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    Investigation on the facet-dependent anisotropy in halide perovskite single crystals
    (American Chemical Society, 2022) Parikh, Nishi; Pandey, Manoj; Prochowicz, Daniel; Kalam, Abul; Tavakoli, Mohammad Mahdi; Satapathi, Soumitra; Akın, Seçkin; Yadav, Pankaj
    Metal halide perovskite (MHP) single crystals (SCs) are proven to possess superior optoelectronic properties compared to those of their polycrystalline thin film analogues. With the advancement and progress in the study of MHP SCs, it is found that the properties at the surface and bulk of SCs are significantly different. However, there are only a few studies present for the facet-dependent performance of MHP SCs. In this work, we have systematically investigated the anisotropic properties of naturally exposed facets ((100) and (112)) in MAPbI3 SCs. We studied the influence of temperature and illumination on the properties of these facets. It was found that hysteresis at the (112) facet is higher than that at the (100) facet because of the higher trap density of 1.17 × 1013 cm-3 at this facet as compared to the trap density of 2.11 × 1012 cm-3 for the (100) facet. Although there exist different kinds of defects at both the facets, the ion migration mechanism remains the same at both facets, which is confirmed by the obtained almost same activation energy of 0.378 and 0.308 eV for (100) and (112) facets, respectively, for ion migration. The photocurrent, responsivity, and EQE values further confirm anisotropic properties of both the facets in MAPbI3 SCs although they are the same from the crystallography point of view. Thus, this study provides a detailed and systematic investigation of the facet-dependent properties in MHP SCs.
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    Is machine learning redefining the perovskite solar cells?
    (Elsevier B.V., 2022) Parikh, Nishi; Karamta, Meera R.; Yadav, Neha; Mahdi Tavakoli, Mohammad; Prochowicz, Daniel; Akın, Seçkin
    Development of novel materials with desirable properties remains at the forefront of modern scientific research. Machine learning (ML), a branch of artificial intelligence, has recently emerged as a powerful technology in optoelectronic devices for the prediction of various properties and rational design of materials. Metal halide perovskites (MHPs) have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell application. Therefore, the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of processing. Here, we comprehensively reviewed different applications of ML in the designing of both MHP absorber layers as well as complete perovskite solar cells (PSCs). At the end, the challenges of ML along with the possible future direction of research are discussed. We believe that this review becomes an indispensable roadmap for optimizing materials composition and predicting design strategies in the field of perovskite technology in the future.
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    Predicting the state parameters of lithium ion batteries: The race between filter-based and data driven approaches
    (Royal Society of Chemistry, 2023) Pandey, Siddhi Vinayak; Parikh, Nishi; Prochowicz, Daniel; Akın, Seçkin; Satapathi, Soumitra; Tavakoli, Mohammad Mahdi
    Lithium ion batteries (LIBs) have revolutionized the era of electrical energy storage by offering high energy density and longer life cycles in various applications such as electric vehicles, electronic gadgets, satellites and power grids. To achieve optimum and reliable performance throughout their life cycle, accurate monitoring of their state parameters such as state of charge (SOC), state of health (SOH), and remaining useful life (RUL) needs to be estimated precisely. Filter-based and data driven techniques estimate these parameters accurately even under dynamic battery operation. In this paper, first, we have given details about experimental techniques through which LIB state parameters are estimated, but due to poor nonlinearity handling capacity of these models, we showcase the potential of various filter-based and data driven techniques with a variety of features extracted from LIBs. Subsequently, we discuss the working and performance of various filter based and data driven algorithms utilised in predicting the state parameters of batteries such as SOC, SOH & RUL in detail. Additionally, a comparative table comprising features, predictive techniques and performance is made to highlight the effectiveness of each method. Finally, we propose a strategy to improve the estimation accuracy of LIBs. Overall, the paper provides a comprehensive review of various estimating lgorithms and their potential in predicting the state parameters of LIBs with an aim to develop an intelligent framework for required applications and highlights the challenges which are yet to be overcome.
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    Probing the low-frequency response of ımpedance spectroscopy of halide perovskite single crystals using machine learning
    (American Chemical Society, 2023) Parikh, Nishi; Akın, Seçkin; Kalam, Abul; Prochowicz, Daniel; Yadav, Pankaj
    Electrochemical impedance spectroscopy (EIS) has emerged as a versatile technique for characterization and analysis of metal halide perovskite solar cells (PSCs). The crucial information about ion migration and carrier accumulation in PSCs can be extracted from the low-frequency regime of the EIS spectrum. However, lengthy measurement time at low frequencies along with material degradation due to prolonged exposure to light and bias motivates the use of machine learning (ML) in predicting the low-frequency response. Here, we have developed an ML model to predict the low-frequency response of the halide perovskite single crystals. We first synthesized high-quality MAPbBr3 single crystals and subsequently recorded the EIS spectra at different applied bias and illumination intensities to prepare the dataset comprising 8741 datapoints. The developed supervised ML model can predict the real and imaginary parts of the low-frequency EIS response with an R2 score of 0.981 and a root mean squared error (RMSE) of 0.0196 for the testing set. From the ground truth experimental data, it can be observed that negative capacitance prevails at a higher applied bias. Our developed model can closely predict the real and imaginary parts at a low frequency (50 Hz-300 mHz). Thus, our method makes recording of EIS more accessible and opens a new way in using the ML techniques for EIS.
