*2.9. Statistical Analysis*

Data are reported as mean ± SEM and have been analyzed by Student's *t*-test or by two-way ANOVA, followed by Tukey's post-hoc test. Analyses have been performed with Graphpad Prism 5 software. Di fferences have been considered to be statistically significant when *p* < 0.05.


**Burkhard Schnepel** studied Social Anthropology in Berlin and Oxford. His doctoral thesis, completed in 1986 in Oxford, was about the divine kingship of the Shilluk of the southern Sudan. From the late 1980s onwards, he switched his regional focus to India, where he did fieldwork and archival research which resulted in publications on ethnohistorical aspects of the jungle kingdoms of Orissa, as well as on village theatre. Since 2002, he has been Professor at the Martin-Luther-University in Halle, Germany, where he started research on the Indian Ocean, especially Mauritius. Since 2008, he has also been Director of the Centre for Interdisciplinary Area Studies and, since 2013, Fellow of the Max Planck Institute for Social Anthropology, Halle, with a major program on "Connectivity in Motion: Port Cities of the Indian Ocean." Selected publications: *The Jungle Kings: Ethnohistorical Aspects of Politics and Ritual in Orissa* (2002), *Orient – Orientalistik – Orientalismus. Geschichte und Aktualität einer Debatte* (co-edited with Gunnar Brands and Hanne Schönig, 2011), and *Connectivity in Motion: Island Hubs in the Indian Ocean World* (co-edited with Edward A. Alpers, 2018).

**Swati Shirwadkar** is currently Professor Emeritus, B. V. University of Pune and was Professor and Head of the Department of Sociology and Centre for Advanced Studies, Director, Erasmus Mundus Euroculture Masters program, S. P. University, Pune, India. She was awarded Honorary Doctorate (Honoris Causa) by the University of Tampere, Finland, in 2014. She was awarded Shastri Indo-Canadian Fellowship for research, worked in York University and University of Toronto, Canada, and was invited as a visiting professor and Diversity Fellow in S. F. Austin State University, USA. She has worked as a visiting scholar at several European Universities. She was invited as a consultant for the high power committee of Maharashtra State, Government of India and UNDP, on the projects related to regional development, gender, and social change. Her research interests and publications are in the field of diasporas, migrants, identity issues and globalization, violence against women, sexuality and reproductive health, education, and socio-cultural changes.

People's transnational mobilities, their activities to build homes in their countries of residence and their connectivities have resulted in multiplicities of belonging to encountered, imagined and represented communities operating within various political contexts. Migrants and their descendants labor to form and transform relations with their country of origin and of residence. People who see their origins in India but are now living elsewhere are a case in point. They have been establishing worldwide home places, whose growing number and vibrancy invite reconsideration of Indian diasporic communities and contexts in terms of 'India(s) beyond India.' Issues of belonging in Indian diasporas include questions of membership not only in the nation of previous and present residence and/or the nation of origin, but also in other communities and networks in political, economic, religious and social realms at local, regional or global levels. Yet, belonging – and especially simultaneous belonging – to various formations is rarely unambiguous. Rather, belonging in all its modes may entail dilemmas that arise from inclusions and exclusions. Bearing in mind such processes, the contributions to this volume endeavor to provide answers to the question of what kinds of diiculties members of Indian communities abroad encounter in connection with their identifications with and participation in specific collectivities. The underlying argument of all the essays collected is that members of Indian diasporas develop strategies to cope with the dilemmas they face in connection with their sense of belonging to particular communities, while they are subjected to specific power relationships. Thus, the volume sheds light on the ways in which dilemmas of belonging are being negotiated in intercultural fields.

Elfriede Hermann is a cultural and social anthropologist at the University of Göttingen, working on identification and belonging, especially in connection with migration and ethnicity, emotions and historicity, social movements, cultural transformations and transculturation, and, recently, climate change.

Antonie Fuhse is a social anthropologist at the University of Göttingen who works on India and Indian mobilities. She is particularly interested in issues of belonging and identification, the anthropology of youth, and the anthropology of time.

Elfriede Hermann, Antonie Fuhse (Eds.) **India Beyond India**

12

India Beyond India:

Elfriede Hermann, Antonie Fuhse (Eds.)

Dilemmas of Belonging

Göttingen Series in

Social and Cultural Anthropology

ISBN: 978-3-86395-361-4 eISSN: 2512-6881

Göttingen University Press Göttingen University Press


**Vishnu Suresh \* , Przemyslaw Janik , Jacek Rezmer and Zbigniew Leonowicz**

Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland<EMAIL_ADDRESS>(P.J<EMAIL_ADDRESS>(J.R<EMAIL_ADDRESS>(Z.L.) **\*** Correspondence<EMAIL_ADDRESS>
Received: 25 December 2019; Accepted: 5 February 2020; Published: 7 February 2020

**Abstract:** The stochastic nature of renewable energy sources, especially solar PV output, has created uncertainties for the power sector. It threatens the stability of the power system and results in an inability to match power consumption and production. This paper presents a Convolutional Neural Network (CNN) approach consisting of different architectures, such as the regular CNN, multi-headed CNN, and CNN-LSTM (CNN-Long Short-Term Memory), which utilizes a sliding window data-level approach and other data pre-processing techniques to make accurate forecasts. The output of the solar panels is linked to input parameters such as irradiation, module temperature, ambient temperature, and windspeed. The benchmarking and accuracy metrics are calculated for 1 h, 1 day, and 1 week for the CNN based methods which are then compared with the results from the autoregressive moving average and multiple linear regression models in order to demonstrate its efficacy in making short-term and medium-term forecasts.

