Combinatorial Synthesis and Screening of Mixed Halide Perovskite Megalibraries DOI
Minliang Lai, Donghoon Shin, Liban Jibril

et al.

Journal of the American Chemical Society, Journal Year: 2022, Volume and Issue: 144(30), P. 13823 - 13830

Published: July 21, 2022

A significant bottleneck in the discovery of new mixed halide perovskite (MHP) compositions and structures is time-consuming low-throughput nature current synthesis screening methods. Here, a high-throughput strategy presented that can be used to synthesize combinatorial libraries MHPs with deliberate control over mixing ratio particle size (for example, CsPb(Br1–xClx)3 (0 < x 1) sizes between ∼100 400 nm). This combines evaporation–crystallization polymer pen lithography (EC-PPL) defect-engineered anion exchange spatially encode composition, respectively. Laser exposure selectively modify defect concentration individual particles, thus degree subsequent exchange, allowing preparation for ultra-high-density arrays distinct (>1 unique particle/μm2). method was utilized rapidly generate library ∼4000 particles then screened high-efficiency blue photoemission, which yielded CsPb(Br0.6Cl0.4)3 as composition highest photoluminescence intensity. The provided here, mechanistic understanding defect-engineering process gleaned from it, will enable rapid exceptional MHP optoelectronic materials.

Language: Английский

Nanoreactors for particle synthesis DOI
Jordan H. Swisher, Liban Jibril, Sarah Hurst Petrosko

et al.

Nature Reviews Materials, Journal Year: 2022, Volume and Issue: 7(6), P. 428 - 448

Published: Jan. 13, 2022

Language: Английский

Citations

86
Colloidal Quantum Dot Solar Cells: Progressive Deposition Techniques and Future Prospects on Large‐Area Fabrication DOI
Qian Zhao, Rui Han, Ashley R. Marshall

et al.

Advanced Materials, Journal Year: 2022, Volume and Issue: 34(17)

Published: Jan. 13, 2022

Colloidally grown nanosized semiconductors yield extremely high-quality optoelectronic materials. Many examples have pointed to near perfect photoluminescence quantum yields, allowing for technology-leading materials such as high purity color centers in display technology. Furthermore, because of chemical yield, and improved understanding the surfaces, these materials, particularly colloidal dots (QDs) can also be ideal candidates other applications. Given urgent necessity toward carbon neutrality, electricity from solar photovoltaics will play a large role power generation sector. QDs are developed shown dramatic improvements over past 15 years photoactive with various innovative deposition properties which lead exceptionally low-cost high-performance devices. Once key issues related charge transport optically thick arrays addressed, QD-based photovoltaic technology become better candidate practical application. In this article, authors show how possibilities different techniques bring cells industrial level discuss challenges perovskite QD particular, achieve large-area fabrication further advancing solve pivotal energy environmental issues.

Language: Английский

Citations

82
Self‐Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow DOI Creative Commons

Kameel Abdel‐Latif,

Robert W. Epps, Fazel Bateni

et al.

Advanced Intelligent Systems, Journal Year: 2020, Volume and Issue: 3(2)

Published: Dec. 10, 2020

Identifying the optimal formulation of emerging inorganic lead halide perovskite quantum dots (LHP QDs) with their vast colloidal synthesis universe and multiple synthesis/postsynthesis processing parameters is a challenging undertaking for material‐ time‐intensive, batch strategies. Herein, modular microfluidic strategy, integrated an artificial intelligence (AI)‐guided decision‐making agent intelligent navigation through complex LHP QDs 10 individually controlled accessible parameter space exceeding 2 × 7 , introduced. Utilizing developed autonomous experimentation strategy within global learning framework, rapidly identified two‐step postsynthesis exchange reaction, different emission colors in less than 40 min per desired peak energy. Using two in‐series reactors enables continuous bandgap engineering via in‐line reactions without need intermediate washing step. inert gas three‐phase flow format successful, self‐synchronized delivery salt precursor into moving droplets containing QDs, resulting accelerated closed‐loop optimization end‐to‐end manufacturing optoelectronic properties.

Language: Английский

Citations

82
The case for data science in experimental chemistry: examples and recommendations DOI
Junko Yano, Kelly J. Gaffney, John M. Gregoire

et al.

Nature Reviews Chemistry, Journal Year: 2022, Volume and Issue: 6(5), P. 357 - 370

Published: April 21, 2022

Language: Английский

Citations

61
Intelligent control of nanoparticle synthesis through machine learning DOI
Honglin Lv, Xueye Chen

Nanoscale, Journal Year: 2022, Volume and Issue: 14(18), P. 6688 - 6708

Published: Jan. 1, 2022

The synthesis of nanoparticles is affected by many reaction conditions, and their properties are usually determined factors such as size, shape surface chemistry. In order for the synthesized to have functions suitable different fields (for example, optics, electronics, sensor applications so on), precise control essential. However, with current technology preparing on a microreactor, it time-consuming laborious achieve synthesis. improve efficiency synthesizing expected functionality, application machine learning-assisted an intelligent choice. this article, we mainly introduce typical methods microreactors, explain principles procedures learning, well main ways obtaining data sets. We studied three types representative nanoparticle preparation assisted learning. Finally, problems in future development prospects discussed.

