Jung-Ryul Lee, Hongki Yoo, Chia Chen Ciang, Young-Jin Kim, Daehee Kim, Teow Wee Teo, Zeinab Mahdavipour, Azizi Abdullah, Bee Ee Khoo, Mohd Zaid Abdullah, Dimitris K Iakovidis, Panagiotis Vartholomeos, Andrew Yacoot, Tao Cai, Mirae Kim, Kyung Chun Kim, Jiamin Ye, Xiao Liang, Lidan Cao, Xingwei Wang, Jianqing Huang, Weiwei Cai, Yingchun Wu, Marco J da Silva, Chao Tan, Sayantan Bhattacharya, Pavlos Vlachos, Christian Cierpka and Massimiliano Rossi

Surface Topography: Metrology and Properties

Correlational study of multiscale analysis and the metrological characteristics of areal surface topography measuring instruments

M Eifler, J Hering-Stratemeier, G von Freymann, C A Brown and J Seewig

Integrated form-position measurement of large-aperture transparent elements based on stereoscopic phase measuring deflectometry

Ting Chen, Peide Yang, Wei Lang, Yunuo Chen, Wei Wang and Xiangchao Zhang

Journal of Physics D: Applied Physics

A ferromagnetic skyrmion-based spin-torque nano-oscillator with modified edge magnetization

Danyu Luo, Guoliang Yu, Yan Li, Yang Qiu, Jiawei Wang, Mingmin Zhu and Haomiao Zhou

Explainable artificial intelligence-based evidential inferencing on process faults in plasma etching

Jeong Eun Choi, Surin An, Younji Lee, Yongil Lee, Dohyun Kim and Sang Jeen Hong

Machine Learning/AI

Journal of Physics: Condensed Matter

Machine learning assisted crystallographic reconstruction from atom probe tomographic images

Jie-Ming Pu, Shuai Chen and Tong-Yi Zhang

Thermal transport in C₆N₇ monolayer: a machine learning based molecular dynamics study

Jing Wan, Guanting Li, Zeyu Guo and Huasong Qin

Discovery of novel materials through machine learning

Akinwumi Akinpelu, Mangladeep Bhullar and Yansun Yao

Integrating machine learning and the finite element method for assessing stiffness degradation in photovoltaic modules

Weiqing Li

Machine learning assisted understanding of the layer-thickness dependent thermal conductivity in fluorinated graphene

Jun-Nan Liang, Hua Tong, Yu-Jia Zeng and Wu-Xing Zhou

Study of the Berezinskii–Kosterlitz–Thouless transition: an unsupervised machine learning approach

Sumit Haldar, Sk Saniur Rahaman and Manoranjan Kumar

Comparison of lattice thermal conductivity using ab-initio DFT, machine learning interatomic potentials, and temperature dependent effective potential: a case study of hexagonal BN and BP bilayer

Harpriya Minhas, Arnab Majumdar and Biswarup Pathak

Deciphering diffuse scattering with machine learning and the equivariant foundation model: the case of molten FeO

Ganesh Sivaraman and Chris J Benmore

Predicting photovoltaic parameters of perovskite solar cells using machine learning

Zhan Hui, Min Wang, Jialu Chen, Xiang Yin, Yunliang Yue and Jing Lu

Bandgap prediction of non-metallic crystals through machine learning approach

Sadhana Barman, Harkishan Dua and Utpal Sarkar

Physics mechanisms underlying the optimization of coherent heat transfer across width-modulated nanowaveguides with calculations and machine learning

Antonios-Dimitrios Stefanou and Xanthippi Zianni

Predicting mechanical properties of CO₂ hydrates: machine learning insights from molecular dynamics simulations

Yu Zhang, Zixuan Song, Yanwen Lin, Qiao Shi, Yongchao Hao, Yuequn Fu, Jianyang Wu and Zhisen Zhang

Thermal conductivity of van der Waals heterostructure of 2D GeS and SnS based on machine learning interatomic potential

Wentao Li and Chenxiu Yang

Machine learning molecular dynamics simulation of CO-driven formation of Cu clusters on the Cu(111) surface

Harry H Halim, Ryo Ueda and Yoshitada Morikawa

Automated characterization of spatial and dynamical heterogeneity in supercooled liquids via implementation of machine learning

Viet Nguyen and Xueyu Song

Expectation–maximization machine learning model for micromechanical evaluation of thermally-cycled solder joints in a semiconductor

Tzu-Chia Chen

Machine learning approach to study quantum phase transitions of a frustrated one dimensional spin-1/2 system

Sk Saniur Rahaman, Sumit Haldar and Manoranjan Kumar

Journal of Physics D: Applied Physics

Dynamic mode decomposition for data-driven analysis and reduced-order modeling of E × B plasmas: I. Extraction of spatiotemporally coherent patterns

F Faraji, M Reza, A Knoll and J N Kutz

Physics-separating artificial neural networks for predicting initial stages of Al sputtering and thin film deposition in Ar plasma discharges