**Keywords:** convolutional neural networks; multi-headed CNN; CNN-LSTM; forecasting; solar output; sliding window; renewable energy


**2. What is Jet Lag?**

#### **2.1. Definition**

The American Academy for Sleep Medicine (AASM), in the second edition of its International Classification of Sleep Disorders [1] defined Jet Lag (circadian disorder, Jet Lag type), as a disorder "related to a temporal mismatch between the timing of the sleep-wake cycle generated by the endogenous circadian clock produced by a rapid change in time zones." In other words, it results from crossing time zones too rapidly for the circadian clock to keep pace.

#### **2.2. Sleep propensity in humans: circadian and homeostatic**

#### *2.2.1. Circadian influences*

In mammals, periods where sleep is favored alternate with periods where it is not. The timing, the duration and the frequency of these periods are regulated in part by the circadian body clock (see below). Timing, duration and frequency also vary across species.

Mice for instance sleep in between 40 and 120 bouts of a few minutes per day-night periods (polyphasic sleep). Human infants also show polyphasic sleep, as infants frequently wake up at night and sleep partly during the day. Most of the time, sleep episodes progressively converge to monophasic sleep with growing age, until one large sleep episode occurs at night. This monophasic organization of sleep is somewhat challenged in older life and there may be a return to forms of polyphasic sleep.

Sleep propensity in humans is maximal at the beginning of the night, moderate in the afternoon, and minimal during the morning and the evening. In parts of the world where working is difficult in the afternoon for climatic reasons, sleep has been observed to come in two phases (biphasic sleep). As our distant ancestors came from tropical areas where work is harder when the sun is high, this biphasic organization of sleep may well have been the first one to have appeared, which might explain a biphasic design.

#### *2.2.2. Homeostatic influences*

Its main symptoms include sleepiness at odd times during the day, and insomnia at night. They vary according to several variables, from individual sensitivity to age, to flight direction

Jet Lag treatment remains difficult, as no simple remedy is available, yet. As long as the earth keeps spinning round and our genome is not modified, the bad news is that Jet Lag is here to stay. Probably, some day it will be possible to turn the body clock forward or back and reset it immediately to the new time zone, but such a procedure has yet to be discovered. The natural

In this chapter, we review the scientific literature on Jet Lag origin, describe its symptoms in

The American Academy for Sleep Medicine (AASM), in the second edition of its International Classification of Sleep Disorders [1] defined Jet Lag (circadian disorder, Jet Lag type), as a disorder "related to a temporal mismatch between the timing of the sleep-wake cycle generated by the endogenous circadian clock produced by a rapid change in time zones." In other words, it results from crossing time zones too rapidly for the circadian clock to

In mammals, periods where sleep is favored alternate with periods where it is not. The timing, the duration and the frequency of these periods are regulated in part by the circadian

Mice for instance sleep in between 40 and 120 bouts of a few minutes per day-night periods (polyphasic sleep). Human infants also show polyphasic sleep, as infants frequently wake up at night and sleep partly during the day. Most of the time, sleep episodes progressively converge to monophasic sleep with growing age, until one large sleep episode occurs at night. This monophasic organization of sleep is somewhat challenged in older life and there may be

Sleep propensity in humans is maximal at the beginning of the night, moderate in the afternoon, and minimal during the morning and the evening. In parts of the world where working is difficult in the afternoon for climatic reasons, sleep has been observed to come in two phases (biphasic sleep). As our distant ancestors came from tropical areas where work is harder when the sun is high, this biphasic organization of sleep may well have been the first

body clock (see below). Timing, duration and frequency also vary across species.

(East or West), to number of meridians crossed, to length of stay and to seasons.

process of adjustment to new time zones is efficient but slow.

**2.2. Sleep propensity in humans: circadian and homeostatic**

one to have appeared, which might explain a biphasic design.

more detail, and see what can be done about it.

60 Circadian Rhythm - Cellular and Molecular Mechanisms

**2. What is Jet Lag?**

*2.2.1. Circadian influences*

a return to forms of polyphasic sleep.

**2.1. Definition**

keep pace.

The propensity to sleep is also a function of the time lapse since the last sleeping episode. The longer the time since the last sleeping episode, the stronger the pressure to enter sleep.

#### *2.2.3. Result of two processes*

Propensity to sleep is thus the result of two processes, one circadian and one homeostatic. The combination of these two processes has been first modelized by Borbély [2]. The relative weight of the two processes against each other has not been determined to the day, but I assume that they are roughly equivalent.

