Data-driven strategy for bandgap database construction of perovskites and the potential segregation study

Abstract

Light-induced segregation limits the practical application of mixed halide perovskites in solar cells. Herein, halide segregation is evaluated by a data-driven approach with constructing a bandgap database of 53,361 mixed ABX₃ [where A = Cs, formamidinium (FA) or methylammonium (MA); B = Pb or Sn; X = Br, Cl, or I] perovskites. A transfer learning strategy was employed to fine-tune the parameters of a Graph Neural Network model using experimental and density functional theory (DFT)-calculated bandgaps. This approach accelerated the construction of a unique database, distinguishing it from others primarily focused on ABX₃ perovskite element substitution. The database is characterized by continuously varying compositions and accurate bandgaps. It was utilized to calculate the free energy of 20,688 mixed iodine-bromine perovskites and generate corresponding phase diagrams for predicting their light-induced segregation behavior. It is found that the bandgap increases with decreasing ionic radii at the A-site and X-site. This composition-dependent bandgap difference drives halide segregation. Moreover, using a higher Cs content at the A-site, rather than MA, reduces this bandgap difference, enhancing photostability. The proposed data-driven strategy can facilitate the targeted design of novel perovskites with mixed compositions and the investigation of halide perovskite segregation.

Keywords

Mixed halide perovskites / bandgap database / machine learning / halide segregation

References

[1] Yu W,Wang H.Breaking the bottleneck of lead-free perovskite solar cells through dimensionality modulation.Chem Soc Rev2024;53:1769-88

[2] Raza H,Gao Y.Potential-induced degradation: a challenge in the commercialization of perovskite solar cells.Energy Environ Sci2024;17:1819-53

[3] Liang Z,Xu H.Homogenizing out-of-plane cation composition in perovskite solar cells.Nature2023;624:557-63 PMCID:PMC10733143

[4] Park SM,Lempesis N.Low-loss contacts on textured substrates for inverted perovskite solar cells.Nature2023;624:289-94

[5] Brinkmann KO,Lang F.Perovskite-organic tandem solar cells.Nat Rev Mater2024;9:202-17

[6] Suchan K,Rehermann C,Kirchartz T.Rationalizing performance losses of wide bandgap perovskite solar cells evident in data from the Perovskite Database.Adv Energy Mater2024;14:2303420

[7] Wang YK,Li JY.In situ inorganic ligand replenishment enables bandgap stability in mixed-halide perovskite quantum dot solids.Adv Mater2022;34:e2200854

[8] Yao Y,Zhang C,Wang K.Organic hole-transport layers for efficient, stable, and scalable inverted perovskite solar cells.Adv Mater2022;34:e2203794

[9] Green MA,Yoshita M.Solar cell efficiency tables (version 62).Prog Photovoltaics2023;31:651-63

[10] Aydin E,De Bastiani M.Pathways toward commercial perovskite/silicon tandem photovoltaics.Science2024;383:eadh3849

[11] Xie L,Liu Y.Interface engineering for efficient raindrop solar cell.ACS Nano2022;16:5292-302

[12] Grandhi GK,Krishnaiah M.Wide-bandgap perovskite-inspired materials: defect-driven challenges for high-performance optoelectronics.Adv Funct Mater2023;2307441

[13] Feng HJ,Tsymbal EY.Tunable optical properties and charge separation in CH₃NH₃Sn_xPb_1-xI₃/TiO₂-based planar perovskites cells.J Am Chem Soc2015;137:8227-36

[14] Liu Z,Krogmeier B.Open-circuit voltages exceeding 1.26 V in planar methylammonium lead iodide perovskite solar cells.ACS Energy Lett2019;4:110-7

[15] Brinkmann KO,Zimmermann F.Perovskite-organic tandem solar cells with indium oxide interconnect.Nature2022;604:280-6

[16] Jiang Q,Xian Y.Surface reaction for efficient and stable inverted perovskite solar cells.Nature2022;611:278-83

[17] Lin R,Wei M.All-perovskite tandem solar cells with improved grain surface passivation.Nature2022;603:73-8

[18] Chen W,Xiu J.Monolithic perovskite/organic tandem solar cells with 23.6% efficiency enabled by reduced voltage losses and optimized interconnecting layer.Nat Energy2022;7:229-37

[19] Li L,Wang X.Flexible all-perovskite tandem solar cells approaching 25% efficiency with molecule-bridged hole-selective contact.Nat Energy2022;7:708-17

