id:"swepub:oai:DiVA.org:liu-175898"
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Data-driven analysis of the rotational energy landscapes of an organic cation in a substituted alloy perovskite
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- Sukmas, W. (författare)
- Extreme Conditions Physics Research Laboratory (ECPRL), Physics of Energy Materials Research Unit (PEMRU), Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand; Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok, 10400, Thailand
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- Ektarawong, A. (författare)
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok, 10400, Thailand; Chula Intelligent and Complex Systems (CHICS), Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand
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- Tsuppayakorn-Aek, P. (författare)
- Extreme Conditions Physics Research Laboratory (ECPRL), Physics of Energy Materials Research Unit (PEMRU), Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand; Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok, 10400, Thailand
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- 2021
- 2021
- Engelska.
- Ingår i: Materials Advances. - : Royal Society of Chemistry. - 2633-5409. ; 2:7, s. 2366-2372
- Tidskriftsartikel (refereegranskat)
Abstract
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- Lead-free hybrid organic-inorganic perovskites have recently emerged as excellent materials particularly in highly potential yet low-cost photovoltaic technologies. Calculations have previously suggested that CH3NH3BiSeI2 can be used as an alternative material for the highly studied CH3NH3PbI3 due to its eco-friendliness and comparable performance. Herein, with the aid of Euler angles, the interplay between the organic CH3NH3 (MA) cation and the inorganic BiSeI2 framework, obtained from first-principles calculations, is thoroughly scrutinised by means of the multidimensional total energy landscape. The highest peak of 17.9 meV per atom, protruding from the average plateau of 9 meV per atom within the four-dimensional topography, is equivalent to 208 K, the temperature at which the MA cations freely reorient. Moreover, the complexity of the angle-energy relationship is mitigated by exploiting a high-fidelity simulation based on deep learning. The deep artificial neural network of five hidden layers with 500 neurons, each fed by ten descriptors-three Euler angles and seven various bond lengths-predicts the total energies with an accuracy within the root mean square error of 0.39 ± 0.03 meV per atom for the test dataset. This novel statistical model in turn offers a tantalising promise to provide an accurate prediction of this materials energies, while diminishing the need for costly first-principles calculations. © The Royal Society of Chemistry.
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- NATURVETENSKAP -- Kemi -- Teoretisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Theoretical Chemistry (hsv//eng)
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