, and black phosphorus. The 1L and 2L areas are indicated in each
picture. Scale bar: 40 $\mu$m. (e,f) AFM and Raman spectroscopy
characterization of the exfoliated 2D materials, respectively. Scale bar: 2
$\mu$m.

First, we demonstrate that the Au-assisted exfoliation technique, which can be
used to prepare large-scale monolayer 2D materials [24, 25, 26, 27], is
compatible with our system. Due to the strong adhesion of polycrystalline Au
films, it is possible to exfoliate a variety of 2D materials at high yields.
Figure 1d shows optical images of four typical 2D materials: MoS2, WSe2,
RuCl3, and black phosphorus. The large-scale monolayer and bilayer areas are
marked in each picture. To further confirm the quality and thickness of the
samples, ex situ AFM and Raman spectroscopy measurements were performed, and
the results are shown in Fig. 1e,f. The surface is predominantly covered by
ultrathin flakes, similar to previous works in air. However, distinct from our
UHV exfoliation (see Fig. S1), the Au substrate degrades quickly in air, and
the exfoliation yield declines rapidly after a few minutes of exposure to air
[25].

Next, we show the ability to realize ultrathin 2D materials on single-crystal
substrates with atomically flat interfaces. Such heterostructures are
difficult to realize using traditional mechanical exfoliation techniques for
the following reasons. First, for most materials, atomically clean and flat
surfaces are only stable in ultrahigh vacuum. For example, the
Si(111)-7$\times$7 surface is prone to adsorb contaminants when the vacuum is
worse than $\sim$1$\times$10-9 mbar. Second, even for stable materials, a
large number of adsorbates or bubbles will be trapped at the interfaces during
the exfoliation process, which may seriously affect their intrinsic properties
[28, 29]. Third, the degradation of single-crystal surfaces, including the
adsorption of contaminants or oxidization, tends to reduce the adhesion
energy, which significantly reduces the exfoliation yield of ultrathin 2D
materials [30]. Therefore, the preparation of 2D materials on single-crystal
substrates with high-quality interfaces requires all preparation processes to
be carried out in UHV. Previously, MBE has been proven to be an efficient
method for the preparation of high-quality heterostructures, as exemplified by
Bi2Se3/NbSe2 [7] and FeSe/SrTiO3 [12]. However, as mentioned above, MBE has
significant limitations compared to mechanical exfoliation, which calls for
the development of vacuum exfoliation techniques.

We selected several typical single-crystal substrates, including MgO(100),
SrTiO3(100), Al2O3(0001), and Si(111). After pretreatment by UHV annealing or
flashing, these substrates show atomically flat surfaces, as confirmed by AFM,
STM, and LEED measurements (Fig. 2a-d). Surprisingly, the exfoliation yield
increases significantly due to the improved surface quality of the substrates.
Taking MoS2 as an example, monolayer flakes can be obtained on all of these
substrates, as shown in Fig. 2e-h. In addition to MoS2, other 2D materials can
also be exfoliated on these substrates, including graphene, FeSe, and Bi-2212,
as shown in Fig. 2i-l. The quality of these ultrathin 2D materials was
confirmed by Raman and AFM characterizations (Fig. S2-S4). The successful
exfoliation of different types of ultrathin 2D materials on different
substrates indicates the universality of this method, regardless of the 2D
material and substrate. The increased exfoliation yield might originate from
the enhanced coulombic attraction between 2D materials and the substrates
since atomically flat and clean substrates increase the contact areas with 2D
materials.

###  3.2 Characterization of monolayer phosphorene

Due to the improved quality of the surface and interface, the UHV exfoliation
technique enables the study of exfoliated 2D materials by surface-sensitive
techniques. Here, we take monolayer phosphorene as an example. Although few-
layer phosphorene can be easily isolated from bulk black phosphorus, large-
scale monolayer phosphorene is still difficult to realize. In addition,
phosphorene is easy to degrade in air compared to UHV (see Fig. S5-S7), and
exposing phosphorene to air or low-vacuum conditions will permanently degrade
the surface quality. Such serious degradation hinders an in-depth
investigation of its physical properties by surface-sensitive techniques. To
date, only a few works have been reported on the optical and transport
properties of monolayer phosphorene [31, 32], while direct studies of its
structure and electronic properties by LEED and ARPES are still lacking.

Based on our UHV exfoliation technique, we isolated millimeter-sized monolayer
phosphorene, as shown in the optical image in Fig. 3a; such large-scale
samples enable measurements using conventional LEED and ARPES techniques. The
thickness of the exfoliated phosphorene was confirmed by AFM and Raman
spectroscopy characterizations, as shown in Fig. S8. The LEED pattern of the
exfoliated monolayer phosphorene is displayed in Fig. 3c, which shows a
rectangular structure. The absence of the (10) diffraction spots is due to the
phase cancellation caused by the surface glide mirror symmetry [33]. The
estimated lattice constants agree with those of bulk black phosphorus,
indicating the absence of structural transition or charge density waves. The
ARPES intensity map along the $\Gamma$-Y direction is shown in Fig. 3f. A
hole-like parabolic band centered at the $\Gamma$ point is observed, which is
consistent with previous calculations [34]. The valence band top is 0.2 eV
below the Fermi level, slightly deeper than that of bulk black phosphorus. The
downward shift of the hole-like bands might originate from electron doping
effects of the Au substrate.

###  3.3 Optical responses of monolayer TMDCs on different substrates

Having confirmed the high quality of the exfoliated 2D materials by LEED and
ARPES, we move on to show that the improved quality provides opportunities to
realize rich interface-induced phenomena. Here, we study the optical responses
of monolayer TMDCs on different metal substrates, including Au, Ag, Cr, and
Fe. When TMDCs, such as MoS2, come into contact with Au, the photoluminescence
(PL) signal will be completely quenched because of the strong charge transfer
at the interface [25, 35], as shown in Fig. 4a. However, similar PL quenching
effects have not been verified when monolayer TMDCs are placed on other metal
substrates. The difficulty of such experiments lies in the air sensitivity of
other metals. Unlike Au, which is relatively stable in air, the surfaces of
Ag, Cr, and Fe will rapidly oxidize and adsorb contaminants under low-vacuum
conditions. Therefore, using traditional mechanical exfoliation techniques,
the exfoliated 2D material is in direct contact with metal oxides or
contaminants rather than with the pristine metal surface. All of these
difficulties can be avoided by the UHV exfoliation technique. Due to the
improved surface quality of metal films under UHV, we successfully realized
monolayer MoS2 and WSe2 on all of these substrates, as shown in Fig. S10.

The PL spectra of monolayer WSe2 on different metal films are displayed in
Fig. 4b. For WSe2 on Au, the PL peak at $\sim$1.65 eV from the A exciton is
completely quenched, consistent with previous reports [25]. However, this peak
was still visible when WSe2 was placed on Ag, Cr, and Fe. In addition to the
survival of the PL signal, we observed a significant redshift of the PL peak,
which might be attributed to the enhanced trion photoluminescence [36].
Similar phenomena have also been observed in MoS2, as shown in Fig. S11. There
are three possible reasons for the survival of the PL signal of TMDCs on Ag,
Cr, and Fe. First, these metals might have much weaker orbital hybridization
with TMDCs than Au, and electrons in the excited states of TMDCs have a lower
probability of transferring to substrates. Second, although Ag, Cr, and Fe
hybridize with TMDCs, the transition of electrons from excited states to
hybridized states is also radiative, leading to the survival of the PL signal.
Third, since the PL spectra were acquired in ambient conditions, oxygen might
penetrate TMDCs, oxidize the topmost metal layers, and decouple TMDCs from the
substrates [38].

The Raman spectra of monolayer MoS2 on different substrates are displayed in
Fig. 4c. Similar to suspended MoS2, the E${}_{2g}^{1}$ and A1g peaks of MoS2
on Fe and Cr are unimodal with a wavenumber spacing of $\sim$19 cm-1 [37]. The
shift of the Raman peaks is negligible, indicating a weak interaction of these
substrates with MoS2. When the substrate is switched to Au, the A1g peak is
split, accompanied by a significant redshift and broadening of the
E${}_{2g}^{1}$ peak, in agreement with previous reports [39]. The Raman
behavior of MoS2/Au might originate from charge transfer and local lattice
deformation at the interface, as illustrated in Fig. 4d. In contrast with Au,
the Ag substrate has different effects on the Raman behavior of MoS2. The A1g
peak does not split, while the E${}_{2g}^{1}$ peak is split by $\sim$9 cm-1.
Since E${}_{2g}^{1}$ is an in-plane vibrational mode, the splitting of this
mode indicates a strong in-plane lattice distortion caused by the substrate.
Similar results have been reported in strained [40] and twisted bilayer MoS2
[41], but the splitting is smaller than the current case. In addition, all
three Raman modes, especially 2LA(M), show significant enhancement on Ag. The
enhancement of Raman peaks might originate from surface plasmon resonance,
which has been reported in Ag nanoparticle-decorated MoS2 [42].

##  4 Summary and outlook

To summarize, we report a universal UHV exfoliation technique for realizing 2D
materials and heterostructures with ideal interfaces. The improved surface
quality grants access to study their intrinsic properties by surface-sensitive
techniques, especially for air-sensitive materials. In addition, the
universality of this technique provides unprecedented opportunities to realize
rich interface-induced properties. Due to the different optical responses of
TMDCs on metal substrates shown above, a number of intriguing properties can
be readily expected. For example, the superconducting critical temperature of
monolayer FeSe grown on SrTiO3(001) is enhanced to $>$60 K compared with bulk
FeSe. However, epitaxial FeSe can only grow along the crystallographic
direction of SrTiO3(001). With the UHV exfoliation technique, one can easily
isolate ultrathin FeSe on SrTiO3 or other substrates with controlled twist
angles (see Fig. S14). In-depth investigations of these heterostructures may
not only shed light on the mechanism for the enhanced superconductivity but
also be conducive to realizing superconductors with higher critical
temperatures.

Acknowledgements This work was supported by the Ministry of Science and
Technology of China (Grant No. 2018YFE0202700), the National Natural Science
Foundation of China (Grants No. 11974391, No. 11825405, No. 1192780039, and
No. U2032204), the Beijing Natural Science Foundation (Grant No. Z180007), the
International Partnership Program of Chinese Academy of Sciences (Grant No.
112111KYSB20200012), and the Strategic Priority Research Program of Chinese
Academy of Sciences (Grants No. XDB33030100).