[20] Datta K,Hope MA.Light-induced halide segregation in 2D and quasi-2D mixed-halide perovskites.ACS Energy Lett2023;8:1662-70 PMCID:PMC10111410

[21] Zhang J,Guo Q.A universal grain “cage” to suppress halide segregation of mixed-halide inorganic perovskite solar cells.ACS Energy Lett2022;7:3467-75

[22] Wen J,Liu Z.Steric engineering enables efficient and photostable wide-bandgap perovskites for all-perovskite tandem solar cells.Adv Mater2022;34:e2110356

[23] Yang G,Yu ZJ.Defect engineering in wide-bandgap perovskites for efficient perovskite-silicon tandem solar cells.Nat Photon2022;16:588-94

[24] Wang C,Liang J.Suppressing phase segregation in wide bandgap perovskites for monolithic perovskite/organic tandem solar cells with reduced voltage loss.Small2022;18:e2204081

[25] Wright AD,Johnston MB.Temperature-dependent reversal of phase segregation in mixed-halide perovskites.Adv Mater2023;35:e2210834

[26] Shirzadi E,Ansari F,Hagfeldt A.Deconvolution of light-induced ion migration phenomena by statistical analysis of cathodoluminescence in lead halide-based perovskites.Adv Sci2022;9:e2103729 PMCID:PMC9069390

[27] Wang Z,Zhu T.Suppressed phase segregation for triple-junction perovskite solar cells.Nature2023;618:74-9

[28] Cai R,Wang X.Accelerated perovskite oxide development for thermochemical energy storage by a high-throughput combinatorial approach.Adv Energy Mater2023;13:2203833

[29] Sabino FP,Zunger A.Light-induced frenkel defect pair formation can lead to phase-segregation of otherwise miscible halide perovskite alloys.Adv Energy Mater2023;13:2301539

[30] Shin Y.Tunable ferroelectricity in oxygen-deficient perovskites with Grenier structure.npj Comput Mater2023;9:218

[31] Barker AJ,Deschler F.Defect-assisted photoinduced halide segregation in mixed-halide perovskite thin films.ACS Energy Lett2017;2:1416-24

[32] Mao W,Bernardi S.Light-induced reversal of ion segregation in mixed-halide perovskites.Nat Mater2021;20:55-61

[33] Brennan MC,Kamat PV.Photoinduced anion segregation in mixed halide perovskites.Trends Chem2020;2:282-301

[34] Chen Z,Tao S.Unified theory for light-induced halide segregation in mixed halide perovskites.Nat Commun2021;12:2687 PMCID:PMC8113520

[35] Bechtel JS.First-principles thermodynamics study of phase stability in inorganic halide perovskite solid solutions.Phys Rev Mater2018;2:045401

[36] Frohna K,Macpherson S.Nanoscale chemical heterogeneity dominates the optoelectronic response of alloyed perovskite solar cells.Nat Nanotechnol2022;17:190-6

[37] Ghasemi M,Zhou C.Controllable acceleration and deceleration of charge carrier transport in metal-halide perovskite single-crystal by Cs-cation induced bandgap engineering.Small2022;18:e2107680

[38] Mussakhanuly N,Bernardi S.Thermal disorder-induced strain and carrier localization activate reverse halide segregation.Adv Mater2024;36:e2311458

[39] Zhu C,Fu Y.Strain engineering in perovskite solar cells and its impacts on carrier dynamics.Nat Commun2019;10:815 PMCID:PMC6379394

[40] Yang F.Effects of size mismatch of halide ions on the phase stability of mixed halide perovskites.Phys Scr2024;99:025937

[41] Slotcavage DJ,Mcgehee MD.Light-induced phase segregation in halide-perovskite absorbers.ACS Energy Lett2016;1:1199-205

[42] Wang P,Cai B,Zheng X.Solution-processable perovskite solar cells toward commercialization: progress and challenges.Adv Funct Mater2019;29:1807661

[43] Li N,Chen Z.Microscopic degradation in formamidinium-cesium lead iodide perovskite solar cells under operational stressors.Joule2020;4:1743-58

[44] Gautam SK,Miquita DR,Geffroy B.Reversible photoinduced phase segregation and origin of long carrier lifetime in mixed-halide perovskite films.Adv Funct Mater2020;30:2002622

[45] Das B,Rau U.Effect of doping, photodoping, and bandgap variation on the performance of perovskite solar cells.Adv Opt Mater2022;10:2101947

[46] Wang T,Ardekani H.Sustainable materials acceleration platform reveals stable and efficient wide-bandgap metal halide perovskite alloys.Matter2023;6:2963-86

