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Greenhouse gas emissions present a significant challenge to humanity, and utilizing renewable electricity to convert emitted CO2 into value-added products offers a promising solution; however, traditional CO2 capture and regeneration processes remain energy-intensive, restricting the overall system efficiency and decarbonization efficacy. In this study, an advanced direct reduction of captured CO2 with large current densities for formate electrosynthesis was demonstrated without the need for CO2 regeneration or compression. The bismuth nanosheet (DRM-BiNS) was synthesized by direct reduction of a Bi-based MOF, representing a new class of catalytic materials with a large surface area and interconnected pores, suitable for the direct reduction of captured CO₂. By seamlessly combining experimentation and simulation, insights into the structure-parameter-performance relation were acquired in a flow cell setting, including critical membrane-electrode distance, cell orientation, and pumping flow rate. Important flow-cell components, such as catholyte volume, electrode substrate, membrane choice, and ionomer type, were also carefully examined to enhance the cell performance. In sharp contrast to prior studies limited to current densities below 20 mA/cm² in bicarbonate-based captured CO2 solutions, this work demonstrates a remarkable current density of 300 mA/cm² with an FE to formate comparable to the case with gas-fed CO2 reduction. Moreover, the process sustained an FE above 50% at a high current density of 500 mA/cm². The DRM-BiNS catalyst exhibited outstanding selectivity, activity, and stability, significantly outperforming oxide-derived bismuth nanosheets (OD-BiNS) in captured CO2 reduction. These findings offer critical insights into the development of sustainable and scalable CO2 utilization technologies. 

The topological Hall effect (THE), a quantum phenomenon arising from the emergent magnetic field generated by a topological spin texture, is a key method for detecting non-coplanar spin structures like skyrmions in magnetic materials. Here, we investigate a bilayer structure of Pt and the conducting ferrimagnet NiCo2O4 (NCO) of perpendicular magnetic anisotropy and demonstrate a giant THE across a temperature range of 2–350 K. The absence of THE in a single-layer Pt and NCO, as well as in Pt/Cu/NCO, suggests its interfacial origin. The maximum THE occurring just before the NCO coercive field indicates its connection to magnetic nucleation centers, which are topologically equivalent to skyrmions. The large normalized THE, based on the emergent-field model, points to a high population density of small magnetic nucleation centers. This aligns with the seemingly unresolvable domain structures by the employed techniques during magnetization reversal, even though clear domain structures are detected after zero-field cooling. These results establish heavy metal/NCO as a promising system for exploring topological spin structures. 

We utilize a combined computational-experimental approach to examine the influence of indium nanoparticle (NP) array distributions on deep-ultraviolet (UV) plasmon resonances. For photon energies < 5.7 eV, analysis of ellipsometric spectra reveals an increase in silicon reflectance induced by indium NP arrays on silicon. For various energies in the range 5.7–7.0 eV, a decrease in reflectance is induced by the NP arrays. Similar trends in reflectance are predicted from finite-difference time-domain (FDTD) simulations using NP size distributions extracted from atomic-force micrographs as input. In addition, in the energy range of 7.4–9.2 eV, the FDTD simulations reveal reflectance minima, characteristic of localized surface plasmon resonances. Electron energy-loss spectroscopy collected from individual indium NPs reveals the presence of LSPR at ≈ 8 eV, further supporting the promise of indium NP arrays on silicon for deep-UV plasmonics. 

Tellurium is a heavy chemical element exhibiting chirality, anisotropy, and strong spin-orbit coupling; conse quently, displaying a huge potential in quantum hardware technologies. In this article, tellurium quantum dots, with sizes around 19 ± 3 nm and energy bandgap around 2.4 eV, were successfully synthesized by pulsed laser ablation in liquids (PLAL). The synthesis was performed by using a nanosecond Nd:YAG laser emitting at 1064 nm and pulsing the laser beam at 1 kHz. Toluene (C6H5CH3) was used as a solvent to avoid oxidation of the dots. Non-polarized and polarized Raman spectroscopy as well as X-Ray diffraction were performed on the dots to study their quantum confinement and anisotropy. Finally, strongly confined tellurium quantum dots were obtained; and, their properties underline their potential as quantum light sources. 

Foraging strategies are shaped by interactions with the environment, and evolve under metabolic constraints. Optimal strategies for isolated and competing organisms have been studied extensively in the absence of evolution. Much less is understood about how metabolic constraints shape the evolution of an organism’s ability to detect and reach food. To address this question, we introduce a minimal agent-based model of the coevolution of two phenotypic attributes critical for successful foraging in crowded environments: movement speed and perceptual acuity. Under competition higher speed and acuity lead to better foraging success, but at higher metabolic cost. We derive the optimal foraging strategy for a single agent, and show that this strategy is no longer optimal for foragers in a group. We show that mutation and selection can lead to the coexistence of two strategies: A metabolically costly strategy with high acuity and velocity, and a metabolically cheap strategy. Generally, in evolving populations speed and acuity co-vary. Therefore, even under metabolic constraints, trade-offs between metabolically expensive traits are not guaranteed.