Polymer Informatics– tag –
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Tohoku University Proposes New AI-Integrated Autonomous Framework for Polymer Materials Discovery
EurekAlert! (Advanced Institute for Materials Research (AIMR), Tohoku University) Japan Overview A research team at Tohoku University has proposed a novel framework integrating AI and autonomous laboratories to overcome key bottlenecks i... -
University of Washington Develops Self-Healing Polymer Library ‘DPAL’ with Machine Learning, Accelerating Materials Design
EurekAlert! USA Overview University of Washington researchers have developed a novel machine learning approach to accelerate polymer material design and discovery. They created the "Dynamic Polymer Annotated Library (DPAL)" with self-hea... -
Tohoku University Unveils AI-Powered ‘Self-Driving Lab’ for Accelerated Polymer Discovery
Tohoku University (WPI-AIMR) Japan Overview Researchers at Tohoku University's WPI-AIMR have developed an integrated, closed-loop AI system that dramatically accelerates the discovery of new polymer materials. By seamlessly linking polym... -
ACS Publications: PolyCLIP Framework Outperforms Existing Polymer Property Prediction Models by 13.32%, Establishes New Foundation for Multimodal Polymer Informatics
ACS Publications USA Overview ACS Publications announced PolyCLIP, a CLIP-based multimodal framework, achieved up to 13.32% better performance in polymer property prediction than existing unimodal and multimodal models. The study demonst... -
AI and Polymer Informatics Slash Material Development Time from Decades to Months
ChemCopilot USA Overview AI, machine learning, and polymer informatics frameworks are dramatically accelerating polymer R&D, potentially reducing the development cycle for novel commercial polymers from 10-15 years to mere months or ... -
Matmerize Launches AI-Driven PolymRize Platform to Accelerate Polymer Design for Gas Separation Membranes and More
Matmerize (Halo) USA Overview Matmerize has introduced 'PolymRize,' a cloud-based AI and machine learning polymer informatics platform. This platform instantly predicts and designs polymers with tailored gas permeability and selectivity,... -
Notre Dame University Develops AI Polymer Discovery Platform to Overcome Data Scarcity, Accelerating Novel Material Exploration
Notre Dame Research USA Overview Notre Dame University's AI & Materials Initiative developed a framework leveraging multiple information sources to overcome data scarcity in polymer informatics. They created ADEPT, an automated molec... -
Machine Learning Predicts Thermal Properties of PHB/PHBV-Based Materials with Improved Accuracy Using Integrated Polymer Database
MDPI Switzerland Overview This study reports a novel machine learning (ML) approach for predicting thermal properties (glass transition temperature, melting point, crystallization temperature) of PHB and PHBV-based materials. By building... -
arXiv: PolyGraphPy Unifies Atomistic Simulation and ML-Driven Polymer Design in a Python Framework
arXiv Unknown Overview A new paper on arXiv introduces "PolyGraphPy," a unified Python framework for atomistic simulation and machine learning (ML)-driven polymer design. This open-source framework seamlessly integrates atomistic simulat...
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