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QTAIM method for accelerated prediction of band gaps in perovskites

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Abstract

Efficient prediction of electronic properties of semiconductors is a cornerstone in the rational design of materials for various technological applications, including optoelectronics, photovoltaics and catalysis. Topological analysis of electron density is a powerful tool to unravel the correlations between the composition of isostructural compounds and their electronic properties. Resorting to this approach in theory or in experiment requires an elaboration of descriptors connecting the composition with the electronic structure characteristics. In the current work, the application of chemical topology for prediction of band gaps is illustrated for the model systems of perovskite compounds. The correlations between the band gaps and the electron density at the bond critical points are established, enabling the construction of composition–property maps. The procedure applying PBE-based descriptors for evaluation of the band gaps, calculated with resources-demanding methods, such as hybrid functionals or GW, is outlined. Finally, it is demonstrated how topological indices can be used to predict the band gaps for yet unsynthesized materials on the basis of available experimental data for isostructural compounds.

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References

  1. Bader RF (1990) Atoms in molecules: a quantum theory, The International Series of Monographs on Chemistry, vol 22. Clarendon Press, Oxford

    Google Scholar 

  2. Bader RFW (1991) Chem Rev 91(5):893

    Article  CAS  Google Scholar 

  3. Bertini L, Cargnoni F, Gatti C (2007) Theor Chem Acc 117(5):847

    Article  CAS  Google Scholar 

  4. Ormeci A, Simon A, Grin Y (2010) Angew Chem Int Ed 49(47):8997

    Article  CAS  Google Scholar 

  5. Matthies O, Grin Y, Kohout M (2017) ChemistrySelect 2(25):7659

    Article  CAS  Google Scholar 

  6. Grin Y, Fedorchuk A, Faria RJ, Wagner FR (2018) Crystals 8:2

    Article  Google Scholar 

  7. Saleh G, Ceresoli D, Macetti G, Gatti C (2019) Computational Materials Discovery. The Royal Society of Chemistry, London, pp 117–175

    Google Scholar 

  8. Hohenberg P, Kohn W (1964) Phys Rev 136:B864

    Article  Google Scholar 

  9. Contreras-García J, Calatayud M, Piquemal JP, Recio J (2012) Comput Theor Chem 998:193

    Article  Google Scholar 

  10. Contreras-García J, Cardenas C (2017) J Mol Model 23(9):271

    Article  Google Scholar 

  11. Tognetti V, Joubert L (2014) Phys Chem Chem Phys 16:14539

    Article  CAS  Google Scholar 

  12. Tognetti V, Joubert L, Adamo C (2010) J Chem Phys 132(21):211101

    Article  Google Scholar 

  13. Seriani N (2010) J Phys Condens Matter 22(25):255502

    Article  Google Scholar 

  14. Kang CJ (2017) Int J Quantum Chem 118(11):e25548

    Article  Google Scholar 

  15. Burschka J, Pellet N, Moon SJ, Humphry-Baker R, Gao P, Nazeeruddin MK, Grätzel M (2013) Nature 499:316

    Article  CAS  Google Scholar 

  16. Correa-Baena JP, Saliba M, Buonassisi T, Grätzel M, Abate A, Tress W, Hagfeldt A (2017) Science 358(6364):739

    Article  CAS  Google Scholar 

  17. Turren-Cruz SH, Hagfeldt A, Saliba M (2018) Science 362(6413):449

    Article  CAS  Google Scholar 

  18. Kim YH, Cho H, Heo JH, Kim TS, Myoung N, Lee CL, Im SH, Lee TW (2015) Adv Mater 27(7):1248

    Article  CAS  Google Scholar 

  19. Tan ZK, Moghaddam RS, Lai ML, Docampo P, Higler R, Deschler F, Price M, Sadhanala A, Pazos LM, Credgington D, Hanusch F, Bein T, Snaith HJ, Friend RH (2014) Nat Nanotechnol 27(9):687

