相关论文: Data-driven design of new catalytic materials in m…
The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials. One class of materials that currently lacks sufficient training data is oxides,…
Methane pyrolysis provides a scalable alternative to conventional hydrogen production methods, avoiding greenhouse gas emissions. However, high operating temperatures limit economic feasibility on an industrial scale. A major scientific…
Methane (CH4) formation from photocatalytic carbon dioxide (CO2) conversion in water is currently of interest because methane is a fuel, and it can also be transformed into other useful hydrocarbons. However, achieving high selectivity to…
Dry reforming of methane (DRM) over platinum catalysts offers a promising route for CO2 utilization and syngas (H2/CO) production, a versatile feedstock for synthetic fuels. This study employs automated chemical kinetic model generation to…
The transition to sustainable green hydrogen production demands innovative electrocatalyst design strategies that can overcome current technological limitations. This study introduces a comprehensive data-driven approach to predicting and…
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…
Methanol occupies a central role in chemical synthesis and is considered an ideal candidate for cleaner fuel storage and transportation. It can be catalyzed from water and volatile organic compounds such as carbon dioxide, thereby offering…
A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). The sensitivities of the thermo-chemical variables with respect to the…
The search for low-cost, durable, and effective catalysts is essential for green hydrogen production and carbon dioxide upcycling to help in the mitigation of climate change. Discovery of new catalysts is currently limited by the gap…
The oxygen vacancy formation energy ($\Delta E_{vf}$) governs defect dynamics and is a useful metric to perform materials selection for a variety of applications. However, density functional theory (DFT) calculations of $\Delta E_{vf}$ come…
Mitigating the climate crisis requires a rapid transition towards lower-carbon energy. Catalyst materials play a crucial role in the electrochemical reactions involved in numerous industrial processes key to this transition, such as…
Transforming CO$_2$ into methanol represents a crucial step towards closing the carbon cycle, with thermoreduction technology nearing industrial application. However, obtaining high methanol yields and ensuring the stability of…
With the global transition towards cleaner energy and sustainable processes, the demand for efficient catalysts, especially for the oxygen reduction reaction, has gained attention from the scientific community. This research work…
The development of machine learned potentials for catalyst discovery has predominantly been focused on very specific chemistries and material compositions. While effective in interpolating between available materials, these approaches…
As a core technology for green chemical synthesis and electrochemical energy storage, electrocatalysis is central to decarbonization strategies aimed at combating climate change. In this context, computational and machine learning driven…
The conversion of $\mathrm{CO_2}$ to value-added compounds is an important part of the effort to store and reuse atmospheric $\mathrm{CO_2}$ emissions. Here we focus on $\mathrm{CO_2}$ hydrogenation over so-called inverse catalysts:…
Direct air capture (DAC) of carbon dioxide is a critical technology for mitigating climate change, but current materials face limitations in efficiency and scalability. We discover novel DAC materials using a combined machine learning (ML)…
Scalable and cost-effective solutions to renewable energy storage are essential to addressing the world's rising energy needs while reducing climate change. As we increase our reliance on renewable energy sources such as wind and solar,…
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…
The discovery and optimization of high-performance materials is the basis for advancing energy conversion technologies. To understand composition-property relationships, all available data sources should be leveraged: experimental results,…