The intensity of both processes (circadian and homeostatic) is minimal in the morning after a normal episode of sleep, which favors awakening. As the homeostatic pressure has already decreased and the circadian influence allows for some sleep, a tendency to nap may be observed in the afternoon. The processes are at odds in the evening—the homeostasis favoring sleep but the circadian factor opposing it—which explains why it is difficult to enter sleep at that time of the day. The processes converge at the beginning of the night, hence favorizing sleep.

#### **2.3. Body clock (inner clock, internal clock, circadian clock)**

Like other mammals, human beings have a circadian clock, a paired group of nuclei in the base of the hypothalamus—the suprachiasmatic nuclei. They receive information from the retina about external light. These data allow for a daily-based correction and synchronization with the daily cycle of light and dark. The suprachiasmatic nuclei are considered together to represent the "master clock" of the brain, synchronizing a series of hormones (such as melatonin, cortisol and growth hormone), behaviors and other more specialized body clocks (core body temperature, rapid eye movement sleep, for instance).

The actions of the suprachiasmatic nuclei monitor the change from day to night. They have a useful stabilizing function on the body's biological rhythms, but they are slow to react to changes in lighting schedules, so that after time zones have been crossed rapidly, the endogenous signals for sleep and wakefulness do not match the local light-dark and social schedules.

How is the body clock indexed by external time? The major factor is the alternation of dark (night) and light (day) periods. The light signals are transmitted to the hypothalamus and support alignment of the inner body clock to the external time. There are also minor time clues (often called by their original German name, "Zeitgebers"). Minor Zeitgebers include social schedules, eating and drinking patterns, external temperature and physical activity.

Core body temperature is one of the best markers of the body clock. It is important as it has been linked with sleep and its rapid eye movement (REM) and non-rapid eye movement (NREM) components. "The ease of getting to sleep and staying asleep depends not only on previous wake time, but also on associations with the circadian rhythm of core temperature. Sleep is easiest to initiate when core temperature is falling rapidly or is at its lowest and most difficult when body temperature is rising rapidly or is high. Waking is the opposite of sleep initiation, because it occurs when core temperature is rising or is high. Sleep is favored when body temperature is low or rapidly descending, as at the end of a normal evening" [3].

*2.4.5. Sleep debt*

the adaptation process.

be negatively impacted.

*2.4.6. Sleep inertia*

properly either.

**3. Jet Lag symptoms**

**3.1. Descriptive data**

An important factor in the understanding of Jet Lag is the issue of sleep debt (cumulative sleep loss). Insomnia of an hour or two during the first night will add to 1 or 2 h on the second night, and so on. The result after 2–3 days is increased sleepiness, which will favor sleep at times where a fast adaptation would indicate to stay awake (long naps at inappropriate times for instance, staying asleep too long in the morning or going to bed too early). This will delay

Jet Lag

63

http://dx.doi.org/10.5772/intechopen.75929

One hour of sleep debt has been compared to the absorption of at least 33cl of beer [5]. A cumulative debt of 4 h should thus be compared to the absorption of four-five times 33cl. Sleep debt has also been found to parallel alcohol intoxication [6]. It is easy to understand that driving a car, for instance, should be avoided. Similarly, other important activities will

And then there is sleep inertia. Coming out of sleep is not comparable to an electrical switch, it is a biological process that has its complex rules. If you have slept enough and have no circadian problem, then you should feel fully awake after about 15–30 min. But if you have a sleep debt, or are suffering from the effects of shift work or Jet Lag, or have just had too long a nap, your brain may be half asleep, sometimes for hours, unable to sleep but unable to work

Jet Lag symptoms are frequent. Rogers and Reilly [7] indicated that 74% of surveyed travelers reported some form of Jet Lag. Of these respondents, 50% reported above-average tiredness and fatigue and 28% indicated some disruption in normal sleeping patterns. And 5% reported difficulties in concentration, while 5% reported eating problems. Gisquet [8] reported 80% of sleep disorders among travelers: difficulty in falling asleep, insomnia, premature awakening and daytime sleepiness. Among very frequent travelers such as flight personnel and interna-

The most obvious Jet Lag symptoms for the majority of travelers are the inability to sleep during destination night and to remain alert during destination day. It also includes difficulty in concentrating, clumsiness, difficulty with memory, general weakness, dizziness and lethargy [10]. General malaise, dysphoric mood, headaches and gastrointestinal disorders (indigestion, loss of appetite, bowel irregularities) have also been described but cause less harm.

Symptoms logically vary according to the time of day where assessments are made. They will be lighter when day-time overlaps with a day-time at home (or when night-time overlaps with night-time at home). They will be worse when day-time is superimposed on night-time at home (sleepiness) or when night-time is superimposed on day-time at home (insomnia).

tional business executives, the disorder may be recurrent or even chronic [9].

Some of the biological cycles adjust in a few days, while others, such as the core body temperature, take more time [4].

#### **2.4. When the body clock is not in phase with external time**

#### *2.4.1. Body clock resilience: shift work*

One fundamental aspect of the circadian influence is its resilience over time. A good example is shift work. If someone with a regular work schedule abruptly shifts to a night work, that person will usually find it quite difficult to enter sleep in the morning.

