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Related papers: Open Catalyst Experiments 2024 (OCx24): Bridging E…

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Two-dimensional materials supported by single atom catalysis (SACs) are foreseen to replace platinum for large-scale industrial scalability of sustainable hydrogen generation. Here, a series of metal (Al, Sc, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn)…

Materials Science · Physics 2022-11-04 M. V. Jyothirmai , D. Roshini , B. Moses Abraham , Jayant K. Singh

To enhance the activity of photocatalysts for hydrogen production and CO2 conversion, noble metal cocatalysts as electron traps and/or acceptors such as platinum or gold are usually utilized. This study hypothesizes that mixing elements…

Materials Science · Physics 2025-01-17 Jacqueline Hidalgo-Jiménez , Taner Akbay , Xavier Sauvage , Tatsumi Ishihara , Kaveh Edalati

The James Webb Space Telescope enabled the first detection of several rovibrational emission lines of HD in the Orion Bar, a prototypical photodissociation region. This provides an incentive to examine the physics of HD in dense and strong…

Heterogeneous catalysis is an example of a complex materials function, governed by an intricate interplay of several processes, e.g., the different surface chemical reactions, and the dynamic re-structuring of the catalyst material at…

Disorder and defective coordination in the catalytic plane are crucial for enhancing the Hydrogen Evolution Reaction (HER) on two-dimensional catalysts. Amorphous materials are disordered, making them catalytically adaptive for many…

Materials Science · Physics 2026-05-11 Sreehari M S , Ashutosh Krishna Amaram , Raghavan Ranganathan

The demand for safe, high-energy-density batteries has spotlighted halide solid-state electrolytes, which offer the potential for enhanced ionic mobility, electrochemical stability, and interfacial deformability. Accelerating their…

Data-intensive science is increasingly reliant on real-time processing capabilities and machine learning workflows, in order to filter and analyze the extreme volumes of data being collected. This is especially true at the energy and…

Artificial Intelligence · Computer Science 2021-04-21 Chinmaya Mahesh , Kristin Dona , David W. Miller , Yuxin Chen

With increasing emphasis on carbon neutrality, accurate and efficient combustion prediction has become essential for the design and optimization of new generation combustion systems. This study established a computational framework by…

Symbolic regression (SR) is an emerging method for building analytical formulas to find models that best fit data sets. Here, SR was used to guide the design of new oxide perovskite catalysts with improved oxygen evolution reaction (OER)…

Materials Science · Physics 2019-08-20 Baicheng Weng , Zhilong Song , Rilong Zhu , Qingyu Yan , Qingde Sun , Corey G. Grice , Yanfa Yan , Wan-Jian Yin

Modern concrete must simultaneously satisfy evolving demands for mechanical performance, workability, durability, and sustainability, making mix designs increasingly complex. Recent studies leveraging Artificial Intelligence (AI) and…

Machine Learning · Computer Science 2026-03-24 Bayezid Baten , M. Ayyan Iqbal , Sebastian Ament , Julius Kusuma , Nishant Garg

The availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H2) under given parameters of pressure swing and temperature. Previously, we…

Chemical Physics · Physics 2021-02-08 Srimukh Prasad Veccham , Martin Head-Gordon

Particle collisions at accelerators such as the Large Hadron Collider, recorded and analyzed by experiments such as ATLAS and CMS, enable exquisite measurements of the Standard Model and searches for new phenomena. Simulations of collision…

The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some…

Materials Science · Physics 2021-10-04 Krishnendu Mukherjee , Alexander W. Dowling , Yamil Colón

Access to the potential energy Hessian enables determination of the Gibbs free energy, and certain approaches to transition state search and optimization. Here, we demonstrate that off-the-shelf pretrained Open Catalyst Project (OCP)…

Materials Science · Physics 2024-10-08 Brook Wander , Joseph Musielewicz , Raffaele Cheula , John R. Kitchin

Conventional generative models for materials discovery are predominantly trained and validated using data from Density Functional Theory (DFT) with approximate exchange-correlation functionals. This creates a fundamental bottleneck: these…

Artificial Intelligence · Computer Science 2026-04-30 Mahule Roy

At the CHEP03 conference we launched the Physics Analysis eXpert (PAX), a C++ toolkit released for the use in advanced high energy physics (HEP) analyses. This toolkit allows to define a level of abstraction beyond detector reconstruction…

Data Analysis, Statistics and Probability · Physics 2009-11-11 Steffen Kappler , Martin Erdmann , Ulrich Felzmann , Dominic Hirschbuehl , Matthias Kirsch , Guenter Quast , Alexander Schmidt , Joanna Weng

Smart aquaculture systems depend on rich environmental data streams to protect fish welfare, optimize feeding, and reduce energy use. Yet public datasets that describe the air surrounding indoor tanks remain scarce, limiting the development…

Machine Learning · Computer Science 2025-09-30 Youssef Sabiri , Walid Houmaidi , Ouail El Maadi , Yousra Chtouki

Concrete is the most widely used engineered material in the world with more than 10 billion tons produced annually. Unfortunately, with that scale comes a significant burden in terms of energy, water, and release of greenhouse gases and…

The ongoing energy crisis has underscored the urgent need for energy-efficient materials with high energy utilization efficiency, prompting a surge in research into organic compounds due to their environmental compatibility, cost-effective…

Chemical Physics · Physics 2025-07-24 Qi Ou , Hongshuai Wang , Minyang Zhuang , Shangqian Chen , Lele Liu , Ning Wang , Zhifeng Gao

Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the cost of calculating the adsorption…