Deniz N. Cakan, Rishi E. Kumar, Eric Oberholtz, Moses Kodur, Jack R. Palmer, Apoorva Gupta, Ken Kaushal, Hendrik M. Vossler and David P. Fenning
{"title":"PASCAL:包晶自动旋涂组装线加快了三卤化物包晶合金的成分筛选速度","authors":"Deniz N. Cakan, Rishi E. Kumar, Eric Oberholtz, Moses Kodur, Jack R. Palmer, Apoorva Gupta, Ken Kaushal, Hendrik M. Vossler and David P. Fenning","doi":"10.1039/D4DD00075G","DOIUrl":null,"url":null,"abstract":"<p >The Perovskite Automated Spin Coat Assembly Line – PASCAL – is introduced as a materials acceleration platform for the deposition and characterization of spin-coated thin films, with specific application to halide perovskites. We first demonstrate improved consistency of perovskite film fabrication by controlling process parameters, the influence of which is uniquely exposed under the automated experimental framework. Next, we report on an automated campaign of composition engineering to improve the durability of perovskite absorbers for tandem solar cell applications. We screen compositions spanning the triple-cation, triple-halide composition space, MA<small><sub><em>x</em></sub></small>FA<small><sub>0.78</sub></small>Cs<small><sub>0.22−<em>x</em></sub></small>Pb(I<small><sub>0.8−<em>y</em>−<em>z</em></sub></small>Br<small><sub><em>y</em></sub></small>Cl<small><sub><em>z</em></sub></small>)<small><sub>3</sub></small>. Data-driven clustering identifies four characteristic behaviors within this space regarding figures of merit for durability and open-circuit voltage, with data from each sample acquired automatically in PASCAL characterization line. Finally, a film composition durable to light and elevated temperature exposure is identified <em>via</em> a regression model trained on the high-throughput dataset. The approach, hardware, and data detailed herein highlight automated platforms as an opportunity to accelerate the identification and discovery of novel thin film materials and demonstrates the efficacy of PASCAL specifically for automation of solution-processed optoelectronic thin film research.</p>","PeriodicalId":72816,"journal":{"name":"Digital discovery","volume":" 6","pages":" 1236-1246"},"PeriodicalIF":6.2000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/dd/d4dd00075g?page=search","citationCount":"0","resultStr":"{\"title\":\"PASCAL: the perovskite automated spin coat assembly line accelerates composition screening in triple-halide perovskite alloys†\",\"authors\":\"Deniz N. Cakan, Rishi E. Kumar, Eric Oberholtz, Moses Kodur, Jack R. Palmer, Apoorva Gupta, Ken Kaushal, Hendrik M. Vossler and David P. Fenning\",\"doi\":\"10.1039/D4DD00075G\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >The Perovskite Automated Spin Coat Assembly Line – PASCAL – is introduced as a materials acceleration platform for the deposition and characterization of spin-coated thin films, with specific application to halide perovskites. We first demonstrate improved consistency of perovskite film fabrication by controlling process parameters, the influence of which is uniquely exposed under the automated experimental framework. Next, we report on an automated campaign of composition engineering to improve the durability of perovskite absorbers for tandem solar cell applications. We screen compositions spanning the triple-cation, triple-halide composition space, MA<small><sub><em>x</em></sub></small>FA<small><sub>0.78</sub></small>Cs<small><sub>0.22−<em>x</em></sub></small>Pb(I<small><sub>0.8−<em>y</em>−<em>z</em></sub></small>Br<small><sub><em>y</em></sub></small>Cl<small><sub><em>z</em></sub></small>)<small><sub>3</sub></small>. Data-driven clustering identifies four characteristic behaviors within this space regarding figures of merit for durability and open-circuit voltage, with data from each sample acquired automatically in PASCAL characterization line. Finally, a film composition durable to light and elevated temperature exposure is identified <em>via</em> a regression model trained on the high-throughput dataset. The approach, hardware, and data detailed herein highlight automated platforms as an opportunity to accelerate the identification and discovery of novel thin film materials and demonstrates the efficacy of PASCAL specifically for automation of solution-processed optoelectronic thin film research.</p>\",\"PeriodicalId\":72816,\"journal\":{\"name\":\"Digital discovery\",\"volume\":\" 6\",\"pages\":\" 1236-1246\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.rsc.org/en/content/articlepdf/2024/dd/d4dd00075g?page=search\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digital discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2024/dd/d4dd00075g\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital discovery","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/dd/d4dd00075g","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
PASCAL: the perovskite automated spin coat assembly line accelerates composition screening in triple-halide perovskite alloys†
The Perovskite Automated Spin Coat Assembly Line – PASCAL – is introduced as a materials acceleration platform for the deposition and characterization of spin-coated thin films, with specific application to halide perovskites. We first demonstrate improved consistency of perovskite film fabrication by controlling process parameters, the influence of which is uniquely exposed under the automated experimental framework. Next, we report on an automated campaign of composition engineering to improve the durability of perovskite absorbers for tandem solar cell applications. We screen compositions spanning the triple-cation, triple-halide composition space, MAxFA0.78Cs0.22−xPb(I0.8−y−zBryClz)3. Data-driven clustering identifies four characteristic behaviors within this space regarding figures of merit for durability and open-circuit voltage, with data from each sample acquired automatically in PASCAL characterization line. Finally, a film composition durable to light and elevated temperature exposure is identified via a regression model trained on the high-throughput dataset. The approach, hardware, and data detailed herein highlight automated platforms as an opportunity to accelerate the identification and discovery of novel thin film materials and demonstrates the efficacy of PASCAL specifically for automation of solution-processed optoelectronic thin film research.