Author Contributions Baojie Feng, Kehui Wu, and Yuan Huang conceived the
research. Baojie Feng, Kehui Wu, Yuan Huang, and Zhenyu Sun designed the UHV
exfoliation system; Zhenyu Sun, Xu Han, Zhihao Cai, Shaosheng Yue, Daiyu Geng,
Dongke Rong performed the characterization experiments; all authors
contributed to the discussion of the data and writing of the manuscript.

Competing Financial Interests The authors declare no competing financial
interests.

## References

  * [1] Liu Y, Weiss NO, Duan X, et al. Van der Waals heterostructures and devices. Nat Rev Mater 2016;1:16042.
  * [2] Novoselov KS, Mishchenko A, Carvalho A, et al. 2D materials and van der Waals heterostructures. Science 2016;353:461.
  * [3] Manzeli S, Ovchinnikov D, Pasquier D, et al. 2D transition metal dichalcogenides. Nat Rev Mater 2017;2:17033.
  * [4] Roy S, Zhang X, Puthirath AB, et al. Structure, properties and applications of two-dimensional hexagonal boron nitride. Adv Mater 2021;33:2101589.
  * [5] Xia F, Wang H, Hwang JCM, et al. Black phosphorus and its isoelectronic materials. Nat Rev Phys 2019;1:306-17.
  * [6] Morpurgo AF, Kong J, Marcus CM, et al. Gate-controlled superconducting proximity effect in carbon nanotubes. Science 1999;286:263-5.
  * [7] Wang MX, Liu C, Xu JP, et al. The coexistence of superconductivity and topological order in the Bi2Se3 thin films. Science 2012;336:52-5.
  * [8] Hellman F, Hoffmann A, Tserkovnyak Y, et al. Interface-induced phenomena in magnetism. Rev Mod Phys 2017;89:025006.
  * [9] Shoman T, Takayama A, Sato T, et al. Topological proximity effect in a topological insulator hybrid. Nat Commun 2015;6:6547.
  * [10] Fu L, Kane CL. Superconducting proximity effect and Majorana fermions at the surface of a topological insulator. Phys Rev Lett 2008;100:096407.
  * [11] N.-Perge S, Drozdov IK, Li J, et al. Observation of Majorana fermions in ferromagnetic atomic chains on a superconductor. Science 2014;346:602-7.
  * [12] Wang QY, Li Z, Zhang WH, et al. Interface-induced high-temperature superconductivity in single unit-cell FeSe films on SrTiO3. Chin Phys Lett 2012;29:037402.
  * [13] Xi X, Zhao L, Wang Z, et al. Strongly enhanced charge-density-wave order in monolayer NbSe2. Nat Nanotechnol 2015;10:765-70.
  * [14] Cao Y, Fatemi V, Fang S, et al. Unconventional superconductivity in magic-angle graphene superlattices. Nature 2018;556:43-50.
  * [15] Regan EC, Wang D, Jin C, et al. Mott and generalized Wigner crystal states in WSe2/WS2 moiré superlattices. Nature 2020;579:359-63.
  * [16] Xu Y, Liu S, Rhodes DA, et al. Correlated insulating states at fractional fillings of moiré superlattices. Nature 2020;587:214-18.
  * [17] Favron A, Gaufrès E, Fossard F, et al. Photooxidation and quantum confinement effects in exfoliated black phosphorus. Nat Mater 2015;14:826-32.
  * [18] Ye F, Lee J, Hu J, et al. Environmental instability and degradation of single- and few-layer WTe2 nanosheets in ambient conditions. Small 2016;12:5802-8.
  * [19] Shcherbakov D, Stepanov P, Weber D, et al. Raman spectroscopy, photocatalytic degradation, and stabilization of atomically thin chromium tri-iodide. Nano Lett 2018;18:4214-9.
  * [20] Ritter KA, Lyding JW. Characterization of nanometer-sized, mechanically exfoliated graphene on the H-passivated Si(100) surface using scanning tunneling microscopy. Nanotechnology 2008;19:015704.
  * [21] Ritter KA, Lyding JW. The influence of edge structure on the electronic properties of graphene quantum dots and nanoribbons. Nat Mater 2009;8:235-242.
  * [22] Ochedowski O, Begall G, Scheuschner N, et al. Graphene on Si(111)-7$\times$7\. Nanotechnology 2012;23:405708.
  * [23] Imamura H, Visikovskiy A, Uotani R, et al. Twisted bilayer graphene fabricated by direct bonding in a high vacuum. Appl Phys Express 2020;13:075004.
  * [24] Desai SB, Madhvapathy SR, Amani M, et al. Gold-mediated exfoliation of ultralarge optoelectronically-perfect monolayers. Adv Mater 2016;28:4053-8.
  * [25] Velický M, Donnelly GE, Hendren WR, et al. Mechanism of gold-assisted exfoliation of centimeter-sized transition-metal dichalcogenide monolayers. ACS Nano 2018;12:10463-72.
  * [26] Huang Y, Pan YH, Yang R, et al. Universal mechanical exfoliation of large-area 2D crystals. Nat Commun 2020;11:2453.
  * [27] Liu F, Wu W, Bai Y, et al. Disassembling 2D van der Waals crystals into macroscopic monolayers and reassembling into artificial lattices. Science 2020;367:903-6.
  * [28] Gass MH, Bangert U, Bleloch AL, et al. Free-standing graphene at atomic resolution. Nat Nanotechnol 2008;3:676-81.
  * [29] Purdie DG, Pugno NM, Taniguchi T, et al. Cleaning interfaces in layered materials heterostructures. Nat Commun 2018;9:5387.
  * [30] Huang Y, Sutter E, Shi N, et al. Reliable exfoliation of large-area high-quality flakes of graphene and other two-dimensional materials. ACS Nano 2015;9:10612-20.
  * [31] Li L, Yu Y, Ye G, et al. Black phosphorus field-effect transistors. Nat Nanotechnol 2014;9:372-7.
  * [32] Li L, Kim J, Jin C, et al. Direct observation of the layer-dependent electronic structure in phosphorene. Nat Nanotechnol 2017;12:21-5.
  * [33] Dai Z, Jin W, Yu JX, et al. Surface buckling of black phosphorus: Determination, origin, and influence on electronic structure. Phys Rev Mater 2017;1:074003.
  * [34] Rudenko AN, Yuan SJ, Katsnelson MI. Toward a realistic description of multilayer black phosphorus: From GW approximation to large-scale tight-binding simulations. Phys Rev B 2015;92:085419.
  * [35] Bhanu U, Islam MR, Tetard L, et al. Photoluminescence quenching in gold-MoS2 hybrid nanoflakes. Sci Rep 2014;4:5575.
  * [36] Mak KF, He K, Lee C, et al. Tightly bound trions in monolayer MoS2. Nat Mater 2013;12:207-11.
  * [37] Li H, Zhang Q, Yap CCR, et al. From bulk to monolayer MoS2: Evolution of Raman scattering. Adv Funct Mater 2012;22:1385-90.
  * [38] Velicky M, Donnelly GE, Hendren WR, et al. The intricate love affairs between MoS2 and metallic substrates. Adv Mater Interfaces 2020;7:2001324.
  * [39] Velický M, Rodriguez A, Bou$\check{s}$a M, et al. Strain and charge doping fingerprints of the strong interaction between monolayer MoS2 and gold. J Phys Chem Lett 2020;11:6112-18.
  * [40] Lee JU, Woo S, Park J, et al. Strain-shear coupling in bilayer MoS2. Nat Commun 2017;8:1370.
  * [41] Quan J, Linhart L, Lin ML, et al. Phonon renormalization in reconstructed MoS2 moiré superlattices. Nat Mater 2021;20:1100-5.
  * [42] Zhang D, Wu YC, Yang M, et al. Surface enhanced Raman scattering of monolayer MX2 with metallic nano particles. Sci Rep 2016;6:30320.

Figure 2: Exfoliation of ultrathin 2D materials on single-crystal substrates.
(a-c) AFM images of MgO(100), SrTiO3(100), Al2O3(0001), respectively. (d) STM
image of Si(111). The LEED pattern of each substrate is shown in the inset of
(a-d). Scale bar: 400 nm. (e-h) Optical images of ultrathin MoS2, graphene,
Bi-2212, and FeSe. Scale bar: 5 $\mu$m. Figure 3: LEED and ARPES
characterization of monolayer phosphorene. (a) Optical image of UHV-exfoliated
phosphorene on Au. The lateral size of monolayer phosphorene is on the order
of millimeters. (b) LEED pattern of monolayer phosphorene exfoliated in UHV.
(c,d) Crystal structure and Brillouin zone of monolayer phosphorene. (e) ARPES
intensity plot of monolayer phosphorene along the $\Gamma$-Y direction
measured at room temperature. The energy of the incident photon is 21.2 eV.
The valence band maximum is located at the $\Gamma$ point. Figure 4: Optical
responses of monolayer MoS2 and WSe2 on different metal films. (a) Schematic
drawing of the PL quenching process. The transition of electrons in the
excited states of TMDCs to the substrate is nonradiative. (b) PL spectra of
monolayer WSe2 on Au, Ag, Fe, and Cr films. The vertical dashed line indicates
the peak position of the suspended sample. (c) Raman spectra of monolayer MoS2
on Au, Ag, Fe, and Cr. The suspended monolayer MoS2 is shown for comparison.
(d) Schematic drawing of monolayer TMDCs on metal substrates. Local strain and
electron doping can affect the Raman behavior.