[47] Mannodi-kanakkithodi A.Data-driven design of novel halide perovskite alloys.Energy Environ Sci2022;15:1930-49

[48] Al-qaisi S,Alrebdi TA.First-principles investigations of Ba₂NaIO₆ double perovskite semiconductor: material for low-cost energy technologies.Mater Chem Phys2022;275:125237

[49] Liu Y,Liang J,Xiang P.Machine learning for perovskite solar cells and component materials: key technologies and prospects.Adv Funct Mater2023;33:2214271

[50] Li C.Methods, progresses, and opportunities of materials informatics.InfoMat2023;5:e12425

[51] Zhao Y,Zhang J.A bilayer conducting polymer structure for planar perovskite solar cells with over 1,400 hours operational stability at elevated temperatures.Nat Energy2022;7:144-52

[52] Zhao H,Huang H.A robotic platform for the synthesis of colloidal nanocrystals.Nat Synth2023;2:505-14

[53] Liu S,Liu Y.Data-driven controlled synthesis of oriented quasi-spherical CsPbBr₃ perovskite materials.Angew Chem Int Ed Engl2024;63:e202319480

[54] Wu L,Yuan Z.Data-driven fine element tuning of halide double perovskite for enhanced photoluminescence.Adv Opt Mater2024;12:2301245

[55] Wang Z,Yin H.Data-driven materials innovation and applications.Adv Mater2022;34:e2104113

[56] Wang Z,Xie X.Applications of machine learning in perovskite materials.Adv Compos Hybrid Mater2022;5:2700-20

[57] Liu Y,Han S.How machine learning predicts and explains the performance of perovskite solar cells.Solar RRL2022;6:2101100

[58] Hu Y,Zhang L.Machine-learning modeling for ultra-stable high-efficiency perovskite solar cells.Adv Energy Mater2022;12:2201463

[59] Priyanga GS,Nagappan N,Thomas T.Prediction of nature of band gap of perovskite oxides (ABO₃) using a machine learning approach.J Materiomics2022;8:937-48

[60] Chen C,Zuo Y,Ong SP.Graph networks as a universal machine learning framework for molecules and crystals.Chem Mater2019;31:3564-72

[61] Chen C.AtomSets as a hierarchical transfer learning framework for small and large materials datasets.npj Comput Mater2021;7:173

[62] Jacobsson TJ,García-fernández A.An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles.Nat Energy2022;7:107-15

[63] Liu Y,Zhu H,Guan L.Study on bandgap predications of ABX₃-type perovskites by machine learning.Org Electron2022;101:106426

[64] Yang C,Hu M.Accelerating the discovery of hybrid perovskites with targeted band gaps via interpretable machine learning.ACS Appl Mater Interfaces2023;15:40419-27

[65] Ong SP,Jain A.Python materials genomics (pymatgen): a robust, open-source python library for materials analysis.Comp Mater Sci2013;68:314-9

[66] Chen C,Ye W,Ong SP.Learning properties of ordered and disordered materials from multi-fidelity data.Nat Comput Sci2021;1:46-53

[67] Coley CW,Green WH,Jensen KF.Convolutional embedding of attributed molecular graphs for physical property prediction.J Chem Inf Model2017;57:1757-72

[68] Wang J,Ji X,Lu W.Feature selection in machine learning for perovskite materials design and discovery.Materials2023;16:3134 PMCID:PMC10146176

[69] Chen C.A universal graph deep learning interatomic potential for the periodic table.Nat Comput Sci2022;2:718-28

[70] Deng B,Jun K.CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling.Nat Mach Intell2023;5:1031-41

[71] Jain A,Hautier G.Commentary: the materials project: a materials genome approach to accelerating materials innovation.APL Materials2013;1:011002

[72] Sher A,Chen AB.Quasichemical approximation in binary alloys.Phys Rev B Condens Matter1987;36:4279-95

[73] Phan AT,Kang Y.Phase equilibria and thermodynamics of the Fe–Al–C system: critical evaluation, experiment and thermodynamic optimization.Acta Mater2014;79:1-15

[74] Wasiur-rahman S.Critical assessment and thermodynamic modeling of the binary Mg–Zn, Ca–Zn and ternary Mg–Ca–Zn systems.Intermetallics2009;17:847-64

[75] Zhu T,Grater L. Coupling photogeneration with thermodynamic modeling of light-induced alloy segregation enables the discovery of stabilizing dopants. arXiv. [Preprint.] Jan 30, 2023. [accessed on 22 May 2024]. Available from: https://doi.org/10.48550/arXiv.2301.12627.

