Researchers discovered that a polymer additive promotes smooth, layer-by-layer deposition on metal electrodes by tuning interactions with the substrate.

Anisotropies in surface potential driven by competitive ion adsorption can alter facet selectivity during oriented attachment.

Summarizing the state of designed protein hybrid materials, researchers celebrate both the 50th anniversary of the MRS Bulletin and the 2025 Fred Kavli Distinguished Lecturers in Materials Science, Jim De Yoreo and David Baker.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

Specially designed histidine-containing peptoids mimic carbonic anhydrase to accelerate calcite step growth.

Imaging ice microstructures formed by water freezing with atomic resolution for the first time.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

Tailored assemblies mimic natural enzyme activity with significantly higher stability.

In high-entropy oxides, chromium tends to segregate during growth due to oxidation-induced migration of smaller, high-valence cations.

Researchers developed a way to precisely control dopant structures and locations in carbon-based materials.

Researchers developed a pathway for the solution synthesis of core–crown heterostructures with controlled electronic properties.

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

Chromium cations better adapt to changes in oxygen stoichiometry than iron cations.

Using interfacial charge transfer to control cation charges in oxide superlattices offers insights for designing functional heterostructures.

Calcium carbonate mineralization occurs through a multi-step process that begins with a dense liquid phase.

A newly funded project will develop the fundamental understanding of phenomena that underpin material properties important for quantum applications.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.

Fully identifying what controls nanocrystal assembly requires incorporating non-traditional forces into models.