☆ 4.4 Article

In silico active learning for small molecule properties

MOLECULAR SYSTEMS DESIGN & ENGINEERING (2022)

Related references

Note: Only part of the references are listed.

Article Chemistry, Multidisciplinary

Launching a materials informatics initiative for industrial applications in materials science, chemistry, and engineering

Jeffrey M. Ting et al.

Summary: The advent of materials informatics has provided opportunities for transforming traditional scientific research workflows. This article highlights a MI initiative at 3M Corporate Research Laboratories, showcasing the strategic application of MI tools and data-driven methodologies for industrial materials research and product development.

PURE AND APPLIED CHEMISTRY (2022)

Add to Collection

Review Polymer Science

Data-Driven Methods for Accelerating Polymer Design

Tarak K. Patra

Summary: Optimal design of polymers is challenging, but recent advances in computations and machine learning offer potential solutions. This review discusses the central problem of polymer design and explores the ideas and principles behind data-driven methods. The authors present case studies and highlight the transformative impact that combining machine learning, computational characterization, and large datasets can have on polymer research and development.

ACS POLYMERS AU (2022)

Add to Collection

Article Chemistry, Medicinal

Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature

Lei Tao et al.

Summary: The utilization of machine learning techniques in polymer informatics for evaluating properties such as glass transition temperature (T-g) has gained significant attention. A benchmark study was conducted to compare different ML models and explore key factors affecting the prediction of T-g, including structure representations, feature representations, and ML algorithms. This study not only provides guidance for Tg prediction, but also serves as a valuable reference for other polymer informatics tasks.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)

Add to Collection

Review Chemistry, Multidisciplinary

Data-Driven Strategies for Accelerated Materials Design

Robert Pollice et al.

Summary: The ongoing revolution in the natural sciences, driven by machine learning and artificial intelligence, has sparked significant interest in the material science community. To address the imminent climate catastrophe and transform to clean energy, the development of new materials is crucial. New materials, such as organic photovoltaics, show great potential in replacing existing materials and opening up new applications.

ACCOUNTS OF CHEMICAL RESEARCH (2021)

Add to Collection

Review Pharmacology & Pharmacy

Automation and data-driven design of polymer therapeutics

Rahul Upadhya et al.

Summary: Researchers utilize tunable structural parameters of polymers for drug delivery and biomaterial applications, employing intelligent and big data approaches to maximize experimental efficiency. Machine learning and artificial intelligence technologies may play a crucial role in this field.

ADVANCED DRUG DELIVERY REVIEWS (2021)

Add to Collection

Review Materials Science, Multidisciplinary

Polymer informatics: Current status and critical next steps

Lihua Chen et al.

Summary: Artificial intelligence is making significant impact in the field of polymer informatics, with surrogate models being trained on polymer data for instant property prediction. Challenges include lack of curated data availability and the need for machine-readable representations capturing the complexity of polymer structures.

MATERIALS SCIENCE & ENGINEERING R-REPORTS (2021)

Add to Collection

Article Polymer Science

Deep Learning of Binary Solution Phase Behavior of Polystyrene

Jeffrey G. Ethier et al.

Summary: This study demonstrates the effectiveness of machine learning in predicting the cloud point temperatures of polymer solutions, providing a tool for predicting liquid-liquid equilibrium of polymers.

ACS MACRO LETTERS (2021)

Add to Collection

Article Chemistry, Multidisciplinary

Retrosynthetic accessibility score (RAscore) - rapid machine learned synthesizability classification from AI driven retrosynthetic planning

Amol Thakkar et al.

Summary: A machine learning method has been developed to classify whether a synthetic route can be identified for a compound by the CASP tool AiZynthFinder, which is 4500 times faster than the underlying CASP tool. This method can be used for pre-screening virtual molecules and generating higher quality databases for virtual screening of biological activity.

CHEMICAL SCIENCE (2021)

Add to Collection

Article Biochemistry & Molecular Biology

PubChem in 2021: new data content and improved web interfaces

Sunghwan Kim et al.

Summary: PubChem, a popular chemical information resource, has made substantial improvements in the past two years by adding data from over 100 new sources, updating its homepage and record pages, introducing new services like the Periodic Table and Pathway pages, and creating a special data collection related to COVID-19 and SARS-CoV-2 in response to the pandemic.

NUCLEIC ACIDS RESEARCH (2021)

Add to Collection

Review Nanoscience & Nanotechnology

Emerging materials intelligence ecosystems propelled by machine learning

Rohit Batra et al.

Summary: The age of cognitive computing and artificial intelligence is emerging, with AI ecosystems flourishing in materials science and engineering. Machine learning algorithms are utilized to create surrogate models of materials properties, transforming the computational and physical laboratory infrastructural landscapes. Integration of various ML landscape parts may lead to materials-savvy digital assistants and human-machine partnerships for efficient materials screening and discovery.