This would not make sense if there was only a homeostatic force at play. Indeed, the homeostatic pressure will be maximal after a night with no sleep, since the last sleep episode ended 24 h earlier. The homeostasis hence pushes to enter sleep as soon as circumstances will allow for it.

Sleep will however be difficult to find because the body clock insists that it is time to wake up. As a consequence, sleep, if it happens, will be shallowed and fragmented. It is only after several days that the new schedule will be integrated.

And then it could be time to change the work timetable again. Continuous shift work is an unending, impossible to stabilize, and most likely unhealthy process that modern day society is unfortunately not ready to reduce.

#### *2.4.2. Body clock resilience: Jet Lag*

Jet Lag is roughly the equivalent of shift work when people are transported in a fast way (jet airplanes) across one or several meridians, that is, east- or westwards. No Jet Lag should be expected in purely north- or southwards trips. When meridians are traversed, the internal clock remains indexed, for a few days at least, to the old schedule. It is thus not adjusted yet to the new timetable.

#### *2.4.3. Shift work, Jet Lag and Zeitgebers*

There is one substantial advantage of Jet Lag over shift work. In shift work, everything around the worker reminds her that it is presently night and that other people sleep. Most shops are closed, the sky is dark, there are less sounds from the city. The time clues are working against her and do not help synchronize the biological clock. In Jet Lag, what seems strange is the daytime sleepiness and the insomnia at night, although it is basically the same phenomenon. That is because the Zeitgebers here continuously act in favor of adjustment: external light, eating and other social schedules help adjust as fast as possible.

#### *2.4.4. Jet Lag and travel fatigue*

Jet Lag must be distinguished from travel fatigue, that happens every time transport has been long and uncomfortable, be it in car, train, boat or jet. Travel fatigue vanishes after a good night sleep. Jet Lag does not.

#### *2.4.5. Sleep debt*

difficult when body temperature is rising rapidly or is high. Waking is the opposite of sleep initiation, because it occurs when core temperature is rising or is high. Sleep is favored when body temperature is low or rapidly descending, as at the end of a normal evening" [3].

Some of the biological cycles adjust in a few days, while others, such as the core body tem-

One fundamental aspect of the circadian influence is its resilience over time. A good example is shift work. If someone with a regular work schedule abruptly shifts to a night work, that

This would not make sense if there was only a homeostatic force at play. Indeed, the homeostatic pressure will be maximal after a night with no sleep, since the last sleep episode ended 24 h earlier. The homeostasis hence pushes to enter sleep as soon as circumstances will allow for it. Sleep will however be difficult to find because the body clock insists that it is time to wake up. As a consequence, sleep, if it happens, will be shallowed and fragmented. It is only after

And then it could be time to change the work timetable again. Continuous shift work is an unending, impossible to stabilize, and most likely unhealthy process that modern day society

Jet Lag is roughly the equivalent of shift work when people are transported in a fast way (jet airplanes) across one or several meridians, that is, east- or westwards. No Jet Lag should be expected in purely north- or southwards trips. When meridians are traversed, the internal clock remains indexed, for a few days at least, to the old schedule. It is thus not adjusted yet to the new timetable.

There is one substantial advantage of Jet Lag over shift work. In shift work, everything around the worker reminds her that it is presently night and that other people sleep. Most shops are closed, the sky is dark, there are less sounds from the city. The time clues are working against her and do not help synchronize the biological clock. In Jet Lag, what seems strange is the daytime sleepiness and the insomnia at night, although it is basically the same phenomenon. That is because the Zeitgebers here continuously act in favor of adjustment: external light,

Jet Lag must be distinguished from travel fatigue, that happens every time transport has been long and uncomfortable, be it in car, train, boat or jet. Travel fatigue vanishes after a good

perature, take more time [4].

*2.4.1. Body clock resilience: shift work*

62 Circadian Rhythm - Cellular and Molecular Mechanisms

is unfortunately not ready to reduce.

*2.4.3. Shift work, Jet Lag and Zeitgebers*

*2.4.4. Jet Lag and travel fatigue*

night sleep. Jet Lag does not.

*2.4.2. Body clock resilience: Jet Lag*

**2.4. When the body clock is not in phase with external time**

several days that the new schedule will be integrated.

eating and other social schedules help adjust as fast as possible.

person will usually find it quite difficult to enter sleep in the morning.

An important factor in the understanding of Jet Lag is the issue of sleep debt (cumulative sleep loss). Insomnia of an hour or two during the first night will add to 1 or 2 h on the second night, and so on. The result after 2–3 days is increased sleepiness, which will favor sleep at times where a fast adaptation would indicate to stay awake (long naps at inappropriate times for instance, staying asleep too long in the morning or going to bed too early). This will delay the adaptation process.

One hour of sleep debt has been compared to the absorption of at least 33cl of beer [5]. A cumulative debt of 4 h should thus be compared to the absorption of four-five times 33cl. Sleep debt has also been found to parallel alcohol intoxication [6]. It is easy to understand that driving a car, for instance, should be avoided. Similarly, other important activities will be negatively impacted.

