Operando-informed precatalyst programming towards reliable high-current-density electrolysis
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Effect of hydrogen leakage on the life cycle climate impacts of hydrogen supply chains
Hydrogen is of interest for decarbonizing hard-to-abate sectors because it does not produce carbon dioxide when combusted. However, hydrogen has indirect warming effects. Here we conducted a life cycle assessment of electrolysis and steam methane reforming to assess their emissions while considering hydrogen’s indirect warming effects. We find that the primary factors influencing life cycle climate impacts are the production method and related feedstock emissions rather than the hydrogen leakage and indirect warming potential. A comparison between fossil fuel-based and hydrogen-based steel production and heavy-duty transportation showed a reduction in emissions of 800 to more than 1400 kg carbon dioxide equivalent per tonne of steel and 0.1 to 0.17 kg carbon dioxide equivalent per tonne-km of cargo. While any hydrogen production pathway reduces greenhouse gas emissions for steel, this is not the case for heavy-duty transportation. Therefore, we recommend a sector-specific approach in prioritizing application areas for hydrogen.
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Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.
Accelerated symptom improvement in Parkinson’s disease via remote internet-based optimization of deep brain stimulation therapy: a randomized controlled multicenter trial
Deep brain stimulation (DBS) has emerged as an important therapeutic intervention for neurological and neuropsychiatric disorders. After initial programming, clinicians are tasked with fine-tuning DBS parameters through repeated in-person clinic visits. We aimed to evaluate whether DBS patients achieve clinical benefit more rapidly by incorporating remote internet-based adjustment (RIBA) of stimulation parameters into the continuum of care.
A catalyst-coated diaphragm assembly to improve the performance and energy efficiency of alkaline water electrolysers
Alkaline water electrolysers are ideal for gigawatt-scale hydrogen production due to the usage of non-precious metal and low-cost raw materials. However, their performances are modest with the separated electrode and diaphragm structure which can date back to more than 100 years ago. Here we report a catalyst-coated diaphragm assembly to improve the performance of alkaline water electrolysers. The transport resistance of OH– ions is reduced and the electrochemical surface area of catalysts is enlarged by more than forty fold, representing more than 40% increase in hydrogen production rate or as much as 16% reduction in energy consumption. The electrolyser with our catalyst-coated diaphragm assembly delivers current densities as high as 1 A cm−2 at 1.8 V or 2 A cm−2 at 2 V and shows good stability after more than 1000 hours of operation. Therefore, the catalyst-coated diaphragm assembly route is promising for the development of high-performance and efficient alkaline water electrolysers.
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