Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …

With its extremely strong capability of data analysis, machine learning has shown versatile
potential in the revolution of the materials research paradigm. Here, taking dielectric …

Solutions to many of the world's problems depend upon materials research and
development. However, advanced materials can take decades to discover and decades …

Zeolites are versatile catalysts and molecular sieves with large topological diversity, but
managing phase competition in zeolite synthesis is an empirical, labor-intensive task. In this …

The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …

In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

Supercapacitors are appealing energy storage devices for their promising features like high
power density, outstanding cycling stability, and a quick charge–discharge cycle. The …

Batteries are central to modern society. They are no longer just a convenience but a critical
enabler of the transition to a resilient, low-carbon economy. Battery development capabilities …

Abstract We present the Novel-Materials-Discovery (NOMAD) Artificial-Intelligence (AI)
Toolkit, a web-browser-based infrastructure for the interactive AI-based analysis of materials …

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s.
Online analysis methods are needed to enable the collection of only interesting subsets of …