# Taurid stream #628: a reservoir of large cometary impactors

Hadrien A. R. Devillepoix School of Earth and Planetary Sciences, Curtin
University, Perth WA 6845, Australia  Peter Jenniskens SETI Institute, 189
Bernardo Avenue, Mountain View, CA 94043, USA  NASA Ames Research Center, Mail
Stop 241-11, Moffett Field, CA 94035, USA  Philip A. Bland School of Earth and
Planetary Sciences, Curtin University, Perth WA 6845, Australia  Eleanor K.
Sansom School of Earth and Planetary Sciences, Curtin University, Perth WA
6845, Australia  Martin C. Towner School of Earth and Planetary Sciences,
Curtin University, Perth WA 6845, Australia  Patrick Shober School of Earth
and Planetary Sciences, Curtin University, Perth WA 6845, Australia  Martin
Cupák  School of Earth and Planetary Sciences, Curtin University, Perth WA
6845, Australia  Robert M. Howie School of Earth and Planetary Sciences,
Curtin University, Perth WA 6845, Australia  Benjamin A. D. Hartig School of
Earth and Planetary Sciences, Curtin University, Perth WA 6845, Australia
Seamus Anderson School of Earth and Planetary Sciences, Curtin University,
Perth WA 6845, Australia  Trent Jansen-Sturgeon School of Earth and Planetary
Sciences, Curtin University, Perth WA 6845, Australia  Jim Albers  SETI
Institute, 189 Bernardo Avenue, Mountain View, CA 94043, USA

(Received June 30, 2021; Accepted August 18, 2021)

###### Abstract

The Desert Fireball Network observed a significant outburst of fireballs
belonging to the Southern Taurid Complex of meteor showers between October 27
and November 17, 2015. At the same time, the Cameras for Allsky Meteor
Surveillance project detected a distinct population of smaller meteors
belonging to the irregular IAU shower #628, the s-Taurids. While this
returning outburst was predicted and observed in previous work, the reason for
this stream is not yet understood. 2015 was the first year that the stream was
precisely observed, providing an opportunity to better understand its nature.
We analyse the orbital elements of stream members, and establish a size
frequency distribution from millimetre to metre size range.

The stream is highly stratified with a large change of entry speed along
Earth’s orbit. We confirm that the meteoroids have orbital periods near the
7:2 mean-motion resonance with Jupiter. The mass distribution of this
population is dominated by larger meteoroids, unlike that for the regular
Southern Taurid shower. The distribution index is consistent with a gentle
collisional fragmentation of weak material.

A population of metre-sized objects is identified from satellite observations
at a rate consistent with a continuation of the size-frequency distribution
established at centimetre size. The observed change of longitude of perihelion
among the s-Taurids points to recent (a few centuries ago) activity from
fragmentation involving surviving asteroid 2015TX2̣4. This supports a model
for the Taurid Complex showers that involves an ongoing fragmentation cascade
of comet 2P/Encke siblings following a breakup some 20,000 years ago.

Meteoroids — Meteor Shower: Taurids, s-Taurids — Comet: 2P/Encke

††journal: PSJ

##  1 Introduction

The Southern and Northern Taurid showers are part of a Taurid Complex of
meteor showers with daytime and nighttime components, the night-time showers
of which spread from September to December along Earth’s path (Jenniskens,
2006; Brown et al., 2013). Whipple (1940) first identified comet 2P/Encke as
the likely parent body. The comet now has evolved to a phase in the rotation
of the nodal line that keeps its nodes far from Earth. However, this Jupiter
family comet moves in a short 3.3-year orbit that is decoupled from Jupiter,
which makes both the comet and meteoroid orbits relatively stable for long
periods of time. The wide dispersion of the showers’ longitude of perihelion
requires a formation age at least 20,000 years ago, the minimum time it takes
to disperse the longitude of perihelion of the orbits as wide as observed.

Clube & Napier (1984) first suggested that the a large number of potential
other parent body asteroids were part of a Taurid Complex that originated from
a giant comet breakup 20,000 years ago. However, Jenniskens (2006) pointed out
that these early proposed parent bodies appeared to be S- or O-class stony
asteroids, instead, which evolved into Encke-like orbits from a source in the
asteroid belt via the $\nu_{6}$ resonance. The same conclusion was also
reached more recently by Popescu et al. (2014) and Tubiana et al. (2015).

Jenniskens (2006) and Jenniskens et al. (2016a) also noticed that there was no
mirror image between Taurid shower component nodes in northern and southern
branches, suggesting that meteoroids did not survive long enough to fully
disperse their nodes around the original orbit. A full precession of the nodal
line takes about 5,000 years, hence individual shower components in the South
and North branches are likely younger than 5000 years. Instead, Jenniskens
(2006) proposed that a more restricive set of possible parent bodies with
semi-major axis close to the 2.22 AU of comet 2P/Encke was responsible and the
20,000 year old stream now reflects the current dispersion of these smaller
parent bodies that continue to generate Taurid meteoroids in the recent past.
One possible parent was identified as asteroid 2004 TG10, now known to be a
1.3 km large object (H = 19.4) with low 0.018 albedo.

This idea that the Taurid complex is active as a whole, and is not just the
remnant of a single 20,000+ years old break up, is supported by the orbital
analysis done by Whipple & El-Din Hamid (1952). Long before modern orbital
integrators and the introduction of orbital similarity criteria $D$
(Southworth & Hawkins, 1963; Drummond, 1981), they were able to identify a
group of Southern Taurids that dynamically converged 1400 years in the past.
To explain why Encke did not match the orbit of the group, they suggested that
the stream of material could have come from a companion, which could have
itself separated from Encke earlier. More recently, Olech et al. (2016)
reported two large bolides entering the skies of Poland on October 31, 2015.
The meteoroids have very similar orbits ($D_{D}=0.011$), and the authors
identify two asteroids (2005 UR and 2005 TF50) as potential members of the
stream. Using a backward integration, they show that these 4 objects (two
meteoroids and two NEOs) have their orbital elements converge 1500 years ago,
in good agreement with Whipple & El-Din Hamid (1952). That does not exclude
that the bolides originated from one of the two asteroids in more recent
times.

The 2015 bolides were part of an outburst of fireballs that is a repeating
phenomenon for the Southern Taurid complex in late October and early November.
Every 3+ years, there is a significant uptick of Taurid fireballs (Table 1).
There is no clear link to the times when comet Encke returns to perihelion.
Instead, it appears that a cloud of meteoroids remains concentrated around a
certain position (range of mean anomaly) along the orbit. Olech et al. (2017)
reported on Taurids observed in the Polish Fireball Network in 2005 and 2015
and found that over 100 fireballs moved in similar orbits as asteroid 2015
TX24. Similarly, Spurný et al. (2017) found that 113 out of 144 Taurid
fireballs observed by the European Network (EN) in 2015 had similar orbital
elements and suggested that both asteroids 2015 TX24 and 2005 UR were
associated with this stream, and possibly 2005 TF50, arguing that these
several hundred metre diameter bodies represented an extension of the
population of bodies seen among the observed fireballs.

Froeschle & Scholl (1986) first suggested that meteoroids can be trapped by
strong mean motion resonances (MMR) with Jupiter. Material trapped in a MMR is
prevented from undergoing full nodal precession, explaining concentrations of
dust in mean anomaly over long periods of time. Asher et al. (1993) suggested
that this occurred to some Taurids trapped in 7:2 MMR with Jupiter. The
expected periodic signature of outbursts was later verified by Asher & Izumi
(1998). Their model is successful at explaining enhanced activity in years
when the Earth comes within $\Delta_{M}\in\pm 30/40\arcdeg$ of the resonance
centre in mean anomaly (Table 1). Asher & Izumi (1998) also published future
and past year outburst predictions by his model.

Year | $\Delta_{M}$ | Observations
---|---|---
1995 | $+29\arcdeg$ | Spurný (1997)
1998 | $-13\arcdeg$ | Beech et al. (2004)
2005 | $+11\arcdeg$ | Dubietis & Arlt (2007); Shrbený & Spurný (2012); Olech et al. (2017)
2008 | $-30\arcdeg$ | SonotaCo (2009)
2012 | $+35\arcdeg$ | Madiedo et al. (2014)
2015 | $-07\arcdeg$ | this work; Spurný et al. (2017) Olech et al. (2017)
2022 | $+17\arcdeg$ | upcoming return
Table 1: Predicted returns of the Taurid Swarm. Updates for recent years are
published at the website
https://www.cantab.net/users/davidasher/taurid/swarmyears.html, accessed May
16, 2017.

Jenniskens et al. (2016b) have identified this shower in 2010 - 2013 CAMS data
as #628 in the IAU Working List of Meteor Showers, and called it the s-Taurids
(IAU code STS). We note that the ”new stream” of Spurný et al. (2017)
corresponds to the same IAU #628. Hereafter meteor showers IAU #2 (codenamed
STA) refers to the ”regular” Southern Taurids, IAU #628 (codenamed STS)
designates the resonant Southern Taurid branch (s-Taurids), and the Southern
Taurid Complex encompass members from both sub-streams.

Spurný et al. (2017) outlined a correlation between size and strength: larger
bodies among the 2015 Taurids tend to be more fragile. If so, that would imply
that metre-sized objects would break at such high altitudes in the Earth’s
atmosphere that they might be recognised in satellite observations. More
recently, Borovička & Spurný (2020) found from a sample of 16 studied Taurid
fireballs that the meteoroids $>10$ cm in size had low tensile strength, less
than 0.01 MPa, and a density less than 1 g cm-3. Smaller meteoroids contain a
higher fraction of materials up to 0.3 MPa in strength.

With an eye on the upcoming 2022 return of the s-Taurids, we present in this
paper observations of the enhanced 2015 Taurid fireball activity as observed
by the Desert Fireball Network (DFN) in Australia and by the Cameras for
Allsky Meteor Surveillance (CAMS) network in California. We investigate
changes in the orbital elements along Earth’s path, the stream’s semi-major
axis distribution and the particle size distribution of the stream in order to
better understand its relationship to comet 2P/Encke and other Taurid Complex
parent bodies.

##  2 Data and methods

DFN and CAMS survey meteoroid impacts at different sizes ranges: CAMS has the
sensitivity to detect large numbers of small millimetre to centimetre size
grains, while the DFN takes advantage of a large collecting area to catch
centimetre to decimetre scale meteoroids, at the cost of lower sensitivity.
When it comes to observing a bright meteor shower like the Taurids, the two
systems complement each other well.

###  2.1 DFN

Figure 1: DN151104_01: a 2.6 s s-Taurid observed at Hughes siding in the
Nullarbor plain, near the Magellanic clouds. This is a crop of the original
all-sky picture. The meteoroid experiences a catastrophic fragmentation at 74
km altitude, shortly before the meteor faded.

