A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou +7 more
wiley +1 more source
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy +3 more
wiley +1 more source
Prioritising topics for developing e-learning resources in healthcare curricula: A comparison between students and educators using a modified Delphi survey. [PDF]
Lim HM +24 more
europepmc +1 more source
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley +1 more source
Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann +8 more
wiley +1 more source
Accelerated Discovery of High Performance Ni3S4/Ni3Mo HER Catalysts via Bayesian Optimization
Integrated workflow accelerates the catalyst discovery of hydrogen evolution reaction via Bayesian optimization. An experiment‐trained surrogate model proposes synthesis conditions, guiding iterative refinement using electrochemical performance metrics.
Namuersaihan Namuersaihan +9 more
wiley +1 more source
Fine-grained causal effect estimation of learning resources via dynamic causal heterogeneous graph neural networks. [PDF]
Ren Y, Chen Z, Jiang X, Du Z.
europepmc +1 more source
Frontier Advances of Emerging High‐Entropy Anodes in Alkali Metal‐Ion Batteries
Recent advances in microscopic morphology control of high‐entropy anode materials for alkali metal‐ion batteries. Abstract With the growing demand for sustainable energy, portable energy storage systems have become increasingly critical. Among them, the development of rechargeable batteries is primarily driven by breakthroughs in electrode materials ...
Liang Du +14 more
wiley +1 more source
Correction of author affiliation: Faculty perceptions and use of e-learning resources for medical education and future predictions. [PDF]
Kim KJ, Kim G, Kang Y.
europepmc +1 more source
Artificial Intelligence as the Next Visionary in Liquid Crystal Research
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam +2 more
wiley +1 more source

