The increasing demand for high-security, high-performance, and low-cost energy storage
systems (EESs) driven by the adoption of renewable energy is gradually surpassing the …

Recent advances in deep learning generative models (GMs) have created high capabilities
in accessing and assessing complex high-dimensional data, allowing superior efficiency in …

Recent advancements in property-directed generative design of inorganic materials account
for periodicity and global Euclidian symmetry through translations, rotations, and reflections; …

Near-infrared (NIR) laser radiation based on Er3+-doped crystals has attracted considerable
attention owing to its important applications in medical imaging, spectroscopy, remote …

Green and intelligent manufacturing has become the key direction of industrial production
development. In-situ measuring and sintering simulation technologies play a key role in the …

Crystal structure prediction (CSP) drives the discovery and design of innovative materials.
However, existing CSP methods rely heavily on formation enthalpies calculated by density …

The development of acid-stable water oxidation electrocatalysts is crucial for high-
performance energy conversion devices. Different from traditional nanostructuring, here we …

The prediction of new compounds via crystal structure prediction may transform how the
materials chemistry community discovers new compounds. In the prediction of inorganic …

The full-potential linear augmented plane wave with local orbital (FP-LAPW) technique is
now used in this approach to better understand the structural, electronic, optical and …

We propose an adiabatic time evolution (ATE) method for obtaining the ground state of a
quantum many-electron system on a quantum circuit based on first quantization. As a …