Tobias Gergs, Thomas Mussenbrock and Jan Trieschmann

Data-driven prediction of the output composition of an atmospheric pressure plasma jet

Li Lin, Sophia Gershman, Yevgeny Raitses and Michael Keidar

Machine learning-based prediction of operation conditions from plasma plume images of atmospheric-pressure plasma reactors

Cheolwoo Bong, Byeong Soo Kim, Mohammed H A Ali, Dongju Kim and Moon Soo Bak

A regression model for plasma reaction kinetics

Martin Hanicinec, Sebastian Mohr and Jonathan Tennyson

Partial EEDF analysis and electron diagnostics of atmospheric-pressure argon and argon–helium DBD plasma

Thijs van der Gaag, Atsushi Nezu and Hiroshi Akatsuka

Physica Scripta

Investigation of the thermal analysis of a wavy fin with radiation impact: an application of extreme learning machine

S Bhanu Prakash, K Chandan, K Karthik, Sriram Devanathan, R S Varun Kumar, K V Nagaraja and B C Prasannakumara

Machine learning-driven process of alumina ceramics laser machining

Razyeh Behbahani, Hamidreza Yazdani Sarvestani, Erfan Fatehi, Elham Kiyani, Behnam Ashrafi, Mikko Karttunen8 and Meysam Rahmat

Early warning signals for critical transitions in complex systems

Sandip V George, Sneha Kachhara and G Ambika

A machine learning approach to predict the efficiency of corrosion inhibition by natural product-based organic inhibitors

Muhamad Akrom, Supriadi Rustad and Hermawan Kresno Dipojono

Nanotechnology

Exploring nonlinear correlations among transition metal nanocluster properties using deep learning: a comparative analysis with LOO-CV method and cosine similarity

Zahra Nasiri Mahd, Alireza Kokabi, Maryam Fallahzadeh and Zohreh Naghibi

Roadmap on magnetic nanoparticles in nanomedicine

Kai Wu, Jian-Ping Wang, Niranjan A Natekar, Stefano Ciannella, Cristina González-Fernández, Jenifer Gomez-Pastora, Yuping Bao, Jinming Liu, Shuang Liang, Xian Wu, Linh Nguyen T Tran, Karla Mercedes Paz González, Hyeon Choe, Jacob Strayer, Poornima Ramesh Iyer, Jeffrey Chalmers, Vinit Kumar Chugh, Bahareh Rezaei, Shahriar Mostufa, Zhi Wei Tay, Chinmoy Saayujya, Quincy Huynh, Jacob Bryan, Renesmee Kuo, Elaine Yu, Prashant Chandrasekharan, Benjamin Fellows, Steven Conolly, Ravi L Hadimani, Ahmed A El-Gendy, Renata Saha, Thomas J Broomhall, Abigail L Wright, Michael Rotherham, Alicia J El Haj, Zhiyi Wang, Jiarong Liang, Ana Abad-Díaz-de-Cerio, Lucía Gandarias, Alicia G Gubieda, Ana García-Prieto and Mª Luisa Fdez-Gubieda

Thermal, mechanical, and electrical properties of Si-stacked nanosheet transistors using machine learning interatomic potentials

Mohamed Saleh, Hamdy Abdelhamid and Amr M Bayoumi

Improving the coverage area and flake size of ReS₂ through machine learning in APCVD

Mario Flores Salazar, Christian Mateo Frausto-Avila, Javier A de Jesús Bautista, Gowtham Polumati, Barbara A Muñiz Martínez, K Chandra Sekhar Reddy, Miguel Ángel Hernández-Vázquez, Elodie Strupiechonski, Parikshit Sahatiya, Mario Alan Quiroz-Juárez and Andres De Luna Bugallo

Carbyne as a promising material for E-nose applications with machine learning

Alexey Kucherik, Ashok Kumar, Abramov Andrey, Samyshkin Vlad, Osipov Anton, Bordanov Ilya, Sergey Shchanikov and Mahesh Kumar

Comparative performance analysis of unmixed and mixed metal oxide sensors for dual-sensing leveraging machine learning

Binowesley Ramakrishnan, Kirubaveni Savarimuthu and M. Emimal

Machine learning accelerated search for the impact limit of the graphene/aluminum alloy whipple structure

Qinghong Ge, Weiping Zhu and Jin-Wu Jiang

Prediction of electrical properties of GAAFET based on integrated learning model

Xuyan Zhang, Siyu Chen, Shulong Wang, Jiarui Li, Dongliang Chen, Yuhang Li, Lan Ma, Shupeng Chen, Hongxia Liu, YuanJie Lv and JunShuai Xue

Algorithm prediction of single particle irradiation effect based on novel TFETs

Chen Chong, Hongxia Liu, Shulong Wang and Zexi Wang

Nano Express

Machine learning-based model for the intelligent estimation of critical heat flux in nanofluids