Materials Science
Controlling light-matter interactions is emerging as a powerful strategy to enhance the performance of organic light-emitting diodes (OLEDs). By embedding the emissive layer in planar microcavities or other modified optical environments,…
Predicting tensorial properties with machine learning models typically requires carefully designed tensorial descriptors. In this work, we introduce an alternative strategy for learning tensorial quantities based on scalar descriptors. We…
The irradiation stability of Cr based protective coatings on zirconium alloys is critical for the development of accident-tolerant fuel claddings. However, conventional surface irradiation often produces shallow, nonuniform damage,…
We investigate iron-cobalt (Fe-Co) alloys as a representative high-performance catalyst system for SWCNT growth in a systematic manner by combining chemical vapor deposition (CVD) experiments with chirality-resolved spectroscopic analysis,…
The design of sustainable materials requires access to materials performance and sustainability data from literature corpus in an organized, structured and automated manner. Natural language processing approaches, particularly large…
Nonlinear mechanical metamaterials can exhibit emergent transport phenomena that mimic topological protection without relying on linear band topology. Here, we realize a bifurcation-induced nonreciprocal lattice that supports robust…
Grain boundary networks and their evolution are strongly influenced by triple junctions. The defect nature of these line defects significantly affects the properties of the network, but they have not been fully characterized to date. Here,…
The tunability of anomalous Hall and Nernst conductivities is investigated in the compensated ferrimagnet Mn$_3$Al under isotropic strain ($\eta$) and chemical potential variation using first-principles calculations. At a chemical potential…
Electric-field driven magnetization switching in FePt/BaTiO$_3$ (001) is demonstrated through first-principles calculations. The magnetic easy axis of FePt layer undergoes a transition from in-plane to perpendicular direction upon…
Electrode-potential-induced dynamic coordination is an essential factor governing the performance of graphene-embedded single-atom catalysts (SACs). While previous studies have primarily centered on structural dynamics at the metal site,…
Prediction of crystal system from X-ray diffraction (XRD) spectra is a critical task in materials science, particularly for perovskite materials which are known for their diverse applications in photovoltaics, optoelectronics, and…
We designed a high-entropy doped NASICON cathode, Na$_3$V$_{1.9}$(CrMoAlZrNi)$_{0.1}$(PO$_4$)$_3$ and investigate its electrochemical performance for sodium-ion batteries (SIBs) to understand the diffusion mechanism including distribution…
Symmetry constraints determine which physical responses are allowed in a given system. Magnetization induced by strain fields, such as in piezomagnetic and flexomagnetic effects, has typically been considered in materials that break…
Molybdenum carbide (MoC) is a promising candidate for substituting expensive platinum-group metals in many applications owing to its low cost and excellent properties. A comprehensive understanding of the carrier dynamics in MoC facilitates…
The Rashba-Edelstein effect (REE), which generates spin accumulation under an applied electric current, quantifies charge-to-spin conversion (CSC) efficiency in non-centrosymmetric systems. However, systematic investigations of REE in…
Zinc-based electrochromic devices offer a sustainable route for dynamic optical management but are plagued by poor cycling stability due to irreversible zinc plating/stripping and side reactions. Herein, we report a robust, high-contrast,…
The utilization of terahertz (THz) emission spectroscopy in femtosecond photoexcited spintronic heterostructures has emerged as a versatile tool for investigating ultrafast spin-transport in a noncontact and non-invasive manner. However,…
HfO2-based ferroelectric films have attracted considerable attention as their nanoscale ferroelectricity and compatibility with cmos technology, fulfilling demands of emerging memory technologies. However, as films scale down,…
Machine learning models have recently emerged to predict whether hypothetical solid-state materials can be synthesized. These models aim to circumvent direct first-principles modeling of solid-state phase transformations, instead learning…
One-dimensional (1D) nanostructures of transition metal trichalcogenides (TMT) show unique properties through the combination of their anisotropic bonding and low dimensionality. Scalable synthesis approaches that enable control over the…