Related papers: Distilling Accurate Descriptors from Multi-Source …
With the development of affordable aberration-correctors, analytical scanning transmission electron microscopy (STEM) studies of complex interfaces can now be conducted at high spatial resolution at laboratories worldwide. Energy-dispersive…
Perovskites with fast oxygen ion conduction can enable technologies like solid oxide fuel cells. One component of fast oxygen ion conduction is low oxygen migration barrier. Here we apply ab initio methods on over 40 perovskites to produce…
The development of high-activity and low-price cathodic catalysts to facilitate the electrochemical sluggish O$_2$ reduction reaction (ORR) is very important to achieve the commercial application of fuel cells. Here, we have investigated…
The development of efficient and stable intermediate-temperature solid oxide fuel cells (SOFCs) necessitates high-performance cathode materials that are cobalt-free, cost-effective, and compatible with proton-conducting electrolytes. While…
Catalyst discovery is paramount to support access to energy and key chemical feedstocks in a post fossil fuel era. Exhaustive computational searches of large material design spaces using ab-initio methods like density functional theory…
Out-of-distribution (OOD) detection is critical for the safe deployment of deep neural networks. State-of-the-art post-hoc methods typically derive OOD scores from the output logits or penultimate feature vector obtained via global average…
We introduce the proper orthogonal descriptors for efficient and accurate interatomic potentials of multi-element chemical systems. The potential energy surface of a multi-element system is represented as a many-body expansion of…
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,…
The discovery of new catalysts that are efficient, sustainable, and low-cost is a major research endeavor for many industrial chemical processes. This requires an understanding and determination of the catalytic origins for the given…
Prediction of properties from composition is a fundamental goal of materials science and can greatly accelerate development of functional materials. It is particularly relevant for ferroelectric perovskite solid solutions where…
Perovskite-type iron oxides with Fe4+ ions have attracted much attention for their versatile helimagnetic phases. While the introduction of a layered A-site ordered structure to AFeO3 with Fe4+ ions potentially lead to novel helimagnetic…
Transition-metal perovskite oxides constitute a series of functional material systems for electronics, catalysis and energy-conversion processes, in which oxygen migration and evolution play a key role. However, the stable metal-oxygen…
Most existing CNN-based salient object detection methods can identify local segmentation details like hair and animal fur, but often misinterpret the real saliency due to the lack of global contextual information caused by the…
The water gas shift reaction (WGS) is important and widely applied in the production of H2. Cu modified perovskites are promising catalysts for WGS reactions in hydrogen generation. However, the structure-dependent stability and reaction…
Recent advancements in dislocation engineering are reshaping the traditional view towards ceramics being brittle. Here, we use KTaO3 (KTO), a perovskite oxide that is newly discovered with room-temperature bulk plasticity, and demonstrate…
In this work, we have proposed a data-driven screening framework combining the interpretable machine learning with high-throughput calculations to identify a series of metal oxides that exhibit both high-temperature tolerance and high power…
The spinel/perovskite heterointerface $\gamma$-Al$_2$O$_3$/SrTiO$_3$ hosts a two-dimensional electron system (2DES) with electron mobilities exceeding those in its all-perovskite counterpart LaAlO$_3$/SrTiO$_3$ by more than an order of…
Metal-organic frameworks (MOFs) have been widely investigated for challenging catalytic transformations due to their well-defined structures and high degree of synthetic tunability. These features, at least in principle, make MOFs ideally…
Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEAs) offer a vast compositional space for tuning such…
Catalysis informatics is constantly developing, and significant advances in data mining, molecular simulation, and automation for computational design and high-throughput experimentation have been achieved. However, efforts to reveal the…