    Article  Google Scholar 

  20. Sun J, Wu J, Tong X, Lin F, Wang Y, Wang ZM (2018) Adv Sci 5(5):1700780

    Article  Google Scholar 

  21. Xu YF, Yang MZ, Chen BX, Wang XD, Chen HY, Kuang DB, Su CY (2017) J Am Chem Soc 139(16):5660

    Article  CAS  Google Scholar 

  22. Volonakis G, Giustino F (2018) Appl Phys Lett 112(24):243901

    Article  Google Scholar 

  23. Luaña V, Costales A, Pendás AM (1997) Phys Rev B 55(7):4285

    Article  Google Scholar 

  24. Luaña V, Costales A, Pendás AM, Pueyo L (1999) J Phys Condens Matter 11(33):6329

    Article  Google Scholar 

  25. Perdew JP, Burke K, Ernzerhof M (1996) Phys Rev Lett 77(18):3865

    Article  CAS  Google Scholar 

  26. Giannozzi P, Baroni S, Bonini N, Calandra M, Car R, Cavazzoni C, Ceresoli D, Chiarotti GL, Cococcioni M, Dabo I, Corso AD, de Gironcoli S, Fabris S, Fratesi G, Gebauer R, Gerstmann U, Gougoussis C, Kokalj A, Lazzeri M, Martin-Samos L, Marzari N, Mauri F, Mazzarello R, Paolini S, Pasquarello A, Paulatto L, Sbraccia C, Scandolo S, Sclauzero G, Seitsonen AP, Smogunov A, Umari P, Wentzcovitch RM (2009) J Phys Condens Matter 21(39):395502

    Article  Google Scholar 

  27. Giannozzi P, Andreussi O, Brumme T, Bunau O, Nardelli MB, Calandra M, Car R, Cavazzoni C, Ceresoli D, Cococcioni M, Colonna N, Carnimeo I, Corso AD, de Gironcoli S, Delugas P, Jr RAD, Ferretti A, Floris A, Fratesi G, Fugallo G, Gebauer R, Gerstmann U, Giustino F, Gorni T, Jia J, Kawamura M, Ko HY, Kokalj A, Küçükbenli E, Lazzeri M, Marsili M, Marzari N, Mauri F, Nguyen NL, Nguyen HV, Otero-de-la Roza A, Paulatto L, Poncé S, Rocca D, Sabatini R, Santra B, Schlipf M, Seitsonen AP, Smogunov A, Timrov I, Thonhauser T, Umari P, Vast N, Wu X, Baroni S (2017) J Phys Condens Matter 29(46):465901

    Article  CAS  Google Scholar 

  28. Rappe AM, Rabe KM, Kaxiras E, Joannopoulos JD (1990) Phys Rev B 41:1227

    Article  CAS  Google Scholar 

  29. Vanderbilt D (1990) Phys Rev B 41:7892

    Article  CAS  Google Scholar 

  30. Monkhorst HJ, Pack JD (1976) Phys Rev B 13:5188

    Article  Google Scholar 

  31. Adamo C, Barone V (1999) J Chem Phys 110(13):6158

    Article  CAS  Google Scholar 

  32. Marini A, Hogan C, Grüning M, Varsano D (2009) Comput Phys Commun 180(8):1392

    Article  CAS  Google Scholar 

  33. Corso AD (2014) Comput Mater Sci 95:337

    Article  Google Scholar 

  34. http://theossrv1.epfl.ch/main/pseudopotentials. Accessed 16 July 2016

  35. Prandini G, Marrazzo A, Castelli IE, Mounet N, Marzari N (2018) Comput Mater 4:72

    Article  Google Scholar 

  36. Blochl PE (1994) Phys Rev B 50(24):17953

    Article  CAS  Google Scholar 

  37. Kresse G, Joubert D (1999) Phys Rev B 59:1758

    Article  CAS  Google Scholar 

  38. Enkovaara J, Rostgaard C, Mortensen JJ, Chen J, Dułak M, Ferrighi L, Gavnholt J, Glinsvad C, Haikola V, Hansen HA, Kristoffersen HH, Kuisma M, Larsen AH, Lehtovaara L, Ljungberg M, Lopez-Acevedo O, Moses PG, Ojanen J, Olsen T, Petzold V, Romero NA, Stausholm-Møller J, Strange M, Tritsaris GA, Vanin M, Walter M, Hammer B, Häkkinen H, Madsen GKH, Nieminen RM, Nørskov JK, Puska M, Rantala TT, Schiøtz J, Thygesen KS, Jacobsen KW (2010) J Phys Condens Matter 22(25):253202

    Article  CAS  Google Scholar 

  39. Mortensen JJ, Hansen LB, Jacobsen KW (2005) Phys Rev B 71:035109

    Article  Google Scholar 

  40. Otero-de-la Roza A, Blanco M, Martín Pendás A, Luaña V (2009) Comput Phys Commun 180(1):157

    Article  CAS  Google Scholar 

  41. Otero-de-la Roza A, Johnson ER, Luaña V (2014) Comput Phys Commun 185(3):1007

    Article  CAS  Google Scholar 

  42. Momma K, Izumi F (2011) J Appl Crystallogr 44:1272

    Article  CAS  Google Scholar 

  43. Eperon GE, Stranks SD, Menelaou C, Johnston MB, Herz LM, Snaith HJ (2014) Energy Environ Sci 7(3):982

    Article  CAS  Google Scholar 

  44. Sutton RJ, Eperon GE, Miranda L, Parrott ES, Kamino BA, Patel JB, Horantner MT, Johnston MB, Haghighirad AA, Moore DT, Snaith HJ (2016) Adv Energy Mater 6(8):1502458