In 2015, the Australian Desert Fireball Network covered 1.5 million $km^{2}$
of sky viewing area, established around $30\arcdeg$ S latitude (Howie et al.,
2017a). Each DFN observatory comprises of a high-resolution still imaging
system: a 36 Mpixels digital camera (Nikon D800, D800E, or D810), associated
with a Samyang 8 mm f/3.5 fish-eye lens, taking 25 seconds exposures at 6400
ISO. In 2015 all observatories operated with these settings. The field of view
of the cameras is all-sky, except for a crop of 10 degrees on the horizons of
long sides of the sensor (usually North and South). The pixel size is 119
seconds of arc in the center, decreasing towards the edges (87 seconds of arc
at $5^{\circ}$ elevation). The cameras are sensitive to stellar magnitude 0.5
for meteors (7.5 for stars), and reliably detect meteors that are brighter
than apparent magnitude -1.5 for $>0.9$ second.

Meteor events are automatically detected in the images by the software
procedures described by Towner & et al. (2019). Astrometric measurements are
performed in the same manner as described by Devillepoix et al. (2018),
resulting in measurements precise down to 1-2 minutes of arc. The
triangulation of meteor trajectories are performed using a weighted straight
line least squares approach, similar to the one described in Borovička (1990).
In order to get an appropriate entry velocity for the meteoroid, an extended
Kalman smoother is applied to the positional data, throughout the visible
bright flight (Sansom et al., 2015). This method also yields statistical
uncertainties that encompass both model errors and measurement errors. These
results are crucial for initialising orbit determination as orbital
parameters, like the semi-major axis and eccentricity, are very sensitive to
the errors in initial velocity. The heliocentric orbit of the meteoroids are
determined using a backward integration from the start of the visible bright
flight. The meteoroid is back-tracked through the upper layers of the
atmosphere, and out of the sphere of influence of the Earth to a distance of
one Hill sphere (Jansen-Sturgeon et al., 2019). Uncertainties on the orbital
parameters are computed using a Monte Carlo method based on the uncertainties
of the first velocity vector observed.

The DFN data reduction pipeline uses aperture photometry on the fireball track
to calculate brightness. Doing photometry on the reference stars used for
astrometry yield instrumental zero point of each camera, accounting for
extinction and vignetting. The fireball brightness is converted into
magnitudes by accounting for the different exposure times: the effective
exposure time for stars is typically 11.2 s (25 s exposure modulated by the
liquid crystal shutter), and 0.06 s or 0.02 s for a fireball shutter break
(see Howie et al. (2017b) for details on the action of the liquid crystal
shutter). Apparent magnitude is converted to absolute (for constant distance
of 100 km) after triangulation, using the observation range. The main
limitation on this technique is the saturation of the sensor, which typically
happens when the fireball exceeds apparent magnitude -6. Blooming of the trail
enables brightness measurements out to about -10 magnitude.

The main use of photometric measurement in the present study is to calculate
meteoroid strength and to get a zero-order mass estimate. As detailed by Brown
et al. (2016), the peak brightness instant of a fireball is a good indicator
of catastrophic fragmentation, and therefore a reasonable proxy for
calculating a bulk tensile strength for the entering body. This method is more
robust to instrumental bias than the PE criterion introduced by Ceplecha &
McCrosky (1976), and has the advantage of being inferred directly from
observable parameters (no mass calculation involved). We therefore use the
following relation from Bronshten (1981) to calculate tensile strength $S$:
$S=\rho_{atm}v^{2}$, where $\rho_{atm}$ is the density of the atmosphere
estimated using the NRLMSISE-00 atmospheric model (Picone et al., 2002). $v$
is the velocity at that instant calculated by the Kalman smoother described by
Sansom et al. (2015). The main limitation of the method comes from the
uncertainty on the instant of peak brightness, dominated by the sampling rate
(10 Hz), which translates into 2 km of altitude for the average Taurid, or a
$\simeq 1.3$ factor in strength.

Thanks to the continental scale of the network, operational and weather biases
are mitigated by the large collecting area and observation time. However a
consequence of this is that precisely determining the surveying area probed by
the instrument is difficult. While calculating probing area as a function of
time may be done accurately and relatively easily when a small number of
narrow angle optics are used, such as described in Blaauw et al. (2016). Even
at a basic level, this kind of work with all-sky cameras spaced on a
continent-scale network, is more tricky, and de-biasing the DFN dataset to get
precise fluxes will be the subject of a future paper.

The DFN observatories, combined with the data reduction methods described
above, have led already to multiple meteorite recoveries: Creston (Jenniskens
et al., 2019), Murrili (Sansom et al., 2020), Dingle Dell (Devillepoix et al.,
2018), as well as 3 more recent (not yet published) recoveries. These
successes in precisely pinpointing the location of meteorites are good
indications that the data reduction process is free of major systematic
issues.

###  2.2 CAMS

The main goal of CAMS is to map the presence of meteor showers of +4 to -5
magnitude meteors throughout the year. In November 2015, CAMS networks had
been established in California, Arizona, Florida, the BeNeLux, and New
Zealand. Most CAMS networks are on the northern hemisphere, but they
experienced a relatively small number of cloudy days that year. CAMS methods
are described in detail in Jenniskens et al. (2011). In brief, CAMS utilises a
network of analog low-light video cameras, mostly Watec Wat902H2 Ultimate
cameras with $30\arcdeg\times 20\arcdeg$ field of view each and +5.4 stellar
limiting magnitude. Customised software detects the meteors, calibrates the
background star field to obtain astrometric positions, and then combines such
data from two or more stations to triangulate the meteor trajectory. CAMS
yields more than 100,000 meteoroid orbits per year, and has proven to be a
very efficient tool for studying meteor showers and linking them to possible
parent objects (Jenniskens et al., 2016b, c, a).

The high detection rate of meteors not assigned to showers by (Jenniskens et
al., 2016a), with geocentric entry speed $<$ 35 km/s from the antihelion
source at the same time as the Taurid showers, provides a baseline of sporadic
meteor shower activity that can be used to calculate the effective observing
time due to weather. The CAMS flux data were de-biasing by assuming a constant
sporadic flux during the s-Taurid activity period. The main CAMS networks are
situated at a latitude of $\phi=+37\deg$, where the Southern Taurid radiant is
up almost all night in early November and the mean altitude of the Southern
Taurid radiant is $hR\simeq 40\deg$. This results in a correction factor of
$1/sin(hR)=1.35$ to get the equivalent zenithal hourly rate. For scaling the
distribution we use the flux density of Grün et al. (1985), $f_{G}=6.85\times
10^{-8}>1\,\mbox{g meteoroids m}^{-2}\,\mbox{year}^{-1}$, and the correction
factor between interplanetary and top of the atmosphere $S=0.67$ be of
Moorhead et al. (2019). From this, we can calculate the influx of s-Taurid on
the Earth as:

$N(\\#628>1\,\mbox{g impacts on
Earth})=\frac{n}{m}*\frac{1}{\sin(hR)}*f_{G}*S*2*\Delta\lambda_{\odot}*\mbox{X-section}_{\mbox{Earth}}$

In this formulation $\Delta\lambda_{\odot}$ is the exposure time to the shower
as observed by CAMS, and the factor 2 is there to compensate that a surface at
top of the atmosphere is effectively twice the collecting area of the model
randomly tumbling plate of Moorhead et al. (2019). In relation to a meteoroid
stream, the Earth’s exposure to the stream can be effectively represented as a
cross-section area defined by its radius.

The reported flux values are limited to a 1 g threshold mass using the
observed magnitude distribution. The count of all sporadic meteors with the
25-30 km/s entry speed of Taurids was assumed to be exponential in shape of
this magnitude interval, from which a detection probability function was
derived by fitting an exponential slope to the bright-end of the magnitude
distribution and then dividing observed counts by the fit-predicted count. The
fraction of completeness for magnitudes -1 and up was: P(m) = 1.00, 0.80 $\pm$
0.02, 0.37 $\pm$ 0.01, 0.093 $\pm$ 0.003, 0.014 $\pm$ 0.002, 0.0011 $\pm$
0.0002, and $\sim$5e-6. This probability function was then applied to the
detected count of shower meteors to derive the magnitude size distribution of
different Taurid Complex component showers.

Figure 2: Detected meteors geocentric entry speed as a function of solar
longitude. STS activity years (left) are separated from other observation
years (right). In DFN data, fireballs identified as Southern Taurids are
marked in black against grey background fireballs. While the STS component of
the Southern Taurids, recognised by its strong date-speed linear relationship,
is visible in the meteor data (CAMS, top left), it is even more obvious at
fireball sizes (DFN, bottom left).

##  3 Results

The 73 measured DFN orbits from the Southern Taurid Complex in 2015 are
provided as an appendix to this manuscript. The CAMS-derived Southern Taurid
Complex orbits were released as part of the 2013 – 2016 CAMS data release and
can be accessed via the project website (http://cams.seti.org) and via the
Meteor Data Center. In 2015, CAMS detected N = 10,942 Southern Taurids (N =
177 $>1$ g) between $\lambda_{\odot}\in[213.19$-$234.25]\arcdeg$. In the same
period, 131,230 (Nspo = 1193 $>1$ g) sporadic meteors were recorded.

###  3.1 Comparison of s-Taurids with regular Southern and Northern Taurids

The s-Taurid shower stands out well from other Southern Taurid complex meteors
by their geocentric speed. Fig. 2 plots the geocentric speed and time (solar
longitude) of all meteors associated with the Southern Taurid complex in both
the CAMS (top) and DFN (bottom) datasets. Vertical white bands are due to
cloudy weather with less than complete coverage. The data are split in two
groups: the outburst years of 2012 and 2015 (Table 4), and the no-outburst
years of 2010, 2011, 2013, 2014, and 2016. The 2012 encounter with the
s-Taurids is $\Delta_{M}=35\arcdeg$ from the centre of the resonance according
to the model of Table 1. Hence, the weak detection of the s-Taurids in 2012 by
CAMS implies an extend of this component until at least mean anomaly
$35\arcdeg$, in agreement.

The outburst years show a component that produces a narrow range of geocentric
entry speed at any given solar longitude, with a strong change in the speed as
a function of time. This component is only weakly present in non-outburst
years (Fig. 2). This component was earlier identified as shower #628 , the
s-Taurids (IAU code STS). The period of activity for this component is
$\lambda_{\odot}\in[213,234]\arcdeg$.

The presence of this STS component is also evident in the 2015 DFN data (Fig.
2), despite a lower number of orbits, as the STS stream largely dominates the
Southern Taurid activity at fireball sizes. The change in velocity with solar
longitude translates into a strong increase of perihelion distance with
increasing solar longitude and a decreasing eccentricity. The semi-major axis
and inclination of the orbits remain nearly constant, as does the longitude of
perihelion.

