Research graph
References from Generative artificial intelligence for nanomaterial discovery and nanoengineering: From data-driven design to autonomous laboratories. Local targets link to admitted publications; unresolved targets remain external evidence.
Materials informatics: emergence to autonomous discovery in the age of AI
2026 · External reference
Artificial intelligence in accelerating materials discovery: opportunities and challenges
10.1002/slct.202507191 · 2026 · External reference
Convergence of computational materials science and AI for next-generation energy storage materials
10.1007/s11664-025-12511-4 · 2026 · External reference
Generative design for alloys: harnessing generative models for faster discovery
10.1002/adma.202520478 · 2026 · External reference
AI-driven design and applications of quantum dots
2026 · External reference
Self-Driving laboratories for Chemistry and Materials science
10.1021/acs.chemrev.4c00055 · 2024 · External reference
Accelerating catalyst materials discovery with large artificial intelligence models
2026 · External reference
Transparent reporting for agentic catalysis enabled by artificial intelligence: Community guidelines and a publication checklist
2026 · External reference
Development of AI-eChemist laboratory
10.20517/aiagent.2026.15 · 2026 · External reference
From descriptors to machine learning interatomic potentials: a review of AI-accelerated electrocatalyst design
10.20517/aiagent.2025.05 · 2025 · External reference
Digital materials ecosystem: from databases to AI agents for autonomous discovery
10.1039/d5sc09229a · 2026 · External reference
Roadmap for transforming heterogeneous catalysis with artificial intelligence
10.1038/s41929-026-01479-x · 2026 · External reference
Machine learning in materials science: data-driven discovery and functional applications
10.3390/encyclopedia6070150 · 2026 · External reference
Artificial intelligence, machine learning, and high-throughput material discovery tools
2026 · External reference
Explainable machine learning in materials science
10.1038/s41524-022-00884-7 · 2022 · External reference
Artificial intelligence-driven revolution in nanozyme design: from serendipity to rational engineering
10.1039/d5mh00719d · 2025 · External reference
The JARVIS Infrastructure is All You Need for Materials Design
2025 · External reference
Beyond chemical structures: lessons and guiding principles for the next generation of molecular databases
10.1039/d4sc04064c · 2024 · External reference
Machine-learning-assisted understanding of polymer nanocomposites composition–property relationship: a case study of nanomine database
10.1021/acs.macromol.2c02249 · 2023 · External reference
Metadata Stewardship in Nanosafety Research: Community-Driven organisation of metadata schemas to support FAIR Nanoscience data
10.3390/nano10102033 · 2020 · External reference
Metal-organic frameworks: role of artificial intelligence and machine learning algorithms for efficient discovery, design, synthesis and prediction of CO2 capture capacity - A state of art review
10.1016/j.seppur.2026.136737 · 2026 · External reference
A closed-loop machine-learning framework for rational design of manganese-based nano-adsorbents
10.1016/j.seppur.2026.138003 · 2026 · External reference
Toward self-driving laboratory 2.0 for chemistry and materials discovery
10.1039/d5mh01984b · 2026 · External reference
Advanced nanoporous and mesoporous materials: emerging innovations, multiscale design, and future perspectives
10.3390/ma19061141 · 2026 · External reference
Cognitive AI beyond prediction: toward reasoning and discovery
10.1039/d5mh02049b · 2026 · External reference
Multiscale modeling and simulation of composite materials: methods, AI integration, and challenges
2026 · External reference
Quantum-enhanced artificial intelligence
2026 · External reference
Artificial intelligence and machine learning approaches for composite materials: recent developments and applications
10.1002/pc.71029 · 2026 · External reference
Machine learning boosts the design and discovery of nanomaterials
10.1021/acssuschemeng.1c00483 · 2021 · External reference
Machine learning applications in nanomaterials: recent advances and future perspectives
2024 · External reference
Digital twins for materials
10.3389/fmats.2022.818535 · 2022 · External reference
The evolution of materials acceleration platforms
10.1007/s10853-021-06281-7 · 2021 · External reference
Materials Acceleration Platforms (MAPs): accelerating materials research
10.1002/adma.202407791 · 2024 · External reference
Nanoparticle synthesis assisted by machine learning
10.1038/s41578-021-00337-5 · 2021 · External reference
Two-step machine learning enables optimized nanoparticle synthesis
10.1038/s41524-021-00520-w · 2021 · External reference
On-the-fly closed-loop materials discovery via Bayesian active learning
10.1038/s41467-020-19597-w · 2020 · External reference
Closed-loop optimization of nanoparticle synthesis enabled by robotics and machine learning
10.1016/j.matt.2023.01.018 · 2023 · External reference
Artificial Chemist: An Autonomous Quantum Dot Synthesis Bot
2020 · External reference
Machine learning-driven advances in nanotechnology: From materials design to process optimization – A review
2026 · External reference
Role of Artificial Intelligence and Machine Learning in Nanosafety
10.1002/smll.202001883 · 2020 · External reference
Machine Learning-Enhanced Nanoparticle design for precision Cancer drug delivery
10.4028/b-xdtcg5 · 2025 · External reference
Applying explainable artificial intelligence and ensemble boosting based machine learning models in predicting the thermal conductivity of nano enhanced phase change materials
2026 · External reference
Interpretable and Explainable Machine Learning for Materials and Chemistry
10.1021/accountsmr.1c00244 · 2022 · External reference
Advances of machine learning in materials science
10.1007/s11467-023-1325-z · 2024 · External reference
A data quality and quantity governance for machine learning in materials science
2023 · External reference
Reproducibility in materials informatics: lessons from ‘A general-purpose machine learning framework for predicting properties of inorganic materials
2024 · External reference
Replicating machine learning experiments in materials Science
2020 · External reference
Ethical artificial intelligence in chemical research and development
2021 · External reference
A review of causality-based fairness machine learning
10.20517/ir.2022.17 · 2022 · External reference
Twenty years of in vitro nanotoxicology: how AI could make a difference
2024 · External reference
Foundation models for materials discovery – current state and future opportunities
2025 · External reference
Unresolved reference
External reference
Materials science in the era of large language models: a perspective
10.1039/d4dd00074a · 2024 · External reference
32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery
10.1088/2632-2153/ae011a · 2025 · External reference
arXiv preprint
2024 · External reference
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
2025 · External reference
Physics informed machine learning
10.1038/s42254-021-00314-5 · 2021 · External reference
Physics informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
10.1016/j.jcp.2018.10.045 · 2019 · External reference
Understanding physics informed neural networks
2024 · External reference
Embedding physics into machine learning: a review of physics informed machine learning
2026 · External reference
Physics informed neural networks in materials modeling and mechanics
2025 · External reference
Autonomous AI agents in ORR electrocatalyst discovery: a review of closed-loop workflows, materials bottlenecks, and energy system translation
10.1039/d6ma00429f · 2026 · External reference
Accelerating multimetallic catalyst discovery with robotics and agentic AI
10.20517/aiagent.2025.07 · 2025 · External reference
Computationally guided high-throughput design of self-assembling drug nanoparticles
10.1038/s41565-021-00870-y · 2021 · External reference
A multimodal robotic platform for multi-element electrocatalyst discovery
10.1038/s41586-025-09640-5 · 2025 · External reference
