ReviewChemical reviews2024
Machine Learning Aided Design and Optimization of Thermal Metamaterials.
Review in Chemical reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
30 citing papers in PubMed.
- Design and Optimization of Composite Thermal Insulation Layers for Mine Ecological Restoration Under Simulated Solar Radiation: Integrating Response Surface Screening with Gaussian Process Bayesian Optimization.Materials (Basel, Switzerland) · 2026Article
- Biomimetic diffusion metamaterials enabled by physical-geometric duality.Nature communications · 2026Article
- Learning to reverse thermal diffusion.National science review · 2026Article
- A Review of Machine Learning Applications in Mechanical Metamaterial Design.Materials (Basel, Switzerland) · 2026Review
- Machine learning-assisted highly efficient thermal management in function-oriented thermochromic smart windows.Light, science & applications · 2026Article
- Review
- Dual-site single-atom catalysts achieve directional adsorption-oxidation control for enhanced photo-Fenton-like reactions.Nature communications · 2026Article
- Multi-Objective Spray Drying Process Optimization via BBD-ANN-AGWO Framework: Case of Andrographolide Amorphous Solid Dispersions.AAPS PharmSciTech · 2026Article
- AI-driven nanomedicine for cancer theranostics.Molecular cancer · 2026Review
- Beyond Conventional Cooling: Advanced Micro/Nanostructures for Managing Extreme Heat Flux.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Inverse design mechanical metamaterials with dual load-bearing and heat-transfer capabilities.PloS one · 2026Article
- A New Pulsed Neutron-Gamma Density Logging Method Based on Gamma-Ray Spectra and Machine Learning.ACS omega · 2025Article
- AI-Integrated Micro/Nanorobots for Biomedical Applications: Recent Advances in Design, Fabrication, and Functions.Biosensors · 2025Review
- Highly Efficient Discovery of 3D Mechanical Metamaterials via Monte Carlo Tree Search.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Tailoring Energy Absorption of Curved-Beam Lattices Through a Data-Driven Approach.Materials (Basel, Switzerland) · 2025Article
- Full polarization and high coherence control of thermal emissions via saddle-band dispersion engineering.Nature communications · 2025Article
- Topology in Thermal, Particle, and Plasma Diffusion Metamaterials.Chemical reviews · 2025Review
- Controlling transient and coupled diffusion with pseudoconformal mapping.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Bio-inspired acoustic metamaterials for traffic noise control: bridging the gap with machine learning.Communications engineering · 2025Review
- Interpretable Prediction and Analysis of PVA Hydrogel Mechanical Behavior Using Machine Learning.Gels (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) has advanced material research that were previously intractable, for example, the machine learning (ML) has been able to predict some unprecedented thermal properties. In this review, we first elucidate the methodologies underpinning discriminative and generative models, as well as the paradigm of optimization approaches. Then, we present a series of case studies showcasing the application of machine learning in thermal metamaterial design. Finally, we give a brief discussion on the challenges and opportunities in this fast developing field. In particular, this review provides: (1) Optimization of thermal metamaterials using optimization algorithms to achieve specific target properties. (2) Integration of discriminative models with optimization algorithms to enhance computational efficiency. (3) Generative models for the structural design and optimization of thermal metamaterials.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.