Fig. 3 shows the de-biased STS rates for CAMS, along with that of the
remaining STA and NTA streams. The rates are normalised to that of all
sporadic meteors with speeds $<35\,\mbox{km s}^{-1}$. This ensures that the
total sporadic count reflects the observing conditions during that part of the
night when the antihelion source is best observed.The sporadic apex and
Toroidal sources have been removed from the count. The 2015 STS count was
compared to the sporadic meteor rate in 2015 only. The multi-year de-biased
distribution produced better defined shower activity profiles than early
results in Jenniskens et al. (2016c). The shower components identified in
Jenniskens et al. (2016a) are still present. The STA and NTA shower profiles
are different, an indication that the nodal line of individual meteoroid
orbits did not fully rotate, as earlier pointed out.

###  3.2 Size frequency distribution of the #628 STS stream

Fig. 4 shows the distribution of peak magnitudes in 0.5 magnitude intervals
for CAMS-detected NTA, STA and STS meteors. The STS population is
significantly more skewed towards brighter meteors. The cumulative mass-
frequency distribution as observed by CAMS (Fig. 8) can be expressed as
$N(>m)=am^{-b}$ with $a=1.42\times 10^{5}$ and $b=0.94$ when expressed in
grams. This is representative of the total influx of s-Taurids during the 2015
encounter.

The annual Southern and Northern Taurids have differential magnitude indices
of $\chi\simeq 3.0$ (Fig. 3), this is close to the typical value for JFC
material ($\chi=3.29\pm 0.09$, as determined by Jenniskens et al. (2016a)). On
the other hand s-Taurids have a much shallower distribution with $\chi=\sim
2.0$ (assuming a sporadic $\chi=3.4$). This gives a differential mass index
for the observable stream of $s=1.75$ ($s=1+2.5\log(\chi)$).

Figure 3: De-biased CAMS shower rates relative to that of sporadic meteors
$<$35 km/s for shower 628 (STS), the Southern Taurids (STA) and the Northern
Taurids (NTA), as a function of solar longitude. Figure 4: Peak magnitude
frequency distribution for Southern Taurids substreams #2 STA, #17 NTA and
#628 STS. Resonant Taurids (STS branch) are generally larger than regular
Southern Taurids (STA).

The observed size distribution confirms that the s-Taurids are relatively rich
in large meteoroids. Indeed, a study by Soja et al. (2011) on radar meteor
observed by the Canadian Meteor Orbit Radar (CMOR) in 2005 (typical observed
mass of $10^{-7}$ kg, which roughly corresponds to optical magnitude +7),
failed to identify the 7:2 resonance from regular Southern Taurids. They
discuss that this is partly due to the poor constraints the radar observations
put on the velocities (and therefore the semi-major axes), so it is not
possible to distinguish STSs from STAs dynamically.Therefore unless the STS
outburst is strong enough to significantly skew the overall Southern Taurids
rates, it is not detectable. Soja et al. (2011) do no provide an upper
constraint on the STS/STA activity, but even without hard numbers this
analysis confirms the trend shown in Fig. 4: the STA branch dominates the STS
branch at the low mass end ($Mv_{max}>-4$).

Figure 5: s-Taurids height of peak brightness as a function of brightness. DFN
magnitudes may be slightly underestimated because of saturation issues.

Beyond CAMS data, towards fireball sizes, flux density data for this stream
becomes more scarce. The DFN and EN fireball networks do not yet have time-
area de-biasing information to calculate flux densities. The masses reported
by (Spurný et al., 2017) give an idea of the slope of the distribution at
magnitudes below -9, where the EN sample appears to be complete (Figure 8).
Although it is apparently more shallow than the slope calculated by CAMS, the
numbers are so small that the extrapoplated flux agrees within 2 error bars (2
sigma). Even at these bright magnitudes there may still be an effect of the
brightness-dependent variation in effective covering/reporting: the brighter
the bolide, the further it can get detected and studied.

###  3.3 Strength of the meteoroids in the #628 STS stream

Figure 5 shows the altitude of peak brightness as a function of peak meteor
magnitude. The result shows that larger meteoroids penetrate deeper in Earth’s
atmosphere before reaching peak brightness, as expected. Among CAMS-detected
visual meteors, that is a fairly continuous trend. However, at the larger
fireball sizes, meteoroid penetration enter a strength dominated regime. The
transition into the strength-dominated regime occurs at about -7 magnitude. In
the strength-dominated regime, the altitude of peak brightness is independent
of mass, although there is a weak trend that the largest meteoroids are weaker
than the smaller meteoroids near this transition. All s-Taurids experience
their peak brightness above 60 km altitude (Fig. 5), and do not survive below
50 km altitude. The deepest penetrating fireball had a minimum height of 54.5
km, while the average end height of the DFN fireballs was 67.2 km (see suppl.
mat. table). This is consistent with the results of Spurný et al. (2017).

Figure 6: Ecliptic orbit plot of all Southern Taurids observed by the DFN in
2015 (pink), and the #628 branch (blue).  Figure 7: Semi-major axis
measurements (with $1\sigma$ uncertainties error bars) of all Southern Taurid
fireballs observed by the DFN 2015. Most are significantly higher than typical
Southern Taurids, compatible with the a 7:2 mean-motion resonance with Jupiter
(centered on 2.256 AU).

###  3.4 Semi-major axis of the fireball orbits

Figure 6 is an ecliptic orbit plot of all Southern Taurids observed by the DFN
in 2015. The Figure shows that most observed Taurid fireballs clustered in a
tight stream with constant longitude of perihelion (all ellipses pointed in
the same direction). These s-Taurids are shown in blue. This stream is highly
stratified: they form a series of more ore less concentric ellipses for
fireballs detected at different solar longitude along the Earth’s orbit.
Unlike most meteoroid streams, this stream appears to be more narrower at
aphelion than at perihelion. The dispersion of perihelion distances (q) of the
blue orbits is 8.9 percent (one standard deviation), while the aphelion
distance (Q) is dispersed by only 2.4 percent, and the semi-major axis (a) by
2.1 percent. a and Q are tightly correlated, a and q are not. The stream
approaches the orbit of Jupiter near aphelion, suggesting that the secular
perturbations responsible for the observed dispersion are strongest near
aphelion, not near perihelion.

Figure 7 plots the semi-major axis of the 2015 Taurid fireballs measured in
the DFN network as a function of solar longitude (time in the year). The DFN-
derived orbits during solar longitudes 217.5 and 227.5 show a clear
concentration of semi-major axis values around the mean semi-major axis a =
$2.234\pm 0.007$ AU with a standard dispersion of 0.041 AU. The mean
calculated error in the semi-major axis values is $0.034\pm 0.014$ AU, in good
agreement with the observed dispersion if all these orbits have exactly the
same semi-major axis of a = 2.2563 AU corresponding to the 7:2 mean-motion
resonance with Jupiter (dashed line). This result confirms earlier conclusions
from EN fireball observations reported by Spurný et al. (2017) that the
meteoroids appear to be trapped in this resonance, and demonstrates the
accuracy of the semi-major axis calculations. Most of the observed dispersion
in semi-major axis is due to measurement error. However, there is a small
systematic error of $-0.022\pm 0.007$ AU.

The fireballs shown in pink are outside the main dispersion. Most have
slightly smaller semi-major axis, while three orbits just reach the orbit of
Jupiter. 52 of the observed trajectories have a semi-major axis within 2 sigma
from the resonant value. 21 have not. Surprisingly, the once that have not
scatter around the time of the outburst over 216.5 to 231.7 degrees solar
longitude (CAMS has 212 to 235 degrees range, see below), while the once that
are within 2 sigma from the resonant value scatter over the whole observing
interval of 207.7 to 255.9 solar longitude. Hence, whether or not the
trajectories scatter around the resonant value is not a mark of the s-Taurids,
it is a mark of the Southern Taurids as a whole.

Some of the pink orbits may represent measurement errors in the initial
velocity determination. Or they are a more perturbed population of meteoroids
that possibly already experienced some changes in semi-major axis due to
encounters with the terrestrial planets. If so, they are likely part of the
background Southern Taurids.

Figure 8: Cumulative mass-frequency distribution. CAMS $>1$ g meteors left is
fitted based on the 2015 data (see Sec. 3.2). The s-Taurid 2015 data of Spurný
et al. (2017) is presented in green, with the event frequency scaled to match
CAMS’ at 50 grams. Note that the different slope for this data may not be real
and could come from a brightness-dependent variation in effective covering
area. The right-hand side estimate comes from 3 likely large s-Taurids
observed by the USG sensors in 2005 and 2015.

###  3.5 The metre-size population

Spurný et al. (2017) first pointed out that the stream contains metre-sized
asteroids. Here, we will attempt to quantify this. The US government (USG)
satellite sensors detect m-scale impactors in Earth’s atmosphere over the
entire planet as a collecting area, or if a meteoroid stream is involved
approaching from a given direction that collection area is the projected Earth
surface to that stream. These data are reported online on the NASA JPL
fireball website111https://cneos.jpl.nasa.gov/fireballs/, accessed May 16,
2017. Even with this large a collection area, the chance of detecting impacts
is small. Figure 8 shows the cumulative mass-frequency distribution from CAMS
and DFN data. The USG detected bolides are about -18 magnitude and brighter
(Tagliaferri, 1994). That leaves a large gap without de-biased data.

Extrapolating the mass-frequency distribution established in Sec. 3.2, we
predict 0.37 meteoroid $>940$ kg impacting the Earth during the 2015 s-Taurid
episode. Indeed, the USG satellites detected no unusual number of fireballs in
late October and early November 2015. One bolide was detected on 2015-10-31,
one on 2015-11-02 and one on 2015-11-13. No velocity components are reported,
so we do not know the radiant or speed of these bolides.

