Materials Science
The mechanical reliability of nitrogen-doped graphene is often attributed to its nitrogen content, yet nitrogen occurs in chemically distinct configurations whose individual mechanical roles, and whose interactions with other defects,…
Refractory high-entropy alloys have emerged as promising candidates for high-temperature applications due to their exceptional mechanical properties. Understanding the thermodynamic mechanisms underlying chemical ordering in these complex…
Polaron formation localizes charge carriers and drives a crossover from band-like to hopping transport in materials. Hopping dynamics can be obtained from DFT supercell calculations of transition states, but these suffer from polaron…
Crystal structure databases curated by high-throughput density functional theory calculations typically serve as the starting point for computational materials discovery efforts. Thermodynamic stability data, such as formation energies and…
Predictive modeling of ultrashort-pulse laser ablation requires temperature-dependent material parameters derived from the electronic structure, namely the electronic thermal conductivity, electron--phonon coupling, and heat capacity. These…
Hubbard-corrected density-functional theory (DFT+$U$) is a popular tool for first-principles modeling of materials with localized $d$ or $f$ electrons, but its on-site corrections tend to over-localize charge and break covalent bonds.…
Quantum materials experiments increasingly rely on microwave, electrical, thermal, optical, and structural probes, but these capabilities are typically assembled from custom hardware that limits reproducibility and scalability. Here we show…
Symmetry-governed magnetic materials have emerged as a promising platform for spintronic functionalities without net magnetization or stray magnetic fields, motivating the exploration of how lattice dynamics couple to symmetry-derived…
Despite the advances in structure-based modeling of polymer properties, accurately predicting glass transition temperature (Tg) is still challenging for polymers whose behavior is strongly influenced by intermolecular interactions and…
The number of possible crystal structures vastly exceeds the number realized among thermodynamically stable inorganic materials, suggesting that experimentally accessible structure space is organized around a limited set of preferred…
Generative artificial intelligence is rapidly transforming materials design by enabling de novo exploration of immense chemical spaces. Yet a large proportion of AI-generated compositions remain implausible, violating established chemical…
Laser annealing (LA) technique has emerged as an effective method for localized crystallization of magneto-optical (MO) garnet thin films on semiconductor substrates. However, no studies have explored the crystallization and magneto-optical…
The iso-orbital indicator $\alpha = (\tau - \tau^\mathrm{vW})/\tau^\mathrm{UEG}$ is a key ingredient of meta-generalized gradient approximation (meta-GGA) functionals, but diverges in low-density tails , causing unphysical exchange…
Nonradiative charge transfer processes play a central role in a wide range of physical phenomena, including reliability phenomena in semiconductor devices such as bias temperature instability, hysteresis, random telegraph noise, and…
The composition-dependent magnetic properties of B2-ordered \zfr~alloys with substitutional disorder on the Fe sublattice are investigated using first-principles calculations within the coherent potential approximation. By systematically…
Commercial fusion energy requires materials that survive intense neutron bombardment whilst extracting extreme heat loads for conversion to electricity. The CuCrZr alloy, the leading heat-sink material for fusion reactors, derives its…
The properties of strongly correlated electron materials exhibit a surprising sensitivity to small lattice distortions, providing an opportunity for their tuning by selective distortion driving, usually achieved by optical excitations.…
This study combines high-throughput DFT calculations with machine learning techniques to uncover the key descriptors governing the nitrogen reduction reaction (NRR) in intermetallic compounds (IMCs). A dataset of 47 bimetallic IMCs was…
The disordered and defect-rich structure of amorphous solids forms heterogeneous, high-dimensional energy landscapes. Such an energy landscape can be described by a discrete-state network of transitions between stable energy minima. Under…
The nonlinear Hall effect (NLHE) enables the generation of a transverse charge current in nonmagnetic materials with broken inversion symmetry while preserving time-reversal symmetry through the Berry curvature dipole (BCD). However, in…