#### *2.4.6. Sleep inertia*

And then there is sleep inertia. Coming out of sleep is not comparable to an electrical switch, it is a biological process that has its complex rules. If you have slept enough and have no circadian problem, then you should feel fully awake after about 15–30 min. But if you have a sleep debt, or are suffering from the effects of shift work or Jet Lag, or have just had too long a nap, your brain may be half asleep, sometimes for hours, unable to sleep but unable to work properly either.


**8.3 The challenges that face SQU in applying the 1000-point electronic system**

According to the reports received in Spring and Fall 2022, from the committee, two challenges face the implementation of the 1000-point electronic system:

1.Technical

2.Human

Following are the technical challenges:

The human challenges can be summarized in the following points:


**5. Application to DFT and TD-DFT methods in polymer solar cells**

Many properties of interest in OPVs can be calculated or developed using DFT based computational methods, including bandgap, optical absorption, intramolecular and intermolecular charge transfer, exciton binding energy, charge transfer integral (to quantify electronic coupling), reorganization energy, and the rate of charge transfer and recombination in D–A compositors. In addition, in natural systems, the effects of the surrounding OPV media on these properties should be addressed. Although the impact of the medium varies depending on its nature and the nature of the transitions involved, low-cost polarization continuum solvation models can be utilized to account for solvation. In such situations, the solvent is treated as a continuous with a static dielectric constant, polarizing and polarized by the solute.

The following is a discussion of the theoretical methodologies and computational techniques mentioned above to foster a greater understanding of the connection between chemical structures and the optical and electrical properties of D–A systems about the rational design of OPV devices.

#### **5.1 Bandgap engineering**

A range of experimentally observed methods utilized may or may not indicate appreciable quantities in diverse contexts. Band gaps (see infra) are essential features to consider when evaluating conducting polymers. Controlling band gaps can improve the electroluminescence of OLEDs or the light absorption efficiency of photovoltaic cells [67]. To make organic polymers with good nonlinear optical response [67] or semiconductors having high electrical conductivity [68], materials with tiny band gaps are sought.

The phrase "bandgap" has multiple meanings. An infinite periodic system's electrical structure is called a "band." Also examined are monomers of conjugated polymers and oligomers of various sizes. The term bandgap also refers to a finite method feature that converges to the infinite periodic (band-structure) limit with oligomer size. The "gap" is the difference in electronic energy levels. Such as the energy difference between the highest occupied molecular orbital (HOMO) and the lowest unoccupied one, or computed energy gaps MO or CO (LUMO) [69]. Lowest optically permissible electronic excitation energy A visible energy gap (also known as an adiabatic or vertical optical gap) is an EO. Also, adiabatic or vertical electron attachment/detachment has associated energies like electron affinity (EA), ionization potential (IP) and electronegativity (EF) = IP-EA. Orbital energies and eigenvalues in KS DFT and HF may or may not be visible. However, approximations in actual computations might lead to big mistakes (see below). Furthermore, an orbital energy gap cannot reflect both EO and EF. Although the interpretation of the orbital energy gap as the fundamental gap is accurate in principle, the multiple approximations in the functionals make this interpretation useless in practice.

Band gaps often exhibit a roughly linear dependence on 1/m, allowing extrapolation to m ! ∞, 1/m ! 0. Generally, the quality of calculated results for different properties strongly relies on the physical models employed [70]. Extrapolating the infinite-periodic limit from a sequence of oligomer simulations requires prudence. Band gaps can diverge from linearity in 1/m [71]. These can also compute band gaps for polymers with unlimited chain lengths. PBCs have the advantage of not requiring further computations or extrapolation. However, PBC quantum chemistry algorithms are less functional than their molecular counterparts, which is a disadvantage.

The cheap computational cost of DFT and TD-DFT allows for the study of large systems. In contrast, the most commonly used functionals for molecules, such as generalized gradient approximations (GGA) and global hybrid GGA functionals,

result in the incorrect asymptotic behavior of a potential, significant delocalization errors, and lack of derivative discontinuity, all of which negatively impact o They showed that the band gaps computed with different hybrid functionals differ significantly, indicating that present hybrid functionals do not yield proper band gaps [72–74]. The link between projected orbital energy gaps and measured band gaps absorption energies is also poor for nonhybrid density functionals. Therefore, typical hybrid and meta-hybrid functionals are not acceptable for assessing the performance of organic photovoltaics, according to Savoie et al. Other hybrid functional analyses found striking agreement with measured optical gaps [75]. Many studies suggest that DFT and TD-DFT have limited predictive potential in this critical field [74]. Using hybrid functionals to integrate eX solves some of the DFT difficulties in extended systems [76]. However, estimated transfer integrals in organic semiconductors are sensitive to eX fraction [77].

#### **5.2 Intramolecular and intermolecular charge transfer**

To explain the transport properties, the charge transfer rate between donor and acceptor moieties could be calculated. Using DFT calculations of the electronic coupling, reorganization energy, and free energy difference associated with one electron transfer from donor to acceptor at the high-temperature limit, we can determine a rate using Marcus's formula [78, 79]. These predictions are then discussed in light of DFT's intrinsic flaws, such as overestimation of actual ground state energy, failure of the basis set to represent the system, and the inability of the functional to approximate critical interactions, to name a few. When it comes to charge transfer, however, there is another problem that is often overlooked.