Table 2: 14 high altitude (¿60 km) meteoroid airbursts observed by the USGS. No velocity information was provided for the events presented here. Highlighted rows show events that fall within the STS activity period. The 4 events at the bottom are excluded for statistical significance reasons (see in the text). Size is calculated from the energy, assuming the velocity is equal to the mean STS velocity observed by the DFN at the same given solar longitude (see Suppl. Mat. Table), and the 1600 $\mbox{kg m}^{-3}$ bulk density estimated by (Babadzhanov & Kokhirova, 2009). Peak brightness time | $\lambda_{\odot}$ | Latitude | Longitude | Altitude | Total Impact Energy | Size
---|---|---|---|---|---|---
ISO UTC | $\arcdeg$ |  $\arcdeg$ (N+) |  $\arcdeg$ (E+) | km | kilotons TNT | m
2015-10-31 11:34:30 | 217.51 | 9.0 | -138.0 | 71.0 | 0.29 | 1.5
2015-06-10 17:43:03 | 79.32 | -11.5 | -161.9 | 61.1 | 1.0 |
2013-08-12 18:08:02 | 140.00 | -34.4 | 118.2 | 66.6 | 0.15 |
2012-02-12 05:25:52 | 322.72 | -31.7 | 54.9 | 61.0 | 0.41 |
2011-01-21 15:11:43 | 301.07 | 18.9 | -44.6 | 61.0 | 0.23 |
2010-12-09 02:54:07 | 256.76 | -54.5 | -169.7 | 66.0 | 0.2 |
2005-12-24 15:30:26 | 272.85 | -54.0 | 17.3 | 66.0 | 0.51 |
2005-11-02 07:04:32 | 219.89 | 33.9 | -154.9 | 68.5 | 0.11 | 1.1
2005-11-02 05:16:47 | 219.81 | 22.9 | -123.8 | 74.0 | 0.21 | 1.3
2005-04-06 01:30:24 | 16.28 | -42.7 | 154.6 | 70.0 | 0.1 |
*2011-08-04 07:25:57 | 131.44 | -40.7 | -86.7 | 63.0 | 0.098 |
2004-01-02 04:27:59 | 281.05 | -28.2 | 3.2 | 63.0 | 0.39 |
1999-06-25 06:27:41 | 93.30 | 50.0 | 121.0 | 69.0 | 0.37 |
1999-01-02 18:25:51 | 281.93 | 47.0 | 103.0 | 65.0 | 0.12 |

However, there are data from multiple years of observation now. If any Taurids
are among these impactors, we expect their penetration depth to be relatively
shallow based on the size-dependence shown in Figure 5.The observed cm-dm
sized meteoroids by CAMS, DFN, and EN show no significant decrease in peak
height as sizes get larger.

The USG data only include the altitude of peak brightness. We started by
filtering the USG dataset by height of maximum brightness $>$60km as a first
pass to identify weak cometary impacts, as STS observed by the DFN break up
$>66$ km (Fig. 5). We note that the stated peak brightness altitude from the
sensors is generally reliable to about $\pm$ 4 km, as shown by Brown et al.
(2016), and that these altitudes are reported for most events from the
beginning of 2005 onwards. Detections are made at night, but also in daytime.
As mentioned by Devillepoix et al. (2019), the typical energy report limit is
0.1 kT TNT, therefore we exclude event 2011-08-04 07:25:57 (0.098 kT reported
yield) from our analysis for detection significance issues. We are left with
10 significant events that fit the height criterion (Table 2). However, there
are no velocity vectors reported for these events, so there is no direct
dynamic link between any of these and the Taurid complex.

Nevertheless, 3 out of these 10 very weak meteoroids fall in the STS activity
period, and even more remarkable they happen in 2005 and 2015, two years
during which strong STS activity has been reported and are predicted by the
model of Asher & Izumi (1998) (Table 1). In 2005, two events occurred in short
succession. All three events suggest the largest fragments in this stream are
at solar longitude $[213,234]\arcdeg$. This combined with data in Fig. 3,
these USG bolides occurred during the STS activity period. We confirm that
these 3 events happened while the Southern Taurid radiant was above the local
horizon.

Table 3: Poisson test on the significance of the impact rate increase of metre-sized weak material (peak brightness $>60\,km$) hitting the Earth observed by the USGS during STS outburst episodes ($\lambda_{\odot}\in[213,234]\arcdeg$). Ranges given are at $2\sigma$ confidence. The influx increase factor during an STS outburst is $[2.1,46]\times$. population | surveyed years | observed events |  $\lambda_{\odot}$ integrated ($\arcdeg$) | rate ($Earth^{-1}\lambda_{\odot}^{-1}$)
---|---|---|---|---
weak impactors population | [2005-2016] | 10 | 3960 | [0.001 - 0.005]
probable STS | 2005, 2008, 2012, 2015 | 3 | 84 | [0.007 - 0.1]

Can these bolides signify a detection of the s-Taurids? Considering the very
low number of events observed, we need to build a statistical test to assess
the significance of this apparent rate increase during a swarm episode. Let us
test the hypothesis $H_{1}$: ”An airburst from weak material (main explosion
$>60$ km) is more likely to happen during a STS activity period” against the
null hypothesis $H_{0}$: ”No increase in the rate of impacts from weak bodies
can be observed during a STS activity episode”. We define a STS swarm episode
as a period that happens on a year predicted by the model of Asher & Izumi
(1998), within the interval where the USG sensors have consistently observed
airbursts heights (2005, 2008, 2012, 2015), and within the activity period
observed by CAMS (solar longitude $\in[213,234]\arcdeg$). We use the
rateratio.test R package 222https://cran.r-project.org/package=rateratio.test,
that implements the methods described in Fay (2010) to carry out the
statistical test. At 95% confidence, the background weak metre scale impact
rate is $[0.001,0.005]$, compared to
$[0.007,0.1]\,Earth^{-1}\lambda_{\odot}^{-1}$ when
$\lambda_{\odot}\in[213,234]\arcdeg$, which corresponds to a weak impactors
influx increase of $[2.5,55]\times$ (see Table. 3 for full test test data and
results). The small $p-value=0.004$ shows strong evidence against the null
hypothesis (at 95% confidence).

Although we cannot definitely link any individual events with the Taurids, the
apparent rate increase in metre-scale weak impactors during the STS outburst
activity is statistically significant, and we can say that during an STS
outburst episode the Earth is more likely to get impacted by a metre-scale STS
than a sporadic meteoroid of the same size. Over an s-Taurid episode, the
number of $>0.1$ kT TNT of s-Taurid impactor is $[0.15,2.1]$ (Fig. 8).

Adding this detection rate to the overall picture shows that the meteoroid
size distribution does not change down to metre size scale (Fig. 8). This
result implies that the #628 STS stream contains some of the largest
meteoroids known to any cometary meteor shower.

Finally, it is possible that the USG satellite detections do not represent all
large bolides in Earth’s atmosphere.The European Network detected one
superbolide during the 2015 outburst called EN311015_180520 (Spurný et al.,
2017). The observation of this 1300 kg bolide over a superbolide coverage area
of roughly $0.1\%$ Earth is statistically unlikely, but not impossible (Fig.
8). The EN311015_180520 superbolide (0.17 kT TNT total kinetic energy) should
have been well within the detection range of the USG sensors, but this bolide
was not reported. A single mis-match is not indicative of a particular issue
as the USG sensors are known to have had as low as 70-80% Earth coverage in
the past (Brown et al., 2002). The USG sensors s-Taurid flux could have been
underestimated by a factor of 2 considering both 2008 and 2012 were taken into
account for the USG clear-sky calculations (Sec. 3.5), as these 2 years were
quite distant from the resonance centre. It could mean that the metre-scale
s-Taurid is a factor of $~{}2$ larger than what we calculated here. That would
still be consistent with a constant mass distribution index from cm to metre
scale (Fig. 8).

##  4 Discussion

###  4.1 Nature and origin of the s-Taurids

The low magnitude distribution index ($\chi=2.0$) and small differential mass
index ($s=1.75$) is atypical of most JFC showers. Such values point to a
collisionally relaxed population, with equal combined cross-section area in
each magnitude bin (s = 1.67), or a collisional cascade where each meteoroid
is broken by a mass just big enough to do so (s = 1.83). This points to a very
gentle collision process such as would be experienced during a cometary
breakup of relatively strong material with intrinsic low-s size distribution.
High velocity collisions in the interstellar medium or other aging processes
like grain charging and thermal cycling did not significantly affect the size
distribution index of this population of meteoroids. That means that the
stream is relatively young and was born from relatively strong cometary
material. Weak cometary material breaks into very steep distributions towards
small particles (Jenniskens, 2006).

The unusual large number of shower fireballs detected by DFN and EN points to
the presence of large meteoroids in this stream. Continuation of the particle
size distribution to larger sizes implies a population of metre-sized objects
in this stream that appears to have been detected in USG satellite
observations. The presence of such large bodies in the stream is consistent
with the material being relatively strong for cometary material in general.
This stream is currently a major contributor to the overall population of
large weak meteoroids. If the USG statistics are representative of larger
cometary impact hazards, the s-Taurids dominate the flux when they are active,
increasing the impact risk by $[2.5,55]\times$ ($2\sigma$), and overall they
represent a significant fraction of all large cometary impactors, even though
their activity period is only a few weeks every couple of years!

Our measured DFN fireball mean semi-major axis of $2.234\pm 0.007$ AU is 0.019
AU higher than the semi-major axis of 2P/Encke, but 0.022 AU lower than the a
= 2.2563 AU corresponding to the 7:2 mean-motion resonance with Jupiter. It is
also 0.031 AU lower than the current semi-major axis of 2015 TX24. Natural
oscillations of semi-major axis are about 0.03 AU in this part of the asteroid
belt (Nesvorný & Morbidelli, 1998), so the motion of all objects will be
affected by the mean-motion resonance. If the breakup happened in the
resonance with small relative ejection velocities, is is likely the resonance
prevented the dispersion of the dust by avoiding Jupiter’s presence at
aphelion when the dust was there.

