Machine learning and molecular dynamics simulation-assisted evolutionary design and discovery pipeline to screen efficient small molecule acceptors for PTB7-Th …
Organic solar cells are the most promising candidates for future commercialization. This goal
can be quickly achieved by designing new materials and predicting their performance …
can be quickly achieved by designing new materials and predicting their performance …
Developing Efficient Small Molecule Acceptors with sp2‐Hybridized Nitrogen at Different Positions by Density Functional Theory Calculations, Molecular Dynamics …
Chemical structure of small molecule acceptors determines their performance in organic
solar cells. Multiscale simulations are necessary to avoid trial‐and‐error based design …
solar cells. Multiscale simulations are necessary to avoid trial‐and‐error based design …
Exploration of efficient electron acceptors for organic solar cells: rational design of indacenodithiophene based non-fullerene compounds
The global need for renewable sources of energy has compelled researchers to explore
new sources and improve the efficiency of the existing technologies. Solar energy is …
new sources and improve the efficiency of the existing technologies. Solar energy is …
First principles study of electronic and nonlinear optical properties of A–D–π–A and D–A–D–π–A configured compounds containing novel quinoline–carbazole …
Materials with nonlinear optical (NLO) properties have significant applications in different
fields, including nuclear science, biophysics, medicine, chemical dynamics, solid physics …
fields, including nuclear science, biophysics, medicine, chemical dynamics, solid physics …
Machine‐Learning Analysis of Small‐Molecule Donors for Fullerene Based Organic Solar Cells
MRSA Janjua, A Irfan, M Hussien, M Ali… - Energy …, 2022 - Wiley Online Library
In recent years, development in organic solar cells speeds up and performance continuously
increases. From the last few years, machine learning gains fame among scientists who are …
increases. From the last few years, machine learning gains fame among scientists who are …
Learning from Fullerenes and Predicting for Y6: Machine Learning and High‐Throughput Screening of Small Molecule Donors for Organic Solar Cells
In recent years, research on the development of organic solar cells has increased
significantly. For the last few years, machine learning (ML) has been gaining the attention of …
significantly. For the last few years, machine learning (ML) has been gaining the attention of …
Synthesis, spectroscopic (13C/1H-NMR, FT-IR) investigations, quantum chemical modelling (FMO, MEP, NBO analysis), and antioxidant activity of the bis …
In the current study, we first synthesized the molecule 1, 2-Bis (2-benzimidazolyl)-1, 2-
ethanediol, called C1. The structural properties of C1 were explored by spectroscopic …
ethanediol, called C1. The structural properties of C1 were explored by spectroscopic …
Predicting benzodithiophene based donor materials with enhanced 19.09% PCE, open-circuit voltage and optoelectronic attributes for solar cell applications …
Abstract Seven benzo [1, 2-b: 4, 5-b′] dithiophene (BDT) based novel donor (D1-D7)
molecules with A-π-D-π-A configuration are investigated by DFT and TD-DFT methods and …
molecules with A-π-D-π-A configuration are investigated by DFT and TD-DFT methods and …
Structural insights, spectral, flourescence, Z-scan, CH… O/NH… O hydrogen bonding and AIM, RDG, ELF, LOL, FUKUI analysis, NLO activity of N-2 (Methoxy phenyl) …
MJ Pramila, DA Dhas, IH Joe, S Balachandran… - Journal of Molecular …, 2023 - Elsevier
Quantum chemical calculations of geometries and vibrational wavenumbers of N-2 (methoxy
phenyl) acetamide (N2MPA) in the ground state were carried out by using density functional …
phenyl) acetamide (N2MPA) in the ground state were carried out by using density functional …
Machine learning-assisted prediction of the biological activity of aromatase inhibitors and data mining to explore similar compounds
Designing molecules for drugs has been a hot topic for many decades. However, it is hard
and expensive to find a new molecule. Thus, the cost of the final drug is also increased …
and expensive to find a new molecule. Thus, the cost of the final drug is also increased …