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Structural modification on Dimethoxythienothiophene based non-fullerene acceptor molecule for construction of high-performance organic chromophores by employing DFT approach

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Comprehensive quantum chemical calculations and molecular docking analysis of uracil mustard by first principle

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Exploration of charge transfer analysis and photovoltaics properties of A-D-A type non-fullerene phenazine based molecules to enhance the organic solar cell properties

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Machine Learning Assisted Prediction of Power Conversion Efficiency of All-Small Molecule Organic Solar Cells: A Data Visualization and Statistical Analysis

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Machine Learning for Organic Photovoltaic Polymers: A Minireview

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Transition Metal-Decorated Mg12O12 Nanoclusters as Biosensors and Efficient Drug Carriers for the Metformin Anticancer Drug

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Meticulous research for design of plasmonics sensors for cancer detection and food contaminants analysis via machine learning and artificial intelligence

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Expert systems for predicting the efficiencies of photomultiplication organic photodetectors

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Quantum Chemical Modeling Approach Toward Phenothiazine‐Based DyeSensitized Solar Cells: Role of Tetracene and Pentacene π‐Spacers in Photovoltaic and Electrochemical Performance

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Functional Organic Materials for Photovoltaics: The Synthesis as a Tool for Managing Properties for Solid State Applications

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Machine Learning Approaches for Predicting Power Conversion Efficiency in Organic Solar Cells: A Comprehensive Review

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Implementing High‐Throughput Screening of Organic Solar Cells using Transfer Learning Based on Fine‐Tuning Neural Network Strategy

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A Theoretical Perspective on the Thermodynamic Stability of Polymer Blends for Solar Cells: From Experiments to Predictive Modeling

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From setup to analysis: A compact guide to performing Molecular Dynamics simulations of ion transport in solids

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Revealing the photoelectric performance and multistep electron transfer mechanism in D-A-π-A dyes coupled with a chlorophyll derivative for co-sensitized solar cells

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Learning from Fullerenes and Predicting for Y6: Machine Learning and High‐Throughput Screening of Small Molecule Donors for Organic Solar Cells

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An innovative approach to design readily synthesizable polymers for all-polymer solar cells

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Probing the Site-Specific Reactivity and Catalytic Activity of Agn (n = 15–20) Silver Clusters

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Feature-driven machine learning approach for predicting photophysical properties of fluorescent compounds: A cheminformatics pipeline

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Multidimensional modelling and designing of efficient small molecule acceptors for organic solar cells

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Designing of a Novel Candidate Multi-epitope Vaccine to boost Immune Responses against SARS‐COV‐2 using Immunoinformatics and Machine Learning based Approach

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Multinomial classification of NLRP3 inhibitory compounds based on large scale machine learning approaches

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Predictive Modeling and Design of Organic Solar Cells: A Data-Driven Approach for Material Innovation

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The use of machine learning, density functional theory, and molecular dynamics simulations for the designing and screening of efficient small molecule donors for organic solar cells

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Active Discovery of Donor:Acceptor Combinations For Efficient Organic Solar Cells

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Experimental and theoretical investigations of a multiwalled carbon nanotubes/SnO2/polyaniline ternary nanohybrid electrode for energy storage

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Prediction of UV/visible absorption maxima of organic compounds in dichloromethane and database generation of organic compounds with red-shifted absorption maxima

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High electron mobility due to extra π-conjugation in the end-capped units of non-fullerene acceptor molecules: a DFT/TD-DFT-based prediction

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Structural, vibrational, fluorescence spectral features, Hirshfeld surface analysis, docking and drug likeness studies on 4-(2-bromo-4-methyl-phenoxymethyl)-6-methyl-coumarin derivative: Experimental and theoretical studies

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Exploration of nonlinear optical behavior in asymmetric dithieno [3,2b:2′,3′d] pyrrole based push pull constrain: A theoretical approach

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Predicting the multiple parameters of organic acceptors through machine learning using RDkit descriptors: An easy and fast pipeline

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Effect of electron-donating groups on the excited state spectroscopy and dynamics of 2′-hydroxychalcone derivatives

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Theoretical analysis on D-π-A dye molecules with different acceptors and terminal branches for highly efficient dye-sensitized solar cells

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Shadow Molecular Dynamics for a Charge-Potential Equilibration Model

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Machine learning assisted designing of Indacenodithiophene (IDT)-based polymers for future application of photoacoustic imaging

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Theoretical designing of small molecule donors for organic solar cells: Analyzing the effect of molecular polarity through structural engineering at terminal position

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From Corpus to Innovation: Advancing Organic Solar Cell Design with Large Language Models

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Towards estimation and mechanism of CO2 adsorption on zeolite adsorbents using molecular simulations and machine learning

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Investigating the adsorption processes of polymer resins for the removal of micropollutants: A comprehensive review in the field of environmental remediation

Jaouad Bensalah, Abhinay Thakur and Ashish Kumar

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Intrinsic Reactivity Index as Descriptor for Accurately Predicting Short-Circuit Current Density in Ternary Organic Solar Cells

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Computational design of new polymers having low exciton binding energy for organic solar cells fabrication: Chemical generation and visualization

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Improved efficiency and stability for acridine orange sensitizers by adding electron donating/accepting π-linker moieties

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The Key Descriptors for Predicting the Exciton Binding Energy of Organic Photovoltaic Materials

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Search of electron-rich and electron-deficient building blocks through data mining and library generation for the designing of polymers for organic solar cells