A system where an extra account is localized on a single molecular unit is impossible to simulate using conventional DFT. As a result, calculations are frequently performed first on the charge donor, then on the charge acceptor, with or without the charge transferred. The overall energy of the system is calculated by adding the energies of the individual components. This is true when a considerable distance separates the donor and acceptor, and the electron density distribution of one entity has no effect on the electron density distribution of the other [79]. The size of the organizations participating in the charge transfer and the quantity and location of the surplus charge should naturally establish this limit. More sophisticated (and consequently more expensive) techniques, such as charge-constrained DFT [80], have been proposed for situations where this limit can never be achieved, such as intramolecular charge transfer [79]. However, standard ground state DFT remains the approach of choice for intermolecular charge transfer in solar cells, which usually involves larger molecular assemblies.

#### **5.3 Extion binding energy**

Exciton binding energy (Eb) is an essential element in polymer electronics and fundamental polymer physics, and it has been a source of debate for a long time. For example, a big Eb is required for a light-emitting polymer so that charge recombination takes precedence. Both the semiempirical model study [81] and the DFT/ LDA Bethe–Salpeter equation (BSE) or GW approaches [82] have relied heavily on theoretical research of Eb of conjugated polymers. The semiempirical model can be addressed nearly precisely for the electron correlation, but the results depend highly on the parameters, even though a qualitative comprehension has been reached [81].

Although the BSE or GW approach is first-principles, it is unclear if the Hohenberg–Kohn–Sham framework might accommodate these many-body adjustments at the Green's function level.

*Applications of Current Density Functional Theory (DFT) Methods in Polymer Solar Cells DOI: http://dx.doi.org/10.5772/intechopen.100136*

Furthermore, the final results differ from one another [82]. We highlight two recent advances in quantum chemistry: (i) Time-Dependent Density Functional Theory (TD-DFT) and its successful application to the lowest-lying excited states [83], and (ii) the hybrid GGA Becke three-parameter Lee–Yang–Parr (B3LYP) functional for the quantitative prediction of chemical and electronic structures [82]. In examining the excitation processes in conjugated systems, the combination of the two has proven quite effective [84]. Tretiak et al. [85] demonstrated that hybrid density functionals might simulate excitonic phenomena and provide satisfactory Eb findings. Pure local spin density approximation (LSDA), generalized gradient approximation (GGA, such as BLYP, BP86, BPBE, PBEPBE, BPW91), meta-GGA (such as PBEKCIS), and hybrid density functionals (H-GGA, such as O3LYP, B3LYP, B972, PBE1PBE) are used to optimize the ground-state geometries of the molecules at the DFT level.

#### **5.4 Electron transfer parameters**

The ET parameters are now frequently calculated using ab initio quantum chemistry methods. In classical Marcus theory [86], two critical parameters determine the temperature-dependent kinetics of electron transfer: the driving force and the reorganization energy. The activation energy, G#, is calculated as follows:

$$
\Delta G^\text{\\\(\lambda\)} = \frac{\left(\lambda + \Delta G^0\right)}{4\lambda} \tag{2}
$$

which then can be used in the Arrhenius relationship for the rate constant

$$k\_{ET} = A \exp\left(\frac{\Delta G^{\circ}}{k\_B T}\right) \tag{3}$$

The Boltzmann constant is denoted by kB. Note that Eq. (3) is essentially classical, and when quantum effects are relevant, the temperature dependence of Eq. (3) breaks down [87].

Although free energies will be used in natural systems, ab initio calculations usually overlook entropy changes and instead use potential energy. When the reactant and product structures are known, G° may readily determine the difference between respective equilibrium energies. However, calculating is more complicated since it involves nonequilibrium energy.

Abs Initio algorithms have difficulties determining since it is not a ground-state attribute. In the adiabatic representation, the ground state potential energy curve is lower than the excited state potential energy curve. To compute, one must first know the energy of the product state at the reactant state's equilibrium structure. Excited-state energies are more difficult to calculate than ground-state energies. TD-DFT methods provide good excited-state energies (e.g., up to 100 atoms). The energy of long-range CT states in TD-DFT is underestimated [88, 89], limiting its use in ET reactions.

In ET research, constrained DFT has various advantages. For starters, restricted DFT makes accessing diabatic states and calculating Marcus parameters a breeze. Second, from ground-state computations, constrained DFT generates diabatic conditions. Excited-state calculations are avoided. Third, the equilibrium structures of the reactant and product states are obtained by optimizing constrained geometry. Third, the quality of diabatic potential energy curves from limited DFT is superior to adiabatic curves from DFT to optimize in adiabatic conditions because fractional charge systems are more susceptible to self-interaction errors [90]. Fourth, the

localization of an unpaired electron is forced via constrained DFT. As a result, restricted DFT energy values are more precise. Limited DFT cannot be used for ET reactions involving a locally excited state as a ground-state approach. To investigate such responses, TD-DFT and limited DFT could be utilized. Our method, in particular, is before the electron source and acceptor. In systems in which the donor and acceptor are not separated, this can be a problem. As a result, our method is now the most effective for long-range ET responses, which is why it was created.