    Article  Google Scholar 

  45. Filip MR, Hillman S, Haghighirad AA, Snaith HJ, Giustino F (2016) J Phys Chem Lett 7(13):2579

    Article  CAS  Google Scholar 

  46. Hao F, Stoumpos CC, Cao DH, Chang RPH, Kanatzidis MG (2014) Nat Photon 8(6):489

    Article  CAS  Google Scholar 

  47. McClure ET, Ball MR, Windl W, Woodward PM (2016) Chem Mater 28(5):1348

    Article  CAS  Google Scholar 

  48. Slavney AH, Hu T, Lindenberg AM, Karunadasa HI (2016) J Am Chem Soc 138(7):2138

    Article  CAS  Google Scholar 

  49. Volonakis G, Filip MR, Haghighirad AA, Sakai N, Wenger B, Snaith HJ, Giustino F (2016) J Phys Chem Lett 7(7):1254

    Article  CAS  Google Scholar 

  50. De Marco N, Zhou H, Chen Q, Sun P, Liu Z, Meng L, Yao EP, Liu Y, Schiffer A, Yang Y (2016) Nano Lett 16(2):1009

    Article  CAS  Google Scholar 

  51. Fang Y, Dong Q, Yuan Y, Huang J (2015) Nat Photon 9:679

    Article  CAS  Google Scholar 

  52. Jang DM, Kim DH, Park K, Park J, Lee JW, Song JK (2016) J Mater Chem C 4:10625

    Article  CAS  Google Scholar 

  53. Koh TM, Fu K, Fang Y, Chen S, Sum TC, Mathews N, Mhaisalkar SG, Boix PP, Baikie T (2014) J Phys Chem C 118(30):16458

    Article  CAS  Google Scholar 

  54. Shi D, Adinolfi V, Comin R, Yuan M, Alarousu E, Buin A, Chen Y, Hoogland S, Rothenberger A, Katsiev K, Losovyj Y, Zhang X, Dowben PA, Mohammed OF, Sargent EH, Bakr OM (2015) Science 347(6221):519

    Article  CAS  Google Scholar 

  55. Brivio F, Walker AB, Walsh A (2013) APL Mater 1(4):042111

    Article  Google Scholar 

  56. Frost JM, Butler KT, Brivio F, Hendon CH, van Schilfgaarde M, Walsh A (2014) Nano Lett 14(5):2584

    Article  CAS  Google Scholar 

  57. Amat A, Mosconi E, Ronca E, Quarti C, Umari P, Nazeeruddin MK, Grätzel M, De Angelis F (2014) Nano Lett 14(6):3608

    Article  CAS  Google Scholar 

  58. Baniecki JD, Yamazaki T, Ricinschi D, Van Overmeere Q, Aso H, Miyata Y, Yamada H, Fujimura N, Maran R, Anazawa T, Valanoor N, Imanaka Y (2017) Sci Rep 7:41725

    Article  CAS  Google Scholar 

  59. Jenkins S (2002) J Phys Condens Matter 14(43):10251

    Article  CAS  Google Scholar 

  60. Ayers PW, Jenkins S (2015) Comput Theor Chem 1053:112. (Special Issue: Understanding structure and reactivity from topology and beyond)

    Article  CAS  Google Scholar 

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Acknowledgements

We acknowledge PRACE for awarding us access to Curie at GENCI@CEA, France and Irene at GENCI@CEA, France. We are grateful to CSC center (Finland) for providing HPC resources.

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Authors and Affiliations

  1. Laboratory of Quantum Mechanics and Molecular Structure, Department of Chemistry, Moscow State University M.V. Lomonosov, Leninskiye Gory 1-3, Moscow, Russian Federation, 119991

    Maria A. Syzgantseva

  2. Laboratory of Molecular Simulation, Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), EPFL SB ISIC LSMO, Rue de l’Industrie 17, Case postale 440, 1951, Sion, Switzerland

    Olga A. Syzgantseva

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  1. Maria A. Syzgantseva
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Correspondence to Olga A. Syzgantseva.

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Syzgantseva, M.A., Syzgantseva, O.A. QTAIM method for accelerated prediction of band gaps in perovskites. Theor Chem Acc 138, 52 (2019). https://doi.org/10.1007/s00214-019-2445-y

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