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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.
Synergistic proton conduction via Ca-vacancy coupled with Li+-bridge in Ca5(PO4)3OH
Proton conductivity plays a crucial role in the advancement of materials for proton ceramic fuel cells (PCFCs) and a variety of electrochemical devices. Traditional approaches to enhancing proton conductivity in perovskites have largely relied on doping strategies to induce structural oxygen vacancies. However, these methods have yet to overcome the challenges associated with achieving desired proton conductivity. Here, we introduce an approach wherein intermediate Li+ ions act as a bridge linked to Ca vacancies, fostering a mechanism for accelerated proton transport. Utilizing protonated Ca5(PO4)3OH-H(Li) as an electrolyte, we achieve a proton conductivity of 0.1 S cm−1 and a fuel cell performance of 661 mW cm−2 at an operational temperature of 550 °C for realizing low temperature PCFCs. This proton transport synergy overcomes traditional doping limitations, enabling the advancement of proton-conducting electrolytes and enhancing the efficiency of proton conducting electrolyte fuel cells, with implications in energy conversion and storage technologies.
First-principles and machine-learning approaches for interpreting and predicting the properties of MXenes
MXenes are a versatile family of 2D inorganic materials with applications in energy storage, shielding, sensing, and catalysis. This review highlights computational studies using density functional theory and machine-learning approaches to explore their structure (stacking, functionalization, doping), properties (electronic, mechanical, magnetic), and application potential. Key advances and challenges are critically examined, offering insights into applying computational research to transition these materials from the lab to practical use.
Iterative printing of bulk metal and polymer for additive manufacturing of multi-layer electronic circuits
In pursuing advancing additive manufacturing (AM) techniques for 3D objects, this study combines AM techniques for bulk metal and polymer on a single platform for one-stop printing of multilayer 3D electronic circuits with two novel aspects. The first innovation involves the embedded integration of electronic circuits by printing low-resistance electrical traces from bulk metal into polymer channels. Cross-section grinding results reveal (92 ± 5)% occupancy of electrically conductive traces in polymer channels despite the different thermal properties of the two materials. The second aspect encompasses the possibility of printing vertical bulk metal vias up to 10 mm in height with the potential for expansion, interconnecting electrically conductive traces embedded in different layers of the 3D object. The work provides comprehensive 3D printing design guidelines for successfully integrating fully embedded electrically conductive traces and the interconnecting vertical bulk metal vias. A smooth and continuous workflow is also introduced, enabling a single-run print of functional multilayer embedded 3D electronics. The design rules and the workflow facilitate the iterative printing of two distinct materials, each defined by unique printing temperatures and techniques. Observations indicate that conductive traces using molten metal microdroplets show a 12-fold reduction in resistance compared to nanoparticle ink-based methods, meaning this technique greatly complements multi-material additive manufacturing (MM-AM). The work presents insights into the behavior of molten metal microdroplets on a polymer substrate when printed through the MM-AM process. It explores their characteristics in two scenarios: When they are deposited side-by-side to form conductive traces and when they are deposited out-of-plane to create vertical bulk metal vias. The innovative application of MM-AM to produce multilayer embedded 3D electronics with bulk metal and polymer demonstrates significant potential for realizing the fabrication of free-form 3D electronics.
Dendritic phytic acid as a proton-conducting crosslinker for improved thermal stability and proton conductivity
There is growing interest in materials that exhibit enhanced proton conductivity at elevated temperatures without the need for humidification. Here, we develop a dendritic proton-conducting dopant for proton exchange membranes based on phytic acid (PhA) salts. PhA, which contains six phosphate groups capable of facilitating proton exchange, interacts with 4-dimethylaminopyridine (DMAP). DMAP serves as a strong electron donor, making it highly reactive with PhA. In this endeavor, cellulose sulfonic acid was selected as the base proton exchange membrane. Notably, the dimethylamino group of DMAP on the surface of DMAP-PhA acts as a basic site, enabling acid-base interactions with the sulfonic acid groups of cellulose sulfonic acid. As a result, DMAP-PhA functions as a proton-conducting crosslinker, significantly improving the thermal stability of the composites and increasing proton conductivity by enhancing the degree of proton dissociation at each interaction site.
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