Language: Английский

Citations

41
Toward the Controlled Synthesis of Lead Halide Perovskite Nanocrystals DOI
Changjiu Sun, Yuanzhi Jiang, Li Zhang

et al.

ACS Nano, Journal Year: 2023, Volume and Issue: 17(18), P. 17600 - 17609

Published: Sept. 8, 2023

Lead halide perovskite nanocrystals (LHP NCs) have rapidly emerged as one of the most promising materials for optical sources, photovoltaics, and sensor fields. The controlled synthesis LHP NCs with high monodispersity precise size tunability has been a subject intensive research in recent years. However, due to their ionic nature, are usually formed instantaneously, corresponding nucleation growth difficult monitor regulated. In this Perspective, we summarize representative attempts achieve NCs. We first highlight burst rapid characteristics conventional methods. Afterward, introduce scheme changing into kinetically dominant, continuously size-tunable via nucleation–growth decoupling. also methods eliminate undesired ripening effects homogeneous distribution through rational ligand selection solvent engineering. hope Perspective will facilitate development protocols advance understanding crystal fundamentals materials.

Language: Английский

Citations

38
Progress and Application of Halide Perovskite Materials for Solar Cells and Light Emitting Devices DOI Creative Commons
Maoding Cheng,

Jingtian Jiang,

Chao Yan

et al.

Nanomaterials, Journal Year: 2024, Volume and Issue: 14(5), P. 391 - 391

Published: Feb. 20, 2024

Halide perovskite materials have attracted worldwide attention in the photovoltaic area due to rapid improvement efficiency, from less than 4% 2009 26.1% 2023 with only a nanometer lever photo-active layer. Meanwhile, this nova star found applications many other areas, such as light emitting, sensor, etc. This review started fundamentals of physics and chemistry behind excellent performance halide for photovoltaic/light emitting methods preparing them. Then, it described basic principles solar cells devices. It summarized strategies including nanotechnology improve application these two areas: structure–property relation how each component devices affects overall performance. Moreover, listed challenges future materials.

Language: Английский

Citations

14
Designing workflows for materials characterization DOI Open Access
Sergei V. Kalinin, Maxim Ziatdinov, Mahshid Ahmadi

et al.

Applied Physics Reviews, Journal Year: 2024, Volume and Issue: 11(1)

Published: March 1, 2024

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis new material typically followed a set steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, sequence synthesis methods their interpretation, research workflow, has traditionally been driven human intuition highly domain specific. Here, we explore concepts scientific workflows that emerge at interface between theory, characterization, imaging. We discuss criteria which these can be constructed special cases multiresolution structural imaging as part more general workflows. Some considerations theory–experiment are provided. further pose emergence user facilities cloud labs disrupts classical progression from ideation, orchestration, execution stages workflow development. To accelerate this transition, propose framework design, including universal hyperlanguages describing laboratory operation, ontological matching, reward functions integration domains, policy development optimization. These tools will enable knowledge-based optimization; lateral instrumental networks, sequential parallel orchestration dissimilar facilities; empower distributed research.

Language: Английский

Citations

12
Understanding Hot Injection Quantum Dot Synthesis Outcomes Using Automated High-Throughput Experiment Platforms and Machine Learning DOI
Rui Xu, Logan P. Keating, Ajit Vikram

et al.

Chemistry of Materials, Journal Year: 2024, Volume and Issue: 36(3), P. 1513 - 1525

Published: Jan. 31, 2024

Machine learning (ML) has demonstrated potential toward accelerating synthesis planning for various material systems. However, ML remained out of reach many materials scientists due to the lack systematic approaches or heuristics developing workflows synthesis. In this work, we report an approach selecting algorithms train models predicting nanomaterial outcomes. Specifically, developed and used automated batch microreactor platform collect a large experimental data set hot-injection outcomes CdSe quantum dots. Thereafter, was using algorithms. The relative performances these were compared sets different sizes with amounts noise added. Neural-network-based show most accurate predictions absorption emission peak, while cascade full width at half-maximum shown be superior direct approach. SHapley Additive exPlanations (SHAP) determine importance parameters. Our analyses indicate that SHAP scores are highly dependent on feature selection highlight inherently interpretable gaining insights from

Language: Английский

Citations

11
Lead-Free Halide Perovskites for Photocatalysis via High-Throughput Exploration DOI
Astita Dubey, Sheryl L. Sanchez, Jonghee Yang

et al.

Chemistry of Materials, Journal Year: 2024, Volume and Issue: 36(5), P. 2165 - 2176

Published: Feb. 27, 2024

This Perspective navigates the transformative synergy between machine learning (ML) techniques and high-throughput (HT) methodologies in realm of photocatalysis, aiming to overcome inefficiencies drawbacks associated with existing photocatalysts. Pb-free hybrid perovskite (HP) nanocrystals (NCs) emerge as promising candidates, offering distinctive physicochemical optical attributes addition nontoxicity. The integration HT automated methods accelerates synthesis characterization novel HP materials while also addressing challenges obtaining large, high-quality data sets for training ML models. proposed multidisciplinary approach, combining experimental computational simulations, aims unravel complexities photocatalytic systems, fostering development innovative strategies development. convergence techniques, is poised revolutionize photocatalysis (PC), propelling field into an era unprecedented discovery innovation.

Language: Английский

Citations

9