Results 51 to 60 of about 3,170,537 (296)

Machine learning small molecule properties in drug discovery

Artificial Intelligence Chemistry, 2023
Machine learning (ML) is a promising approach for predicting small molecule properties in drug discovery. Here, we provide a comprehensive overview of various ML methods introduced for this purpose in recent years.
Nikolai Schapin, Maciej Majewski, Alejandro Varela-Rial, Carlos Arroniz, Gianni De Fabritiis   +4 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

The Enthalpy of Formation of Acetylenes and Aromatic Nitro Compounds for a Group Contribution Method with “Chemical Accuracy”

AppliedChem
In this paper we provide the Group Contribution parameters for acetylenes and aromatic nitro compounds fitting with a recently developed Group Contribution method with chemical accuracy (1 kcal/mol) for the heat of formation of organics. These additional
Robert J. Meier, Paul R. Rablen
doaj   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Predictive performance and QSPR analysis of SARS-CoV-2 and tuberculosis drugs using distance-based topological descriptors

Scientific Reports
Topological descriptors from molecular graphs are crucial in quantitative structure–property relationship (QSPR) analysis, linking structure to physicochemical and biological properties. This work studies the detour distance-based index, Detour Eccentric
Supriya, Radha Rajamani Iyer
doaj   +1 more source

Surfactant Temperature-Dependent Critical Micelle Concentration Prediction with Uncertainty-Aware Graph Neural Network

Chemistry
The critical micelle concentration (CMC) is a fundamental physicochemical property of surfactants with significant implications across multiple industries.
Musa Sh. Adygamov, Emil R. Saifullin, Timur R. Gimadiev, Nikita Yu. Serov   +3 more
doaj   +1 more source

Morphology, Transport, and Dynamics of Protein Adsorption in Open‐Cell Metal Foam

Advanced Engineering Materials, EarlyView.
Stainless steel (SS) open‐cell foams are shown to adsorb more protein per unit area than previously reported 316L SS and chromium oxide surfaces under static and flow conditions. An integrated approach combining 3D pore imaging, flow simulation, and protein adsorption experiments characterizes the foam’s performance.
Chinmaya Prerana Inguva, Joseph Lavoie, Afsaneh Rabiei   +2 more
wiley   +1 more source

DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles

Journal of Cheminformatics
Evaluation of chemical drug-likeness is essential for the discovery of high-quality drug candidates while avoiding unwarranted biological and clinical trial costs.
Yaxin Gu, Yimeng Wang, Keyun Zhu, Weihua Li, Guixia Liu, Yun Tang   +5 more
doaj   +1 more source

High‐Entropy Alloy Interlayers Toward Advanced Joining for High‐Performance Structural Applications: Current Progress and Emerging Challenges

Advanced Engineering Materials, EarlyView.
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan, Jiafen Song, Jinglong Li, Jiangtao Xiong, Tao Yang   +4 more
wiley   +1 more source

QGeoSEP: A Novel Multi‐Task Learning Framework Integrating Quantum, Geometric, and Semantic Features for Collaborative Prediction of Multiple Properties With Potential Application to Energetic Materials

Materials Genome Engineering Advances
Accurate physicochemical property prediction is critical for the rational design of energetic materials (EMs), yet limited high‐quality experimental data and property‐wise data imbalance restrict the application of conventional single‐task and multi‐task
Mingchi Gao, Zhijiang Yang, Tengxin Huang, Yingjun Zhang, Liangliang Wang, Junjie Ding, Mingtian Li   +6 more
doaj   +1 more source