Table 4: Proposed parent bodies for the s-Taurids. object | epoch | $a$ | $e$ | $q$ | $i$ | long. ascen. node | arg. peri. | long. peri.
---|---|---|---|---|---|---|---|---
| TDB | AU |  | AU | $\arcdeg$ | $\arcdeg$ | $\arcdeg$ | $\arcdeg$
2P/Encke | 2015-08-04.0 | 2.2152 | 0.8483 | 0.3360 | 11.781 | 334.568 | 186.547 | 161.115
2003 WP21 | 2020-12-17.0 | 2.2620 | 0.7849 | 0.4866 | 4.295 | 37.654 | 124.030 | 161.390
2004 TG10 | 2020-12-17.0 | 2.2334 | 0.8620 | 0.3083 | 4.183 | 205.073 | 317.381 | 162.454
2005 UR | 2005-10-26.0 | 2.2492 | 0.8818 | 0.2660 | 6.935 | 20.030 | 140.477 | 160.507
2005 TF50 | 2020-12-17.0 | 2.2730 | 0.8692 | 0.2972 | 10.725 | 0.564 | 159.962 | 160.526
2015 TX24 | 2020-12-17.0 | 2.2647 | 0.8724 | 0.2890 | 6.049 | 32.827 | 127.151 | 159.978
s-Taurids (DFN) | 2015-11-05.1 | 2.237 | 0.847 | 0.358 | 5.45 | 42.72 | 115.70 | 158.31

Spurný et al. (2017) argued that the s-Taurids are the product of
fragmentation event (of 2004 TG10?) at about 3.6 AU distance from the Sun,
where the fireball orbits have lowest dispersion, with relatively high
ejection speeds of 1.5 km/s. The observed asteroids 2005 TF50, 2015 TX24 and
2005 UR (and 2004 TG10) were created in that event and now have evolved along
the rotation of the nodal line, now located 2000, 2300 and 2400 yr in rotation
behind 2004 TG10. Material not trapped in the 7:2 mean-motion resonance has
since been lost.

Figure 9: Orbital elements of #628 meteoroids observed by DFN (black dots) and
EN (grey dots, Spurný et al. (2017)), put in context with the discussed
possible parent bodies for the stream (Table 4).

That high ejection speed of 1.5 km/s is contrary to the gentle breakup
conditions implied by the particle size distribution we measured in this
paper. It would also suggest that much of the material was ejected into orbits
outside of the mean-motion resonance and material would still be dispersing
rather quickly along mean anomaly over time. Instead, we see that dust is
confined in a narrow range of mean anomaly. The best handle on age comes from
the work by Whipple & El-Din Hamid (1952) and Olech et al. (2016) who found
that individual fireball orbits originated from a common orbit about 1,500
years ago. However, if the mean-motion resonance is involved, this age may be
an upper limit only.

On closer inspection, we find that the change of argument of perihelion with
node does not align all three bodies (Figure 9). As noticed before by Spurný
et al. (2017), the longitude of perihelion is not quite constant in the
s-Taurids stream. Instead, the trend of argument of perihelion points directly
at asteroid 2015 TX24, which is only 3.5 degrees further in node than the
range of DFN fireballs observed. A few EN fireballs cover the node of 2015
TX24. 2025 TX24 is also close in position to the nodal dependence seen with
perihelion distance, eccentricity and inclination, but those parameters can
scatter more easily and that difference may merely reflect the change in
orbital elements needed to intersect Earth’s orbit.

Asteroid 2005 UR and 2005 TF50 have similar longitude of perihelion as 2015
TX24, but don’t fall along the trend line seen among the meteoroids. We
conclude that these larger asteroids are not simply fragments of this stream
as proposed by Spurný et al. (2017).

A likely scenario is that we are seeing recent activity from a breakup
involving surviving asteroid 2015 TX24. 2015 TX24 now has a semi-major axis of
2.2647 AU (Epoch 2020-Dec-17.0 TDB). That puts it within the normal semi-major
axis oscillation of $\pm 0.03$ AU from the resonance. Solar radiation pressure
will slightly increase the semi-major axis of the DFN meteoroids, but if the
ejection conditions were slightly lowering the semi-major axis, this could
have been compensated. It is possible that the change of longitude of
perihelion away from the node of 2015 TX24 is due the influence of the 7:2
mean-motion resonance. Presumably, the further the meteoroid node now is from
2015 TX24, the stronger the influence of the resonance. The precision of the
semi-major axis is not good enough to verify that. If so, that could mean that
the breakup happened rather recently, perhaps as recently as a few centuries
ago.

This supports a model for the Taurid Complex showers that involves an ongoing
fragmentation cascade of comet 2P/Encke siblings that were created following a
breakup some 20,000 years ago (Jenniskens, 2006). In this scenario, 2015 TX25
broke with 2005 UR and 2005 TF50 from a larger precursor body about 1,500
years ago, and in the past few centuries a further breakup of 2015 TX24
created the fragments observed as the s-Taurids today. Asteroid 2003 WP21 does
not belong to this group and was created earlier.

It is more difficult to understand how we could be seeing activity from comet
2P/Encke. In that case, the resonance must have more dramatically changed the
nodal line. Comet 2P/Encke would be expected to cause meteoroid activity
centered on $\lambda_{\odot}=224.6\arcdeg$, using method ”H” of Hasegawa
(1990), implemented by Neslusan et al. (1998). However, Encke now has nodes
close to perihelion near Mercury and aphelion in the asteroid belt. Comet
Encke’s orbit has changed its longitude of perihelion significantly over the
past two centuries. In 1769, the node was at 157.46°, Pi = 159.19°. In 2020,
the node is at 154.55°, Pi = 161.11°. That rate of change is about the same as
seen in the meteor stream. Around A.D. 1700, the longitude of perihelion of
Encke was the same as that of the core of the s-Taurids. If we are seeing
meteoroids ejected from 2P/Encke in the century around 1700 A.D., there must
have been a subsequent dramatic change of the nodal line.

It is not clear whether or not the periodic nature of the s-Taurids is due to
the 7:2 mean-motion resonance with Jupiter, other than preventing close
encounters with Jupiter. The mean semi-major axis of the meteoroids appears to
be related to that of its parent body. It is perhaps possible that the dust
was released with very low relative ejection speeds and has remained
concentrated in range of mean anomaly due to its young age. In particular, it
is interesting that Spurný et al. (2017) noted that the 1995 detected Taurid
fireballs did not quite have the orbital elements of the 2015 Taurids. They
had larger semi-major axes and smaller perihelia that did not change so much
with solar longitude. This could point to the presence of streams being more
dispersed but narrow, which occasionally wander in Earth’s path.

###  4.2 Meteorite dropping Taurids?

Brown et al. (2013) identified the Taurid showers as a potential source of
macroscopic meteorite dropping events if a large enough meteoroid enters
Earth’s atmosphere. We have seen that the STS branch contains large members,
do members of that population have a chance of surviving entry and falling as
a meteorite? Large s-Taurids behave like weak matter (Fig. 5). They experience
catastrophic disruption at very high altitudes ($>66$ km, see suppl. mat.
table). Their weak nature is not compensated by size, as Spurný et al. (2017)
noted the larger s-Taurids tend to be the weaker ones. The deepest penetrating
STS observed by the DFN ($DN151114\\_04$) is not visible below 52 km.
According to the criteria of Brown et al. (2013), which states that a height
of 35 km and velocity of 10 $\mbox{km s}^{-1}$ are approximate terminal
dynamical criteria for a given event to have a chance of producing a meteorite
fall, this is unlikely to produce a recoverable meteorite on the ground. The
two very bright STSs described by Olech et al. (2016); Spurný et al. (2017)
also terminate at high altitudes of 57.86 and 60.20 km.

Is this weakness a feature of all Southern Taurids? The deepest penetrating
Southern Taurid (MORP $\\#715$) described in the MORP dataset (Halliday et
al., 1996), only penetrates to 54.8 km. As outlined by Brown et al. (2013),
one of the EN fireballs in 1995 penetrated as deep as 30 km. Although this
fireball was tentatively linked with the Taurid Complex, no definite
association with either branch of the Taurids was reported, and the final
velocity was not reported either. More generally, to our knowledge there is no
report in the literature of a Southern Taurid that comes close to the terminal
parameter of Brown et al. (2013).

On the other hand, we have examples of Northern Taurids that are able to
penetrate much lower than the 50 km ceiling that Southern Taurids seem to hit.
For example, on October 9th, 2016, the DFN observed a Northern Taurid
penetrating as deep as 36.4 km, slowing down to 9.7 $\mbox{km s}^{-1}$: the
terminal parameters for this NTA are much closer to the cut-off criteria of
Brown et al. (2013), but still greater than required for a meteorite to
survive. Are we seeing inhomogeneities here in the original composition of
2P/Encke? Or are the stronger materials representative for older meteoroids
that survived the harsh conditions in the interplanetary medium?

##  5 Conclusions

The periodic outbursts of Taurid fireballs and visible meteors are from a
stream called the s-Taurids (IAU shower 628, STS). The shower stands out well
as a concentration of orbits in speed versus solar longitude diagram, with the
shower members having a strongly changing entry speed with position along
Earth’s orbit.

We have established the size frequency distribution for the s-Taurid stream.
Even at gram sizes, the stream shows a very shallow distribution with a
magnitude distribution index of 2.0 (differential mass distribution index of s
= 1.75), atypical of other JFC showers. The distribution appears to remain
unchanged up to metre-sized fragments.

The highly stratified structure of this stream, and the shallow size-frequency
distribution remaining constant over a large range in size, points to the
stream being the product of a gentle and relatively recent break up.

Because the meteoroids initially move on different orbits than 2P/Encke, the
breakup involved a different parent body. That body consisted of weak
material. The distribution of longitude of perihelion along Earth’s orbit
points to the stream having originated from surviving asteroid 2015 TX24 a low
albedo 0.07, $0.25\pm 0.04$ km sized ($H=21.5$) asteroid that is a good
candidate for a 2P/Encke sibling, together with 2014 TG10 and other such
bodies identified earlier. 2015 TX24, 2005 UR and 2005 TF50 may have broken
from a common body 1,500 years ago, with recent activity from 2015 TX24 now
producing the meteoroids detected at Earth as the s-Taurids.

Large metre-sized bodies survive in the s-Taurids, possibly because they
represent relatively strong cometary materials. During the s-Taurid #628
stream (STS) outburst years, the chance of the Earth being hit by a metre
scale weak meteoroid is enhanced by a factor of at least $[2.5,55]$. The Earth
encounters the STS stream on average every 5 years, therefore the STS stream
is responsible for as much as 20% of all weak (airburst $>60\,$km altitude)
metre scale bodies.

From the analysis of terminal parameters (heights and speeds) of the large
Taurid meteoroids observed by the DFN, a macroscopic meteorite from a Southern
Taurid stream seems unlikely, on the other hand we have examples of Northern
Taurids that approach the meteorite dropping terminal parameters discussed by
(Brown et al., 2013). Given their shallow penetration depth, large meteoroids
from the s-Taurids are unlikely to drop meteorites, but might generate dust
that can be collected in the atmosphere.