The coupling constant should be computed to obtain correct adiabatic energies from diabatic ones, making limited DFT more useful. In the adiabatic representation, the two curves create an upper and lower curve, with the energy gap at qc being twice the electronic coupling constant Hab, which is a significant coupling constant in nonadiabatic dynamics. DFT overestimates Hab, which could lead to erroneous RobinDay class III compound assignment. The limited DFT methodology for calculating high-quality diabatic energies could also be used to forecast exact Hab values. One of the difficulties is that constrained DFT techniques do not provide the proper wave function. Hab is the union of two independent wave functions with no equivalent in static density-dependent observables. As a result, some estimates are required to extract Hab from constrained DFT. We are now doing an active study on this topic, and the results will be released soon. Hab can also be employed with restricted DFT to study the issue of degenerate charge transfer states. It can also tackle problems similar to those that the restricted open-shell Kohn-Sham approach can solve [45].

#### **5.5 Scharber's model-electronic properties**

They are using density functional theory and Scharber's model to forecast the power conversion efficiency of organic solar cells. The scientific community has long sought improved polymers with excellent power conversion efficiency. Because polymer synthesis and device production take time, a guide would help find the best polymers. They published a simple model in 2006 that outlines how to estimate the power conversion efficiency of bulk heterojunction solar cells, and they claimed that these devices could attain 10% power conversion efficiencies. To evaluate a polymer's photovoltaic potential, Scharber's model requires knowledge about energy levels. Commonly, cyclic voltammetry is used to obtain these energy levels after polymer production. Modern theoretical tools like density functional theory come into use. These technologies can theoretically predict polymer properties before they are made.

The DFT has been extensively used to develop, explain, and predict the features of present and future organic solar cells [91]. Even though the model predicts certain qualities like open-circuit voltage (VOC) and short-circuit current density (JSC), one may wonder if the model estimates some attributes more precisely than others when combined with density functional theory. The dependability of theoretical computations is critical for understanding and predicting device attributes. There have been extensive research on oligomers [92] and crystals [93], but few comparisons of computations on polymers with experimental evidence. These highest values for power conversion efficiency can be derived by integrating density functional theory determined attributes with Sharber's model.

#### *5.5.1 Scharber's model*

This is equivalent to the maximum power density output of the device divided by the total power density receiving from the Air Mass 1.5 solar spectrum [94], which is 1000 W/m2 . The device's power density comprises the open-circuit

*Applications of Current Density Functional Theory (DFT) Methods in Polymer Solar Cells DOI: http://dx.doi.org/10.5772/intechopen.100136*

voltage, short-circuit current density, and fill factor (FF). According to Scharber's model, the VOC is connected to the difference between the acceptor's LUMO and the donor's HOMO. The VOC is obtained by subtracting 0.3 eV from the energy level difference. This shift was discovered empirically and is linked to residual carrier binding energy and interface effects [95]. An integral of external quantum efficiency (EQE) multiplied by the number of photons from the Air Mass 1.5 sun spectrum at all frequencies. For energies below and above the donor's optical band gap (Eopt), the EQE is just a step function with a value of 0%. The fill factor is FF = 0.65 for all devices. Other EQE and FF assumptions can be made if desired. For example, the EQE could be determined by investigating the Kohn-Sham joint density of states, revealing the frequency-dependent absorption cross-section behavior. In this situation, the polymer layer is thick enough to absorb any photon over the optical band gap, and the film shape essentially limits the EQE. The following equations describe Scharber's mode.

$$PCE = \frac{V\_{OC} J\_{SC} FF}{1000 W/m^2} \tag{4}$$

$$\text{LUMO}\_{donor} > \text{LUMO}\_{acceptor} + \text{0.3eV} \tag{5}$$

$$eV\_{OC} = LUMO\_{acceptor} - LUMO\_{donor} \tag{6}$$

$$E\_{\rm opt} = \text{LUMO}\_{domer} - \text{HOMO}\_{domer} \tag{7}$$

$$EQE(o) = \mathbf{0.65} \times \Theta(\hbar o - E\_{opt})\tag{8}$$

$$J\_{\rm SC} = \int EQE(o) \times \#photons\_{AirMax1.5}(o) do \tag{9}$$

As seen in Eq. (5), this model implies a 0.3 eV energy difference between the donor and acceptor Lumos to enable effective charge transfer. This LUMO offset should not be confused with the 0.3 eV empirical shifts for Eq. (6). So Eopt = 0.6 eV is the maximum value for eVOC.

