Results 41 to 50 of about 3,379 (242)
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
QSPR analysis of some agonists and antagonists of α-adrenergic receptors [PDF]
Medicinal Chemistry Research, 2014 Thirty-three compounds belonging to the sympatholytics and sympathomimetics were analyzed during the study. The biological activity data for the parameters of binding affinity to the α1- and α2-adrenergic receptors together with parameters of the logarithm of the partition coefficient n-octanol/water (log P) were performed using a semi-empirical ...
Kawczak, Piotr +2 more
openaire +2 more sources
Ampliação do índice semi-empírico topológico para Alquilbenzenos e sua aplicação em estudos de Qspr / qsrr [PDF]
, 2004 TCC (graduação) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas, Curso de Química.Neste estudo o Índice Semi-Empírico Topológico (IET) foi desenvolvido e otimizado com o objetivo de predizer a retenção cromatográfica de
PORTO, Ledilege Cucco
core
QSPR analysis of threshold of odor for the large number of heterogenic chemicals
Molecular Diversity, 2017 Quantitative structure-property relationships for odor thresholds based on representation of the molecular structure by the simplified molecular input-line entry system were established using the CORAL software. The total set of compounds with numerical data on the so-called arithmetic odor thresholds ([Formula: see text]) was distributed into the ...
Andrey A. Toropov +4 more
openalex +4 more sources
Advanced Intelligent Discovery, EarlyView.This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo +3 more
wiley +1 more source
Connectivity indices and QSPR analysis of benzenoid hydrocarbons
Open Journal of Discrete Applied Mathematics, 2023 In mathematical chemistry, a large number of topological indices are used to predict the physicochemical properties of compounds, especially in the study of quantitative structure-proerty relationship (QSPR). However, many topological indices have almost the same predictive ability.
openaire +1 more source
Índice semi-empírico topológico: desenvolvimento e aplicação de um novo descritor molecular em estudos de correlação quantitativa estrutura-propriedade (QSPR) [PDF]
, 2003 Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas. Programa de Pós-Graduação em Química.Neste estudo um novo descritor molecular - Índice Semi-Empírico Topológico (IET) - foi desenvolvido, a fim de ...
Junkes, Berenice da Silva
core
QSPR Analysis of Certain Degree Based Topological Indices
, 2017 In QSAR/QSPR study, topological indices are utilized to guess the bioactivity of chemical compounds. In this paper, we study the QSPR analysis of ten degree-based topological indices. Our study reveals some important results which help us to characterize
Sunilkumar Hosamani +9 more
core +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
Carbon Energy, EarlyView.Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su +4 more
wiley +1 more source