Finchetto is hoping to launch a product within the next 18 months
Category: energy – Page 5
First absolute superconducting switch developed in a magnetic device
The University of Jyväskylä, Finland, has been involved as part of an international collaboration that has identified a way to completely suppress superconductivity in superconducting and ferromagnetic junctions. The results published in Nature Communications are key to the development of non-volatile superconducting random access memories and could enable more energy-efficient information and communication technologies.
Relativistic Motion Boosts Engine Efficiency Beyond Limits
The pursuit of more efficient engines continually pushes the boundaries of thermodynamics, and recent work demonstrates that relativistic effects may offer a surprising pathway to surpass conventional limits. Tanmoy Pandit from the Leibniz Institute of Hannover, along with Tanmoy Pandit from TU Berlin and Pritam Chattopadhyay from the Weizmann Institute of Science, and colleagues, investigate a novel thermal machine that harnesses the principles of relativity to achieve efficiencies beyond those dictated by the Carnot cycle. Their research reveals that by incorporating relativistic motion into the system, specifically through the reshaping of energy spectra via the Doppler effect, it becomes possible to extract useful work even without a temperature difference, effectively establishing relativistic motion as a valuable resource for energy conversion. This discovery not only challenges established thermodynamic boundaries, but also opens exciting possibilities for designing future technologies that leverage the fundamental principles of relativity to enhance performance.
The appendices detail the Lindblad superoperator used to describe the system’s dynamics and the transformation to a rotating frame to simplify the analysis. They show how relativistic motion affects the average number of quanta in the reservoir and the superoperators, and present the detailed derivation of the steady-state density matrix elements for the three-level heat engine, providing equations for power output and efficiency. The document describes the Monte Carlo method used to estimate the generalized Carnot-like efficiency bound in relativistic quantum thermal machines, providing pseudocode for implementation and explaining how the efficiency bound is extracted from efficiency and power pairs. Overall, this is an excellent supplementary material document that provides a comprehensive and detailed explanation of the theoretical framework, calculations, and numerical methods used in the research paper. The clear organization, detailed derivations, and well-explained physical concepts make it a valuable resource for anyone interested in relativistic quantum thermal machines.
Relativistic Motion Boosts Heat Engine Efficiency
Researchers have demonstrated that relativistic motion can function as a genuine thermodynamic resource, enabling a heat engine to surpass the conventional limits of efficiency. The team investigated a three-level maser, where thermal reservoirs are in constant relativistic motion relative to the working medium, using a model that accurately captures the effects of relativistic motion on energy transfer. The results reveal that the engine’s performance is not solely dictated by temperature differences, but is significantly influenced by the velocity of the thermal reservoirs. Specifically, the engine can operate with greater efficiency than predicted by the Carnot limit, due to the reshaping of the energy spectrum caused by relativistic motion.
Hydroxyl adsorption identified as key factor in electrocatalytic ammonia production
Compared with the energy-intensive Haber-Bosch process, renewable energy-driven electrocatalytic nitrate reduction reaction (NO3−RR) provides a low-carbon route for ammonia synthesis under mild conditions. Using nitrate from wastewater as the nitrogen source and water as the hydrogen source, this route has the potential to produce ammonia sustainably while mitigating water pollution.
Copper (Cu)-based catalysts show a good performance for NO3−RR to ammonia. However, they suffer from issues including high overpotential, competing nitrite (NO2–) formation, and low overall energy efficiency.
In a study published in ACS Catalysis, a team led by Prof. Bao Xinhe and Prof. Gao Dunfeng from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences, along with Prof. Wang Guoxiong from Fudan University, proposed hydroxyl (*OH) adsorption as a selectivity descriptor for ammonia synthesis via NO3−RR over Cu catalysts.
Overcoming disordered energy in light-matter interactions
Polaritons are formed by the strong coupling of light and matter. When they mix together, all the matter is excited simultaneously—referred to as delocalization. This delocalization has the unique ability to relay energy between matter that is otherwise not possible.
Disordered energy is ubiquitous in nature and the universe. Disordered energy is less organized and less available to do work, such as with heat dissipation. Even in plants, disorder can ruin effective energy transfer.
In the context of polaritons, as disorder increases, it can negatively affect light-matter interactions, including polariton-enabled energy transfers. Overcoming this disorder is an important topic across many scientific fields.
Breaking Barriers in Surface Chemistry: The autoSKZCAM Framework for Ionic Materials
Understanding and predicting chemical reactions on surfaces lies at the heart of modern materials science. From heterogeneous catalysis to energy storage and greenhouse gas sequestration, surface chemistry defines the efficiency and viability of advanced technologies. Yet, computationally modeling these processes with both accuracy and efficiency has been a grand challenge.
A recent study published in Nature Chemistry introduces a breakthrough: the autoSKZCAM framework, an automated and open-source method that applies correlated wavefunction theory (cWFT) to surfaces of ionic materials at costs comparable to density functional theory (DFT). This achievement not only bridges the accuracy gap but also enables routine, large-scale studies of surface processes with chemical accuracy.
