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Research Highlights
Electrode Phase Engineering Improves Reliability of Ultrathin TaOx Memristors for Neuromorphic Computing
This work identifies room-temperature UVO and electrode phase engineering as a practical strategy to improve the performance and reliability of ultrathin TaOx memristors, enabling more robust resistive memory for next-generation in-memory and neuromorphic computing.
AI Enables Low-Dose, Real-Time Atomic Imaging
The study develops a machine learning model that denoises high-resolution transmission electron microscopy images without the need of retraining for completely different samples.
Interpretable Machine Learning Bridges Data-driven Prediction and Spectroscopic Insights
This work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable machine learning (ML) that links atomic structure, electronic structure, and spectroscopic observables.
Novel Strain-Relief Mechanism Revealed by Multimodal Experiments and AI
This work expands the understanding of how nanoscale strain evolves and transforms materials, with potential implications for advanced material design, geoscience, and other strain-driven systems.
Vacancy-Driven Mechanisms in Hydrogen Reduction of Iron Oxides
These insights reveal how controlling atomic-scale defects can improve metal production, enhance catalysts, and design more resilient oxide materials for energy applications.
Surfactant-Guided Reshaping Enables Precise Facet Control in Gold Nanocrystals
The study introduces a one-pot, room-temperature method to reshape gold nanocrystals and control their surface facets. It demonstrates a surfactant-driven mechanism that transforms particles from initial shapes to spheres and then to polyhedral forms while preserving volume.
Arbitrary Design of DNA-Programmable 3D Crystals through Symmetry Mapping
CFN researchers and collaborators developed a symmetry-mapping algorithm, MOSES, that streamlines the design of DNA voxels and can be generalized to patchy particles.
Gas-Dependent Oxide Reduction Revealed at the Atomic Scale
By revealing gas-dependent reduction dynamics, this work provides a mechanistic foundation for metal production and catalyst design.
Simple Method for Trapping of Xenon in Nanocages
Researchers demonstrated a scalable and cost-effective method for trapping Xe, a scarce noble gas relevant to nuclear energy, nuclear safety, non-proliferation, medical imaging, and space propulsion.
Insights into EUV Resist Molecular Uniformity through Nano-Projectile SIMS
This capability provides a powerful new method for understanding and optimizing hybrid resists—key materials for advancing extreme ultraviolet (EUV) lithography in next-generation semiconductor manufacturing.
Reactant-Gas-Induced Nanoparticle Dynamics Depend on Size
We observe size-dependent morphological dynamics of supported metal nanoparticles (NPs) induced by interaction with reactant gases and find these are correlated with reaction pathway and product selectivity.
VISION: Voice-Controlled AI for Next-Gen Scientific Experimentation
This advance showcases how AI can seamlessly extend human interaction with complex scientific instruments, laying foundational infrastructure for AI-augmented scientific discovery.
