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Related papers: Polymer Brushes and Grafted Polymers: AI/ML-Driven…

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Automated interlinear gloss prediction with neural networks is a promising approach to accelerate language documentation efforts. However, while state-of-the-art models like GlossLM achieve high scores on glossing benchmarks, user studies…

Computation and Language · Computer Science 2026-01-26 Michael Ginn , Lindia Tjuatja , Enora Rice , Ali Marashian , Maria Valentini , Jasmine Xu , Graham Neubig , Alexis Palmer

It has recently been proposed that the miscibility of nanoparticles with a polymer matrix can be controlled by grafting polymer chains to the nanoparticle surface. As a first step to study this situation, we have used molecular dynamics…

Soft Condensed Matter · Physics 2010-08-06 Joshua Kalb , Douglas Dukes , Sanat K. Kumar , Robert S. Hoy , Gary S. Grest

Hardly any other area of research has recently attracted as much attention as machine learning (ML) through the rapid advances in artificial intelligence (AI). This publication provides a short introduction to practical concepts and methods…

General Economics · Economics 2020-12-17 Ali R. Baghirzade

Neutral or charged polymers that are densely end-grafted to surfaces form brush-like structures and are highly stretched under good-solvent conditions. We discuss and compare relevant results from scaling models, self-consistent-field…

Soft Condensed Matter · Physics 2007-05-23 Ali Naji , Christian Seidel , Roland R. Netz

Automated machine learning (AutoML) and deep learning (DL) are two cutting-edge paradigms used to solve a myriad of inductive learning tasks. In spite of their successes, little guidance exists for when to choose one approach over the other…

Machine Learning · Computer Science 2021-10-25 Joseph D. Romano , Trang T. Le , Weixuan Fu , Jason H. Moore

The generation of molecules with Artificial Intelligence (AI) is poised to revolutionize materials discovery. Potential applications range from development of potent drugs to efficient carbon capture and separation technologies. However,…

The pursuit of advanced polymers for energy technologies, spanning photovoltaics, solid-state batteries, and hydrogen storage, is hindered by fragmented data ecosystems that fail to capture the hierarchical complexity of these materials.…

Soft Condensed Matter · Physics 2025-05-21 Ying Zhao , Guanhua Chen , Jie Liu

Particulate composites underpin many solid-state chemical and electrochemical systems, where microstructural features such as multiphase boundaries and inter-particle connections strongly influence system performance. Advances in X-ray…

Materials Science · Physics 2026-05-19 Zebin Li , Shimao Deng , Yijin Liu , Jia-Mian Hu

A coarse grained model for flexible polymers end-grafted to repulsive spherical nanoparticles is studied for various chain lengths and grafting densities under good solvent conditions, by Molecular Dynamics methods and density functional…

Soft Condensed Matter · Physics 2015-05-18 Federica Lo Verso , Sergei A. Egorov , Andrey Milchev , Kurt Binder

Artificial intelligence is transforming molecular and materials science, but its growing computational and data demands raise critical sustainability challenges. In this Perspective, we examine resource considerations across the AI-driven…

High-throughput computational screening of polymers offers a powerful way to address the imbalance between the vast number of polymers synthesised for diverse applications and the relatively small subset that can be studied using atomistic…

Materials Science · Physics 2026-03-12 Lois Smith , Samuel Ericson , Vittoria Fantauzzo , Chin Yong , Paola Carbone , Alessandro Troisi

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the…

Artificial intelligence (AI) raises expectations of substantial increases in rates of technological and scientific progress, but such anticipations are often not connected to detailed ground-level studies of AI use in innovation processes.…

Computers and Society · Computer Science 2025-11-21 John P. Nelson , Olajide Olugbade , Philip Shapira , Justin B. Biddle

Machine learning (ML) models for predicting gas permeability through polymers have traditionally relied on experimental data. While these models exhibit robustness within familiar chemical domains, reliability wanes when applied to new…

Materials Science · Physics 2024-06-24 Brandon K. Phan , Kuan-Hsuan Shen , Rishi Gurnani , Huan Tran , Ryan Lively , Rampi Ramprasad

Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing these datasets requires both sufficient compute power and…

This paper addresses the gap between the capabilities and utilisation of robotics and automation in laboratory settings and builds upon the concept of Self Driving Labs (SDL). %to significantly impact laboratory operations. We introduce an…

Systems and Control · Electrical Eng. & Systems 2024-02-20 Shayan Azizi , Ehsan Asadi , Shaun Howard , Benjamin W. Muir , Riley O'Shea , Alireza Bab-Hadiashar

Artificial Intelligence (AI), especially AI agents, is increasingly being applied to chemistry, healthcare, and manufacturing to enhance productivity. In this review, we discuss the progress of AI and agentic AI in areas related to, and…

The combination of high-throughput experimentation techniques and machine learning (ML) has recently ushered in a new era of accelerated material discovery, enabling the identification of materials with cutting-edge properties. However, the…

Self-driving labs are transforming drug discovery by enabling automated, AI-guided experimentation, but they face challenges in orchestrating complex workflows, integrating diverse instruments and AI models, and managing data efficiently.…

Software Engineering · Computer Science 2025-04-02 Yao Fehlis , Paul Mandel , Charles Crain , Betty Liu , David Fuller

In this study, a versatile methodology for initiating polymerization from monomers in highly cross-linked materials is investigated. As polymerization progresses, force-field parameters undergo continuous modification due to the formation…

Computational Engineering, Finance, and Science · Computer Science 2024-01-15 Wonseok Lee , Sanggyu Chong , Jihan Kim