相关论文: High-Throughput Search for Photostrictive Material…
Automated analysis of high-resolution transmission electron microscopy (HRTEM) images is increasingly essential for advancing research in organic electronics, where precise characterization of nanoscale crystal structures is crucial for…
Two-dimensional materials such as graphene and transition metal dichalcogenides (TMDs) are ideal candidates to create ultra-thin electronics suitable for flexible substrates. Although optoelectronic devices based on TMDs have demonstrated…
Strain engineering is a powerful and widely used strategy for boosting the performance of electronic and optoelectronic devices. Here, we demonstrate an approach to tune the photoelectric properties of Platinum sulfide (PtS$_2$) by using a…
A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab initio calculations are widely used to guide experiments by…
Transient detection and flux measurement via image subtraction stand at the base of time domain astronomy. Due to the varying seeing conditions, the image subtraction process is non-trivial, and existing solutions suffer from a variety of…
Future generation technologies demand high efficiency photodetectors to enable sensing and switching devices for ultrafast communication and machine vision. This require direct-band gap materials with high photosensitivity, high detectivity…
Half-Heuslers are a promising family for thermoelectric (TE) applications, yet only a small fraction of their potential chemistries has been experimentally explored. In this work, we introduce a distinct computational high-throughput…
The excellent optoelectronic properties, straightforward synthesis, and robust material stability of quasi-2D metal halide perovskites have made them a hot research topic for optoelectronic devices. In layered organic-inorganic perovskites,…
We present a selection of candidates of clusters and protoclusters of galaxies identified in the photometric data of the HSC-SSP Wide Public Data Release 3 (PDR3), spanning the redshift range $\rm 0.1 \leq z \leq 2$. The selection method,…
Thermoelectric materials, which can convert waste heat into electricity or act as solid-state Peltier coolers, are emerging as key technologies to address global energy shortages and environmental sustainability. However, discovering…
Excitons -- two-particle correlated electron-hole pairs -- are the dominant low-energy optical excitation in the broad class of semiconductor materials, which range from classical silicon to perovskites, and from two-dimensional to organic…
This work presents a machine learning approach to predict novel perovskite oxide materials in the Pr-Al-O and Pr-Sc-O compound families with the potential for photoluminescence applications. The predicted materials exhibit a large bandgap…
High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli…
The discovery of new superconducting materials, particularly those exhibiting high critical temperature ($T_c$), has been a vibrant area of study within the field of condensed matter physics. Conventional approaches primarily rely on…
Photoplasticity, the light-induced change in plastic deformation, plays a pivotal role in the mechanical durability and manufacturing of semiconductor materials. Yet, its governing mechanisms remain incompletely understood, owing to the…
Finding cost-effective and efficient photocatalytic materials able to catalyse the water splitting reaction under visible light is one of the greatest challenges in current environmental material science. Despite that many photocatalysts…
We cast the relation between the chemical composition of a solid-state material and its superconducting critical temperature (Tc) as a statistical learning problem with reduced complexity. Training of query-aware similarity-based ridge…
Atomically thin two-dimensional (2D) semiconductors are extensively investigated for opto-electronic applications that require strong light-matter interactions. In view of such applications, it is essential to understand how…
Data-driven methods, in particular machine learning, can help to speed up the discovery of new materials by finding hidden patterns in existing data and using them to identify promising candidate materials. In the case of superconductors,…
A critical challenge for the integration of the optoelectronics is that photodetectors have relatively poor sensitivities at the nanometer scale. It is generally believed that a large electrodes spacing in photodetectors is required to…