Abstract Machine learning (ML) has been rapidly transforming the landscape of natural
sciences and has the potential to revolutionize the process of data analysis and hypothesis …

The discovery of advanced materials is the cornerstone of human technological
development and progress. The structures of materials and their corresponding properties …

Porous adsorbents have common characteristics, such as high porosity and a large specific
surface area. These characteristics, attributed to the internal structure of the material …

Complex pore structures in catalysts can significantly impact flow, heat transfer, and
ultimately, reaction efficiency. In steam methane reforming (SMR) for hydrogen production …

Activated carbon (AC) is essential for its exceptional adsorption properties and high surface
area in various applications. Adsorption/desorption (A/D) processes with AC can be …

“Fifth generation and beyond” communication technologies have sparked considerable
demand for polymer composite materials with low thermal expansion coefficients (CTE) and …

Operator learning promises generalized and accelerated predictions for fluid flow problems.
Using non-body fitted Cartesian mesh based CFD simulation data, we explore if multiphase …

Tackling the issues posed by climate change and the need to reduce greenhouse gas
emissions has led to the development of novel adsorbent materials tailored for clean energy …

This review analyzes the current practices in the data-driven characterization, design and
optimization of disordered nanoporous materials with pore sizes ranging from angstroms …

The discovery of advanced materials is the cornerstone of human technological
development and progress. The structures of materials and their corresponding properties …