When the cloud of meteoroids next returns close to the Earth in 2022, the
Large Synoptic Survey Telescope (Ivezic et al., 2008) will be able up and
running and should be able to better constraint on the hypothetical population
of metre-sized s-Taurids. The recently commissioned Geostationary Lightning
Mapper (Jenniskens et al., 2018) should also be able to fill the observation
gap around the decimetre scale, and notably provide good estimate of the flux
density of STS meteoroids in this range.

This research is supported by the Australian Research Council through the
Australian Laureate Fellowships scheme, receives institutional support from
Curtin University, and uses the computing facilities of the Pawsey
supercomputing centre. The DFN data reduction pipeline makes intensive use of
Astropy, a community-developed core Python package for Astronomy (Astropy
Collaboration et al., 2013). PJ is supported by grant 80NSSC19K0513 of NASA’s
Emerging Worlds program and grant 80NSSC19K0563 of NASA’s Solar System
Workings program.

## References

  * Asher et al. (1993) Asher, D. J., Clube, S. V. M., & Steel, D. I. 1993, MNRAS, 264, 93, doi: 10.1093/mnras/264.1.93
  * Asher & Izumi (1998) Asher, D. J., & Izumi, K. 1998, MNRAS, 297, 23, doi: 10.1046/j.1365-8711.1998.01395.x
  * Astropy Collaboration et al. (2013) Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068
  * Babadzhanov & Kokhirova (2009) Babadzhanov, P. B., & Kokhirova, G. I. 2009, A&A, 495, 353, doi: 10.1051/0004-6361:200810460
  * Beech et al. (2004) Beech, M., Hargrove, M., & Brown, P. 2004, The Observatory, 124, 277
  * Blaauw et al. (2016) Blaauw, R. C., Campbell-Brown, M., & Kingery, A. 2016, MNRAS, 463, 441, doi: 10.1093/mnras/stw1979
  * Borovička (1990) Borovička, J. 1990, Bulletin of the Astronomical Institutes of Czechoslovakia, 41, 391
  * Borovička & Spurný (2020) Borovička, J., & Spurný, P. 2020, Planet. Space Sci., 182, 104849, doi: 10.1016/j.pss.2020.104849
  * Bronshten (1981) Bronshten, V. A. 1981, Moscow Izdatel Nauka
  * Brown et al. (2013) Brown, P., Marchenko, V., Moser, D. E., Weryk, R., & Cooke, W. 2013, Meteoritics and Planetary Science, 48, 270, doi: 10.1111/maps.12055
  * Brown et al. (2002) Brown, P., Spalding, R. E., ReVelle, D. O., Tagliaferri, E., & Worden, S. P. 2002, Nature, 420, 294, doi: 10.1038/nature01238
  * Brown et al. (2016) Brown, P., Wiegert, P., Clark, D., & Tagliaferri, E. 2016, Icarus, 266, 96, doi: 10.1016/j.icarus.2015.11.022
  * Ceplecha & McCrosky (1976) Ceplecha, Z., & McCrosky, R. E. 1976, J. Geophys. Res., 81, 6257, doi: 10.1029/JB081i035p06257
  * Clube & Napier (1984) Clube, S. V. M., & Napier, W. M. 1984, MNRAS, 211, 953, doi: 10.1093/mnras/211.4.953
  * Devillepoix et al. (2018) Devillepoix, H. A. R., Sansom, E. K., Bland, P. A., et al. 2018, Meteoritics and Planetary Science, 53, 2212, doi: 10.1111/maps.13142
  * Devillepoix et al. (2019) Devillepoix, H. A. R., Bland, P. A., Sansom, E. K., et al. 2019, MNRAS, 483, 5166, doi: 10.1093/mnras/sty3442
  * Drummond (1981) Drummond, J. D. 1981, Icarus, 45, 545, doi: 10.1016/0019-1035(81)90020-8
  * Dubietis & Arlt (2007) Dubietis, A., & Arlt, R. 2007, MNRAS, 376, 890, doi: 10.1111/j.1365-2966.2007.11488.x
  * Fay (2010) Fay, M. P. 2010, The R Journal, 2, 53
  * Froeschle & Scholl (1986) Froeschle, C., & Scholl, H. 1986, A&A, 158, 259
  * Grün et al. (1985) Grün, E., Zook, H. A., Fechtig, H., & Giese, R. H. 1985, Icarus, 62, 244, doi: 10.1016/0019-1035(85)90121-6
  * Halliday et al. (1996) Halliday, I., Griffin, A. A., & Blackwell, A. T. 1996, Meteoritics and Planetary Science, 31, 185, doi: 10.1111/j.1945-5100.1996.tb02014.x
  * Hasegawa (1990) Hasegawa, I. 1990, PASJ, 42, 175
  * Howie et al. (2017a) Howie, R. M., Paxman, J., Bland, P. A., et al. 2017a, Experimental Astronomy, doi: 10.1007/s10686-017-9532-7
  * Howie et al. (2017b) —. 2017b, Meteoritics and Planetary Science, 52, 1669, doi: 10.1111/maps.12878
  * Ivezic et al. (2008) Ivezic, Z., Axelrod, T., Brandt, W. N., et al. 2008, Serbian Astronomical Journal, 176, 1, doi: 10.2298/SAJ0876001I
  * Jansen-Sturgeon et al. (2019) Jansen-Sturgeon, T., Sansom, E. K., & Bland, P. A. 2019, Meteoritics and Planetary Science, 54, 2149, doi: 10.1111/maps.13376
  * Jenniskens (2006) Jenniskens, P. 2006, Meteor Showers and Their Parent Comets (Cambridge University Press)
  * Jenniskens et al. (2011) Jenniskens, P., Gural, P. S., Dynneson, L., et al. 2011, Icarus, 216, 40, doi: 10.1016/j.icarus.2011.08.012
  * Jenniskens et al. (2016a) Jenniskens, P., Nénon, Q., Gural, P. S., et al. 2016a, Icarus, 266, 384, doi: 10.1016/j.icarus.2015.11.009
  * Jenniskens et al. (2016b) Jenniskens, P., Nénon, Q., Albers, J., et al. 2016b, Icarus, 266, 331, doi: 10.1016/j.icarus.2015.09.013
  * Jenniskens et al. (2016c) Jenniskens, P., Nénon, Q., Gural, P. S., et al. 2016c, Icarus, 266, 355, doi: 10.1016/j.icarus.2015.08.014
  * Jenniskens et al. (2018) Jenniskens, P., Albers, J., Tillier, C. E., et al. 2018, Meteoritics and Planetary Science, 53, 2445, doi: 10.1111/maps.13137
  * Jenniskens et al. (2019) Jenniskens, P., Utas, J., Yin, Q.-Z., et al. 2019, Meteoritics and Planetary Science, 54, 699, doi: 10.1111/maps.13235
  * Madiedo et al. (2014) Madiedo, J. M., Ortiz, J. L., Trigo-Rodríguez, J. M., et al. 2014, Icarus, 231, 356, doi: 10.1016/j.icarus.2013.12.025
  * Moorhead et al. (2019) Moorhead, A. V., Egal, A., Brown, P. G., Moser, D. E., & Cooke, W. J. 2019, Journal of Spacecraft and Rockets, 56, 1531, doi: 10.2514/1.A34416
  * Neslusan et al. (1998) Neslusan, L., Svoren, J., & Porubcan, V. 1998, A&A, 331, 411
  * Nesvorný & Morbidelli (1998) Nesvorný, D., & Morbidelli, A. 1998, AJ, 116, 3029, doi: 10.1086/300632
  * Olech et al. (2016) Olech, A., Żoła̧dek, P., Wiśniewski, M., et al. 2016, MNRAS, 461, 674, doi: 10.1093/mnras/stw1261
  * Olech et al. (2017) —. 2017, MNRAS, 469, 2077, doi: 10.1093/mnras/stx716
  * Picone et al. (2002) Picone, J. M., Hedin, A. E., Drob, D. P., & Aikin, A. C. 2002, Journal of Geophysical Research (Space Physics), 107, 1468, doi: 10.1029/2002JA009430
  * Popescu et al. (2014) Popescu, M., Birlan, M., Nedelcu, D. A., Vaubaillon, J., & Cristescu, C. P. 2014, A&A, 572, A106, doi: 10.1051/0004-6361/201424064
  * Sansom et al. (2015) Sansom, E. K., Bland, P., Paxman, J., & Towner, M. 2015, Meteoritics and Planetary Science, 50, 1423, doi: 10.1111/maps.12478
  * Sansom et al. (2020) Sansom, E. K., Bland, P. A., Towner, M. C., et al. 2020, Meteoritics and Planetary Science, 55, 2157, doi: 10.1111/maps.13566
  * Shrbený & Spurný (2012) Shrbený, L., & Spurný, P. 2012, in LPI Contributions, Vol. 1667, Asteroids, Comets, Meteors 2012, 6436
  * Soja et al. (2011) Soja, R. H., Baggaley, W. J., Brown, P., & Hamilton, D. P. 2011, MNRAS, 414, 1059, doi: 10.1111/j.1365-2966.2011.18442.x
  * SonotaCo (2009) SonotaCo. 2009, WGN, Journal of the International Meteor Organization, 37, 55
  * Southworth & Hawkins (1963) Southworth, R. B., & Hawkins, G. S. 1963, Smithsonian Contributions to Astrophysics, 7, 261
  * Spurný (1997) Spurný, P. 1997, Planet. Space Sci., 45, 541, doi: 10.1016/S0032-0633(97)00006-8
  * Spurný et al. (2017) Spurný, P., Borovička, J., Mucke, H., & Svoreň, J. 2017, A&A, 605, A68, doi: 10.1051/0004-6361/201730787
  * Tagliaferri (1994) Tagliaferri, E. 1994, In: Hazards Due to Comets and Asteroids, ed. T. Gehrels, M. S. Matthews, & A. Schumann (University of Arizona Press)
  * Towner & et al. (2019) Towner, M., & et al. 2019, PASA
  * Tubiana et al. (2015) Tubiana, C., Snodgrass, C., Michelsen, R., et al. 2015, A&A, 584, A97, doi: 10.1051/0004-6361/201425512
  * Whipple (1940) Whipple, F. 1940, Photographic Meteor Studies, III. The Taurid Shower, Harvard reprint (Astronomical Observatory of Harvard College)
  * Whipple & El-Din Hamid (1952) Whipple, F. L., & El-Din Hamid, S. 1952, Helwan Institute of Astronomy and Geophysics Bulletins, 41, 3