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Asif Mahmood, Sumaira Naeem, Afra Javed, Zunaira Shafiq, Mohamed A. El-Sheikh, Hosam O. Elansary and Muhammad Ramzan Saeed Ashraf Janjua

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Tuning the optoelectronic properties of selenophene-diketopyrrolopyrrole-based non-fullerene acceptor to obtain efficient organic solar cells through end-capped modification

Rimsha Ijaz, Muhammad Waqas, Ahmed Mahal, Manel Essid, Imen Zghab, Rasheed Ahmad Khera, Hadil Faris Alotaibi, Maysoon Al-Haideri, Ali S. Alshomrany, Saba Zahid, Naifa S. Alatawi and Zouhaier Aloui

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Exploring the Electronic, Optical, and Charge Transfer Properties of A-D-A-Type IDTV-ThIC-Based Molecules To Enhance Photovoltaic Performance of Organic Solar Cells

Maham Majeed, Muhammad Waqas, Zouhaier Aloui, Manel Essid, Mahmoud A. A. Ibrahim, Rasheed Ahmad Khera, Mohamed Shaban and Muhammad Ans

ACS Omega, 2023, 8, 45384
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Designing high-efficiency organic semi-conductors for organic photodetectors assisted by machine learning and property prediction

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Perspectives on Development of Optoelectronic Materials in Artificial Intelligence Age

Ting Yuan, Xianzhi Song, Yuxin Shi, Shuyan Wei, Yuyi Han, Linjuan Yang, Yang Zhang, Xiaohong Li, Yunchao Li, Lin Shen and Louzhen Fan

Chemistry An Asian Journal, 2024, 19
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Methods, progresses, and opportunities of materials informatics

Chen Li and Kun Zheng

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Green energy harvesting from CO2 and NOx by MXene materials: Detailed historical and future prospective

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OMNI-P2x universal neural network potential for excited-state simulations

Mikołaj Martyka, Xin-Yu Tong, Joanna Jankowska and Pavlo O. Dral

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Investigation of the Anticancer Potential of 2-alkoxycarbonylallyl Esters Against Metastatic Murine Breast Cancer Line 4T1 Targeting the EGFR: A Combined Molecular Docking, QSAR, and Machine Learning Approach

Babatunde Samuel Obadawo, Oluwatoba Emmanuel Oyeneyin, Taoreed Olakunle Owolabi, Damilohun Samuel Metibemu, Nureni Ipinloju, Kehinde Henry Fagbohungbe, Helen Omonipo Modamori and Victor Olanrewaju Olatoye

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A machine learning-assisted study on organic solvents in electrolytes for expanding the electrochemical stable window of zinc-ion batteries

Guangsheng Xu, Yajuan Zhang, Mingxi Jiang, Jinliang Li, Hengchao Sun, Jiabao Li, Ting Lu, Chenglong Wang, Guang Yang and Likun Pan

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Singlet‐Triplet Energy Gap as a Critical Molecular Descriptor for Predicting Organic Photovoltaic Efficiency

Guangchao Han and Yuanping Yi

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Design of polymers with higher atomization energy with help of machine learning and chemical space generation

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A machine learning prediction model for quantitative analyzing the influence of non-radiative voltage loss on non-fullerene organic solar cells

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Ground-State Descriptor Enables Machine Learning-Assisted Virtual Screening of AIE-Active Mechanofluorochromic Molecules with High Contrast

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The Key Descriptors for Predicting the Exciton Binding Energy of Organic Photovoltaic Materials

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Designing of novel organic semiconductors materials for organic solar cells: A machine learning assisted proficient pipeline

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Rational polymer design for organic solar cells through similarity index-based data mining

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A systematic approach to generate polymer library: A search for polymers with high dipole moment

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Data-driven design of polymers for possible use for fluorescent applications

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Strategies and Mechanisms To Minimize Energy Loss in Non-Fullerene Bulk Heterojunction Organic Solar Cells: Experimental and Computational Approaches

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In Silico-DFT Investigation of Nanocluster Alloys of Al-(Mg, Ge, Sn) Coated by Nitrogen Heterocyclic Carbenes as Corrosion Inhibitors

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Designing of benzofuran‐based monomers for photodetectors through similarity analysis and library enumeration

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Directed Message Passing Neural Network for Predicting Power Conversion Efficiency in Organic Solar Cells

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Refine the evaluation of photophysical properties of organometallic chromophores under confined molecular crystal conditions

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Multidimensional modeling assisted mining of GDB17 chemical database: A search for polymer donors for organic solar cells and machine learning assisted performance prediction

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Data mining and library generation to search electron-rich and electron-deficient building blocks for the designing of polymers for photoacoustic imaging

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Energy Level Prediction of Organic Semiconductors for Photodetectors and Mining of a Photovoltaic Database to Search for New Building Units

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A bibliometric analysis of machine learning techniques in photovoltaic cells and solar energy (2014–2022)

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Computational Screening of Glyme-Based Room-Temperature Aluminum Plating Solutions

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Improving optoelectronic and charge transport properties of aza-BODIPY-based non-fullerene acceptors by end-capped modification for high-performance organic solar cells

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AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)

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Electron transfer from a new chalcone dye to TiO2 nanoparticles: Synthesis, photophysics, and excited-state dynamics

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In Silico modeling and exploration of new acceptor molecules with enhanced power conversion efficiency for high-performance organic solar cell applications

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Machine Learning Assisted Designing of Dyes and Oscillator Strength Prediction: Chemical Space Generation and Visualization

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