NATURE REVIEWS MATERIALS (2021)

Add to Collection

Article Chemistry, Physical

Machine learning enabled autonomous microstructural characterization in 3D samples

Henry Chan et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Add to Collection

Article Multidisciplinary Sciences

Self-driving laboratory for accelerated discovery of thin-film materials

B. P. MacLeod et al.

SCIENCE ADVANCES (2020)

Add to Collection

Article Chemistry, Physical

Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys

Anh Tran et al.

JOURNAL OF CHEMICAL PHYSICS (2020)

Add to Collection

Review Chemistry, Multidisciplinary

QSAR without borders

Eugene N. Muratov et al.

CHEMICAL SOCIETY REVIEWS (2020)

Add to Collection

Article Materials Science, Multidisciplinary

Challenges and opportunities of polymer design with machine learning and high throughput experimentation

Jatin N. Kumar et al.

MRS COMMUNICATIONS (2019)

Add to Collection

Article Materials Science, Multidisciplinary

Active-learning and materials design: the example of high glass transition temperature polymers

Chiho Kim et al.

MRS COMMUNICATIONS (2019)

Add to Collection

Article Materials Science, Multidisciplinary

A data ecosystem to support machine learning in materials science

Ben Blaiszik et al.

MRS COMMUNICATIONS (2019)

Add to Collection

Article Materials Science, Multidisciplinary

Accelerating high-throughput searches for new alloys with active learning of interatomic potentials

Konstantin Gubaev et al.

COMPUTATIONAL MATERIALS SCIENCE (2019)

Add to Collection

Article Multidisciplinary Sciences

Organic synthesis in a modular robotic system driven by a chemical programming language

Sebastian Steiner et al.

SCIENCE (2019)

Add to Collection

Review Materials Science, Multidisciplinary

From DFT to machine learning: recent approaches to materials science-a review

Gabriel R. Schleder et al.

JOURNAL OF PHYSICS-MATERIALS (2019)

Add to Collection

Review Chemistry, Multidisciplinary

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules

Melanie Trobe et al.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2018)

Add to Collection

Review Materials Science, Multidisciplinary

The Materials Genome Initiative and artificial intelligence

James A. Warren

MRS BULLETIN (2018)

Add to Collection

Article Biochemistry & Molecular Biology

LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands

Leela S. Dodda et al.

NUCLEIC ACIDS RESEARCH (2017)

Add to Collection

Article Biochemical Research Methods

OpenMM 7: Rapid development of high performance algorithms for molecular dynamics

Peter Eastman et al.

PLOS COMPUTATIONAL BIOLOGY (2017)

Add to Collection

Article Materials Science, Multidisciplinary

Optimal experimental design for materials discovery

Roozbeh Dehghannasiri et al.

COMPUTATIONAL MATERIALS SCIENCE (2017)

Add to Collection

Article Materials Science, Multidisciplinary

The Materials Data Facility: Data Services to Advance Materials Science Research

B. Blaiszik et al.

JOM (2016)

Add to Collection

Review Engineering, Electrical & Electronic

Taking the Human Out of the Loop: A Review of Bayesian Optimization

Bobak Shahriari et al.

PROCEEDINGS OF THE IEEE (2016)

Add to Collection

Review Materials Science, Multidisciplinary

The Materials Genome Initiative, the interplay of experiment, theory and computation

Juan J. de Pablo et al.

CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE (2014)

Add to Collection

Article Chemistry, Physical

OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation

Peter Eastman et al.

JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2013)

Add to Collection

Article Biochemistry & Molecular Biology

Estimation of the size of drug-like chemical space based on GDB-17 data

P. G. Polishchuk et al.

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2013)

Add to Collection

Review Chemistry, Multidisciplinary

InChI - the worldwide chemical structure identifier standard

Stephen Heller et al.

JOURNAL OF CHEMINFORMATICS (2013)

Add to Collection

Article Chemistry, Multidisciplinary

CurlySMILES: a chemical language to customize and annotate encodings of molecular and nanodevice structures

Axel Drefahl

JOURNAL OF CHEMINFORMATICS (2011)

Add to Collection

Article Computer Science, Interdisciplinary Applications

OpenMM: A Hardware-Independent Framework for Molecular Simulations

Peter Eastman et al.

COMPUTING IN SCIENCE & ENGINEERING (2010)

Add to Collection

Article Chemistry, Multidisciplinary

PACKMOL: A Package for Building Initial Configurations for Molecular Dynamics Simulations

L. Martinez et al.

JOURNAL OF COMPUTATIONAL CHEMISTRY (2009)

Add to Collection

Article Chemistry, Multidisciplinary

Molecular modeling of organic and biomolecular systems using BOSS and MCPRO

WL Jorgensen et al.

JOURNAL OF COMPUTATIONAL CHEMISTRY (2005)

Add to Collection

Article Chemistry, Multidisciplinary

Active learning with support vector machines in the drug discovery process

MK Warmuth et al.

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2003)

Add to Collection

© Peeref 2019-2024. All rights reserved.