#### **5.6 Photoabsorption spectrum**

Time-dependent DFT has surpassed all other methods for calculating organic compounds' excitation energies and optical characteristics in the last decade. Visual features like absorption spectra and optical band gap can be used to validate structures further. To better understand the electronic transitions of polymer monomers, used TD-DFT/CAMB3LYP/with varied basis set levels to perform quantum calculations on electronic absorption spectra in the gaseous phase and solvent. Aside from the bandgap, the computational prediction of whole spectrum excitation energies and cross-sections above the bandgap is equally crucial to solar cell efficiency. The excited electron tends to decay toward the conduction level (or the LUMO level) before being injected into the anode due to vibronic (molecular dyes) or photonic (solid dyes) contact with the environment, resulting in thermalization loss of the cell efficiency. The choice of time-dependent TD-DFT can be critical in accurately reproducing absorption, especially when using donor-acceptor dyes with charge-transfer excitations, as in the current study, where range corrected functionals become a viable option. The band maximum (λmax) is an apparent essential feature of the absorption spectra.

These are significant for optical properties of polymers in polymer solar cell applications, ranging from TD-DFT methodologies to predicted absorption wavelengths (λmax), oscillator strengths (f), and vertical excitation energies (E).


**4. OCTA in macular oedema of different pathologies**

Macular oedema is a pathological component of myriad ocular conditions and is a major cause of visual morbidity. Macular oedema can be due to inflammatory cause (as in uveitis), vascular, diabetes mellitus, retinal vein occlusion, CNV, metabolic, or in cases of retinal dystrophies. The high-resolution OCT B-scans allow for accurate description of macular oedema in terms of thickness, morphological pattern (cystoid, spongy or associated neurosensory detachment), and the anatomical involvement of selected retinal layers, the outer plexiform layer (OPL) (**Figure 5**). Such details can be useful not only for disease diagnosis but also for follow-up of treatment response. An advantage of OCTA over the traditional OCT B-scans is the ability to simultaneously correlate macular oedema with the underlying aetiological vascular process, for example ischemia and vascular drop-outs.

**In diabetic eyes**, OCTA can delineate successfully the enlarged FAZ with underlying non-perfusion that increases according to the severity of diabetic retinopathy, quantitative measurement of vascular density (mainly perfusion density and vessel density), reduced capillary density in the superficial and deep capillary plexuses,

#### **Figure 5.**

*Optical coherence tomography angiography (OCTA) of mild NPDR with diabetic maculopathy, the SCP (b, e) showed well-defined perifoveal and parafoveal vessels with areas void of flow representing area of capillary dropouts, more than those seen with the conventional FFA (a). SAME findings in the DCP (c, f) but more advanced regarding the areas of ischemia there is significant decrease in the perfusion as measured by the vessels density and flow index (d) more evident in the DCP.*

#### **Figure 6.**

*Mac Tel type 2 OCT-angiography shows temporal flow voids areas in the superficial and deep capillary plexuses, spacing between the vessels with increased vascular diameter, and minimal vascular invasion of the FAZ at the deep capillary plexus. The B scan shows multiple hyporeflective cavitations, focal loss of the inner/outer segment with no evidence of external limiting membrane disruption.*

microaneurysms (appear as focally dilated saccular or fusiform capillaries), choriocapillaris flow voids changes and increased vessel tortuosity. Moreover, OCTA may show DR before it is clinically detectable.

However, OCTA has certain limitations in the assessment of vascular retinal diseases associated with macular oedema. It is incapable of testing the structural and functional integrity of vessel walls and hence cannot demonstrate leakage (reflecting the breakdown of the blood-retinal barrier) as in FFA or ICGA. FFA has the advantage of showing abnormal blood vessels, such as retinal neovascularization or intraretinal microvascular abnormalities. In addition, OCTA has so far, a limited imaging field missing most of the peripheral retina which is the main site of pathology in a number of retinal diseases (the developing widefield OCTA technology). Therefore, for DR, fluorescein angiography will remain an essential vital diagnostic modality and OCTA will be the alternative or complementary method of angiography that can be safely (in risky patients especially with impaired kidney functions) and more frequently performed to assess the effectiveness of treatment in DR [11–14].

Macular telangiectasia Type 2 (MacTel2) is a neurodegenerative change affecting the Muller cells in the macular area. SD-OCT abnormalities in MacTel include; cyst formation in the inner retina, disruption of the external limiting membrane, loss of inner/outer segment, parafoveal venular dilation, hyporeflective cavitation of the outer retina, perifoveal capillary leakage, and subretinal neovascularization. In OCTA, Zeimer et al. noted vascular changes in the deep capillary network (enlargement of vessels, larger intervascular spaces, dilated, dendritic appearance

#### **Figure 7.**

*Advanced mac Tel type 2 OCT-angiography showed temporal flow voids areas in the superficial and deep capillary plexuses. Telangiectatic vessels are seen among the superficial and deep plexuses with increased vascular diameter as well as rarefied vessels; temporal and superior to the FAZ with right-angled configuration and, vascular invasion of the FAZ at the superficial and deep capillary plexuses. The B scan showed multiple hyporeflective cavitations with focal and diffuse loss of the inner outer segment as well as external limiting membrane disruption.*

of vessels, telangiectasis, reduction and/or loss of capillary density), and the extension of anastomoses toward the superficial capillary network with progression of the disease. RPE-proliferations were often associated with "contraction" of surrounding vessels [14, 15] (**Figures 6** and **7**).