Review of machine learning‐driven design of polymer‐based dielectrics
MX Zhu, T Deng, L Dong, JM Chen… - IET …, 2022 - Wiley Online Library
Polymer‐based dielectrics are extensively applied in various electrical and electronic
devices such as capacitors, power transmission cables and microchips, in which a variety of …
devices such as capacitors, power transmission cables and microchips, in which a variety of …
Materiomically designed polymeric vehicles for nucleic acids: quo vadis?
R Kumar - ACS Applied Bio Materials, 2022 - ACS Publications
Despite rapid advances in molecular biology, particularly in site-specific genome editing
technologies, such as CRISPR/Cas9 and base editing, financial and logistical challenges …
technologies, such as CRISPR/Cas9 and base editing, financial and logistical challenges …
Polymer Structure Predictor (PSP): A Python toolkit for predicting atomic-level structural models for a range of polymer geometries
Three-dimensional atomic-level models of polymers are the starting points for physics-based
simulation studies. A capability to generate reasonable initial structural models is highly …
simulation studies. A capability to generate reasonable initial structural models is highly …
[HTML][HTML] Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors
The efficient and economical exploitation of polymers with high thermal conductivity (TC) is
essential to solve the issue of heat dissipation in organic devices. Currently, the …
essential to solve the issue of heat dissipation in organic devices. Currently, the …
LGB-Stack: Stacked Generalization with LightGBM for Highly Accurate Predictions of Polymer Bandgap
Recently, the Ramprasad group reported a quantitative structure–property relationship
(QSPR) model for predicting the E gap values of 4209 polymers, which yielded a test set R 2 …
(QSPR) model for predicting the E gap values of 4209 polymers, which yielded a test set R 2 …
Informatics-Driven Selection of Polymers for Fuel-Cell Applications
Modern fuel cell technologies use Nafion as the material of choice for the proton exchange
membrane (PEM) and as the binding material (ionomer) used to assemble the catalyst …
membrane (PEM) and as the binding material (ionomer) used to assemble the catalyst …
Design of polymers for energy storage capacitors using machine learning and evolutionary algorithms
To meet the demands of emerging electrification technologies, polymers that are capable of
withstanding high electric fields at high temperatures are needed. Given the staggeringly …
withstanding high electric fields at high temperatures are needed. Given the staggeringly …
Accelerated Scheme to Predict Ring-Opening Polymerization Enthalpy: Simulation-Experimental Data Fusion and Multitask Machine Learning
Ring-opening enthalpy (Δ H ROP) is a fundamental thermodynamic quantity controlling the
polymerization and depolymerization of an important class of recyclable polymers, namely …
polymerization and depolymerization of an important class of recyclable polymers, namely …
[HTML][HTML] PolyNC: a natural and chemical language model for the prediction of unified polymer properties
H Qiu, L Liu, X Qiu, X Dai, X Ji, ZY Sun - Chemical Science, 2024 - pubs.rsc.org
Language models exhibit a profound aptitude for addressing multimodal and multidomain
challenges, a competency that eludes the majority of off-the-shelf machine learning models …
challenges, a competency that eludes the majority of off-the-shelf machine learning models …
Transferring a molecular foundation model for polymer property predictions
Transformer-based large language models have remarkable potential to accelerate design
optimization for applications such as drug development and material discovery. Self …
optimization for applications such as drug development and material discovery. Self …