Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation

Y **e, K Sattari, C Zhang, J Lin - Progress in Materials Science, 2023 - Elsevier
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …

In Situ and Emerging Transmission Electron Microscopy for Catalysis Research

HY Chao, K Venkatraman, S Moniri, Y Jiang… - Chemical …, 2023 - ACS Publications
Catalysts are the primary facilitator in many dynamic processes. Therefore, a thorough
understanding of these processes has vast implications for a myriad of energy systems. The …

Autonomous experimentation systems for materials development: A community perspective

E Stach, B DeCost, AG Kusne, J Hattrick-Simpers… - Matter, 2021 - cell.com
Solutions to many of the world's problems depend upon materials research and
development. However, advanced materials can take decades to discover and decades …

AI-driven framework for recognition of guava plant diseases through machine learning from DSLR camera sensor based high resolution imagery

A Almadhor, HT Rauf, MIU Lali, R Damaševičius… - Sensors, 2021 - mdpi.com
Plant diseases can cause a considerable reduction in the quality and number of agricultural
products. Guava, well known to be the tropics' apple, is one significant fruit cultivated in …

Time-resolved transmission electron microscopy for nanoscale chemical dynamics

FM Alcorn, PK Jain, RM van der Veen - Nature Reviews Chemistry, 2023 - nature.com
The ability of transmission electron microscopy (TEM) to image a structure ranging from
millimetres to Ångströms has made it an indispensable component of the toolkit of modern …

Data augmentation and deep learning methods in sound classification: A systematic review

OO Abayomi-Alli, R Damaševičius, A Qazi… - Electronics, 2022 - mdpi.com
The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …

YOLO-Fish: A robust fish detection model to detect fish in realistic underwater environment

A Al Muksit, F Hasan, MFHB Emon, MR Haque… - Ecological …, 2022 - Elsevier
Over the last few years, several research works have been performed to monitor fish in the
underwater environment aimed for marine research, understanding ocean geography, and …

Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook

M Botifoll, I Pinto-Huguet, J Arbiol - Nanoscale Horizons, 2022 - pubs.rsc.org
In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …

Automated image analysis for single-atom detection in catalytic materials by transmission electron microscopy

S Mitchell, F Parés, D Faust Akl… - Journal of the …, 2022 - ACS Publications
Single-atom catalytic sites may have existed in all supported transition metal catalysts since
their first application. Yet, interest in the design of single-atom heterogeneous catalysts …

Deep-Learning Aided Atomic-Scale Phase Segmentation toward Diagnosing Complex Oxide Cathodes for Lithium-Ion Batteries

D Zhu, C Wang, P Zou, R Zhang, S Wang, B Song… - Nano Letters, 2023 - ACS Publications
Phase transformation─ a universal phenomenon in materials─ plays a key role in
determining their properties. Resolving complex phase domains in materials is critical to …