[76] Abedi S,Baninajarian S.Statistical analysis of the performance of a variety of first-principles schemes for accurate prediction of binary semiconductor band gaps.J Chem Phys2023;158:184109

[77] Ramadan AJ,Johnston MB.Methylammonium-free wide-bandgap metal halide perovskites for tandem photovoltaics.Nat Rev Mater2023;8:822-38

[78] Peng S,Braun M.Kinetics and mechanism of light-induced phase separation in a mixed-halide perovskite.Matter2023;6:2052-65

[79] Wu P,Saidaminov MI.A Roadmap for efficient and stable all-perovskite tandem solar cells from a chemistry perspective.ACS Cent Sci2023;9:14-26 PMCID:PMC9881206

[80] Eperon GE,Menelaou C,Herz LM.Formamidinium lead trihalide: a broadly tunable perovskite for efficient planar heterojunction solar cells.Energy Environ Sci2014;7:982

[81] Brivio F,Walsh A.Structural and electronic properties of hybrid perovskites for high-efficiency thin-film photovoltaics from first-principles.APL Mater2013;1:042111

[82] Noh JH,Heo JH,Seok SI.Chemical management for colorful, efficient, and stable inorganic-organic hybrid nanostructured solar cells.Nano Lett2013;13:1764-9

[83] Tao S,Brocks G.Absolute energy level positions in tin- and lead-based halide perovskites.Nat Commun2019;10:2560 PMCID:PMC6561953

[84] Butler KT,Walsh A.Band alignment of the hybrid halide perovskites CH₃NH₃PbCl₃, CH₃NH₃PbBr₃ and CH₃NH₃PbI₃.Mater Horiz2015;2:228-31

[85] Lu X,Li K.First-principles insight into the photoelectronic properties of Ge-based perovskites.RSC Adv2016;6:86976-81

[86] Braly IL,Rajagopal A.Current-induced phase segregation in mixed halide hybrid perovskites and its impact on two-terminal tandem solar cell design.ACS Energy Lett2017;2:1841-7

[87] Dong X,Niu T.Phase-pure engineering for efficient and stable formamidinium-based perovskite solar cells.Solar RRL2022;6:2200060

[88] Otero-Martínez C,Schrenker NJ.Fast A-site cation cross-exchange at room temperature: single-to double- and triple-cation halide perovskite nanocrystals.Angew Chem Int Ed Engl2022;61:e202205617 PMCID:PMC9540746

[89] Boldyreva AG,Tsarev S.Unraveling the impact of hole transport materials on photostability of perovskite films and p-i-n solar cells.ACS Appl Mater Interfaces2020;12:19161-73

[90] Xie LQ,Nan ZA.Understanding the cubic phase stabilization and crystallization kinetics in mixed cations and halides perovskite single crystals.J Am Chem Soc2017;139:3320-3

[91] Zhong Y,Wang X.Inhibition of ion migration for highly efficient and stable perovskite solar cells.Adv Mater2023;35:e2302552

[92] Mathew P,Kamat PV.Ramifications of ion migration in 2D lead halide perovskites.ACS Energy Lett2024;9:1103-14

[93] Zhang L,Jiang Y.Stable and efficient mixed-halide perovskite LEDs.ChemSusChem2024;17:e202301205

[94] Sun H,Liu X.Suppressed phase segregation with small A-site and large X-site incorporation for photostable wide-bandgap perovskite solar cells.Small Methods2024;17:e2400067

[95] Wang C,Zhou B.Self-healing behavior of the metal halide perovskites and photovoltaics.Small2024;20:e2307645

[96] Wang K,Zhang J.Short-range migration of A-site cations inhibit photoinduced phase segregation in FA_xMA_yCs_1-x-yPbI_3-zBr_z single crystals.J Phys Chem C2021;125:23050-7

[97] Cho J.Photoinduced phase segregation in mixed halide perovskites: thermodynamic and kinetic aspects of Cl–Br segregation.Adv Opt Mater2021;9:2001440

[98] Knight AJ.Preventing phase segregation in mixed-halide perovskites: a perspective.Energy Environ Sci2020;13:2024-46

[99] Chen S,Chen H.Exploring the stability of novel wide bandgap perovskites by a robot based high throughput approach.Adva Energy Mater2018;8:1701543

[100] Cao J,Liu S.Tailoring the Cs/Br ratio for efficient and stable wide-bandgap perovskite solar cells.Solar RRL2023;7:2200955