End-capped engineering of Quinoxaline core-based non-fullerene acceptor materials with improved power conversion efficiency

Journal of Molecular Graphics and Modelling, Journal Year: 2023, Volume and Issue: 127, P. 108699 - 108699

Published: Dec. 23, 2023

Language: Английский

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The Solution is the Solution: Data-Driven Elucidation of Solution-to-Device Feature Transfer for π-Conjugated Polymer Semiconductors

ACS Applied Materials & Interfaces, Journal Year: 2022, Volume and Issue: 14(3), P. 3613 - 3620

Published: Jan. 17, 2022

The advent of data analytics techniques and materials informatics provides opportunities to accelerate the discovery development organic semiconductors for electronic devices. However, engineering solutions is limited by ability control thin-film morphology in an immense parameter space. combination high-throughput experimentation (HTE) laboratory offers tremendous avenues traverse expansive domains tunable variables offered semiconductor thin films. This Perspective outlines steps required incorporate a comprehensive methodology into experimental polymer-based technologies. translation solution processing property metrics behavior crucial inform efficient HTE collection application data-centric tools construct new process-structure-property relationships. We argue that detailed investigation state prior deposition conjunction with characterization will yield deeper understanding physicochemical mechanisms influencing performance π-conjugated polymer electronics, data-driven approaches offering predictive capabilities previously unattainable via traditional means.

Language: Английский

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Molecular Thin Films Enable the Synthesis and Screening of Nanoparticle Megalibraries Containing Millions of Catalysts

Journal of the American Chemical Society, Journal Year: 2023, Volume and Issue: 145(25), P. 14031 - 14043

Published: June 13, 2023

Megalibraries are centimeter-scale chips containing millions of materials synthesized in parallel using scanning probe lithography. As such, they stand to accelerate how discovered for applications spanning catalysis, optics, and more. However, a long-standing challenge is the availability substrates compatible with megalibrary synthesis, which limits structural functional design space that can be explored. To address this challenge, thermally removable polystyrene films were developed as universal substrate coatings decouple lithography-enabled nanoparticle synthesis from underlying chemistry, thus providing consistent lithography parameters on diverse substrates. Multi-spray inking arrays polymer solutions metal salts allows patterning >56 million nanoreactors designed vary composition size. These subsequently converted inorganic nanoparticles via reductive thermal annealing, also removes deposit megalibrary. mono-, bi-, trimetallic synthesized, size was controlled between 5 35 nm by modulating speed. Importantly, coating used conventional like Si/SiOx, well typically more difficult pattern on, such glassy carbon, diamond, TiO2, BN, W, or SiC. Finally, high-throughput discovery performed context photocatalytic degradation organic pollutants Au-Pd-Cu megalibraries TiO2 2,250,000 unique composition/size combinations. The screened within 1 h developing fluorescent thin-film top proxies catalytic turnover, revealing Au0.53Pd0.38Cu0.09-TiO2 most active photocatalyst composition.

Language: Английский

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Machine Learning Study on the Virtual Screening of Donor–Acceptor Pairs for Organic Solar Cells

physica status solidi (a), Journal Year: 2024, Volume and Issue: 221(9)

Published: March 11, 2024

The selection of electron donors and nonfullerene acceptors (NFAs) in organic solar cells (OSCs) is crucial for improving photovoltaic performance. Machine learning (ML) has brought a breakthrough solution. Herein, 292 donor‐NFA pairs with experimental OSC parameters from the reported articles are collected. ML descriptors include device processing parameters, molecular properties, structure. five regression models, random forest (RF), extra tree regression, gradient boosting tree, adaptive boosting, artificial neural network (ANN) trained. GridSearchCV used hyperparameter optimization models. SHapley Additive exPlanation approach employed to analyze descriptor importance. Among trained RF model shows superior performance, achieving Pearson's correlation coefficient ( r ) 0.81 on test set. Based NFAs constructed dataset, 9779 donor–NFA OSCs generated by randomly combining donor acceptor molecules. utilized predict power conversion efficiency (PCE) new donor–acceptor OSCs. results indicate that composed PBDB‐TF as L8‐BO can achieve remarkable PCE 17.9%.

Language: Английский

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Roadmap on metal-halide perovskite semiconductors and devices

Materials Today Electronics, Journal Year: 2025, Volume and Issue: unknown, P. 100138 - 100138

Published: Jan. 1, 2025

Language: Английский

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