Recent progress and future prospects on all-organic polymer dielectrics for energy storage capacitors
QK Feng, SL Zhong, JY Pei, Y Zhao, DL Zhang… - Chemical …, 2021 - ACS Publications
With the development of advanced electronic devices and electric power systems, polymer-
based dielectric film capacitors with high energy storage capability have become particularly …
based dielectric film capacitors with high energy storage capability have become particularly …
Emerging materials intelligence ecosystems propelled by machine learning
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …
successes and promises, several AI ecosystems are blossoming, many of them within the …
Predicting materials properties with little data using shotgun transfer learning
There is a growing demand for the use of machine learning (ML) to derive fast-to-evaluate
surrogate models of materials properties. In recent years, a broad array of materials property …
surrogate models of materials properties. In recent years, a broad array of materials property …
Polymer informatics: Current status and critical next steps
Artificial intelligence (AI) based approaches are beginning to impact several domains of
human life, science and technology. Polymer informatics is one such domain where AI and …
human life, science and technology. Polymer informatics is one such domain where AI and …
Review of polymer‐based nanodielectric exploration and film scale‐up for advanced capacitors
DQ Tan - Advanced Functional Materials, 2020 - Wiley Online Library
The uprising demands for electrical power and electrification requires advanced dielectric
functionalities including high capacitance density, high energy density, high current …
functionalities including high capacitance density, high energy density, high current …
Matminer: An open source toolkit for materials data mining
As materials data sets grow in size and scope, the role of data mining and statistical learning
methods to analyze these materials data sets and build predictive models is becoming more …
methods to analyze these materials data sets and build predictive models is becoming more …
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
The use of machine learning in computational molecular design has great potential to
accelerate the discovery of innovative materials. However, its practical benefits still remain …
accelerate the discovery of innovative materials. However, its practical benefits still remain …
Machine-learning predictions of polymer properties with Polymer Genome
Polymer Genome is a web-based machine-learning capability to perform near-
instantaneous predictions of a variety of polymer properties. The prediction models are …
instantaneous predictions of a variety of polymer properties. The prediction models are …
Polymer genome: a data-powered polymer informatics platform for property predictions
The recent successes of the Materials Genome Initiative have opened up new opportunities
for data-centric informatics approaches in several subfields of materials research, including …
for data-centric informatics approaches in several subfields of materials research, including …
Hierarchical materials from high information content macromolecular building blocks: construction, dynamic interventions, and prediction
Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature.
Because hierarchy gives rise to unique properties and functions, many have sought …
Because hierarchy gives rise to unique properties and functions, many have sought …