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    Probing the surface and bulk electrical response of MAPbBr3Single crystals
    (American Chemical Society, 2022) Yadav, Pankaj; Parikh, Nishi; Prochowicz, Daniel; Kalam, Abul; Tavakoli, Mohammad Mahdi; Akın, Seçkin
    Single crystals (SCs) of halide perovskites are rapidly gaining attention over their polycrystalline thin-film counterparts due to their superior optoelectronic properties. One of the various reasons for their improved properties is the reduced defect concentration as compared with thin films. Since their discovery, many efforts have been devoted to discerning the surface and bulk properties of SCs. However, it is difficult to probe the surface and bulk responses of SCs, and only a few reports distinguishing between these properties have been presented. In this study, we distinguished between the surface and bulk electrical responses of methylammonium lead tribromide (MAPbBr3) SCs using impedance spectroscopy (IS). The electrical response of the MAPbBr3SC was recorded using different optical excitations for the generation of carriers. The Nyquist plots and capacitance-frequency responses observed under blue and red wavelengths differ significantly from each other and were studied systematically. The results obtained suggest that the photocurrent and capacitive response under blue light are higher than those under red light. Moreover, the change in the low-frequency capacitance is lower in the case of blue light. This is because of the polarization of the interface of metal contacts and the surface of SCs or due to defect-mediated conductivity. As the carriers are collected efficiently from the surface following a rapid process, they do not contribute to the capacitance build-up with temperature. To the best of our knowledge, electrical responses such as the impedance and the capacitive response of SCs using different illumination wavelengths and temperatures have been rarely discussed in the literature. © 2022 American Chemical Society. All rights reserved.
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    Rationalizing the effect of polymer-controlled growth of perovskite single crystals on optoelectronic properties
    (American Chemical Society, 2022) Parikh, Nishi; Sevak, Parth; Jowhar Khanam, Sarvani; Prochowicz, Daniel; Akın, Seçkin; Satapathi, Soumitra; Tavakoli, Mohammad Mahdi
    To improve and modulate the optoelectronic properties of single-crystal (SC) metal halide perovskites (MHPs), significant progress has been achieved. Polymer-assisted techniques are a great approach to control the growth rate of SCs effectively. However, the resultant optoelectrical properties induced by polymers are ambiguous and need to be taken into the consideration. In this study, we have synthesized methylammonium lead triiodide (MAPbI3) SCs using polyethylene glycol (PEG) and polystyrene (PS) polymers where PEG contains oxygen functionalities and PS does not. We studied the electrical properties of these SCs under dark and illumination conditions. It was observed that PEG-assisted SCs showed few defects with lower photocurrent as compared to the PS-assisted ones because of defect-mediated conductivity. The results are further verified by transient current response, responsivity, and capacitance-frequency measurements. The present study sheds light on the polymer selection for the growth of MHP SCs and their optoelectronic properties.
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    Recent progress of light intensity-modulated small perturbation techniques in perovskite solar cells
    (John Wiley and Sons Inc, 2021) Parikh, Nishi; Narayanan, Saranya; Kumari, Hemant; Prochowicz, Daniel; Kalam, Abul; Satapathi, Soumitra; Akın, Seçkin
    The small perturbation frequency-resolved techniques have been powerful tools in unraveling the kinetic processes governing the operation of perovskite solar cells (PSCs). One such technique is electrochemical impedance spectroscopy (EIS). However, a thorough interpretation of the EIS response of PSCs is still lacking owing to the absence of a uniform electrical equivalent circuit. In this context, intensity-modulated photocurrent/photovoltage spectroscopy (IMPS/IMVS) can be the link between the optical and electrical responses of PSCs and complement the IS technique. In this review, the progress made in interpreting the IMPS/IMVS response of various types of PSCs is summarized and diverse prospects are discussed. First, the basic theory and models present in the literature are discussed. Next, the IMPS/IMVS response of mesoporous and planar PSCs based on various physical parameters is discussed. At last, proposed future prospects for the development of this field are discussed.