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Photoelectron imaging of substituted benzenes in aqueous aerosol droplets
Item type: Data Collection
Heitland, Jonas; Lee, Jong Chan; Abma, Grite Lolkje; et al. (2026)
Towards understanding electrolyte-dependant dynamics and kinetics of lithium deposition and stripping by operando neutron imaging
Item type: Journal Article
Winter, Eric; Carreon Ruiz, Eric Ricardo; Kondracki, Łukasz; et al. (2026)
Rechargeable lithium (Li) metal batteries, which use Li metal as the negative-electrode, promise energy densities that are two times higher than those achievable with conventional Li-ion batteries. However, the practical application of Li-metal batteries is currently constrained, and where the central challenge is dendritic Li growth, leading to cell failure. To overcome these limitations, electrolytes compatible with Li metal are required, where various electrolyte formulations have been proposed, but a mechanistic understanding of their effects to the kinetics and dynamics of Li deposition remains incomplete. Here, we introduce operando neutron imaging as a versatile modality for observing electrolyte-dependent Li-deposit nucleation, Li-metal plating and stripping behaviour with high temporal and spatial resolution. We tested three different carbonate electrolytes with varying concentrations of fluoroethylene carbonate (FEC) and found that low levels of the FEC additive contribute to better Li cycling reversibility, while higher concentrations lead to adverse effects, revealing an unexpected and critical limitation of FEC-additive application for improving Li-metal cycling. Our imaging methodology can be a starting point for much broader operando studies of the plating and stripping behaviour of Li metal in any electrolyte, potentially making it a key tool for future electrolyte developments.
Welfare and Cost Aggregation for Multi-Agent Control: When to Choose Which Social Cost Function, and Why?
Item type: Journal Article
Shilov, Ilia; Elokda, Ezzat; Hall, Sophie; et al. (2026)
Many multi-agent socio-technical systems rely on aggregating heterogeneous agents' costs into a social cost function (SCF) to coordinate resource allocation in domains such as energy grids, water allocation, or traffic management. The choice of SCF often entails implicit assumptions and may lead to undesirable outcomes if not rigorously justified. In this paper, we demonstrate that what determines which SCF ought to be used is the degree to which individual costs can be compared across agents and which axioms the aggregation shall fulfill. Drawing on the results from social choice theory, we provide guidance on how this process can be used in control applications. We demonstrate which assumptions about interpersonal utility comparability- ranging from ordinal level comparability to full cardinal comparability- together with a choice of desirable axioms, inform the selection of a correct SCF, be it the classical utilitarian sum, the Nash SCF, or maximin. Thus, fixing comparability level first, then choosing an objective from the compatible class, and reporting both as part of the specification, makes the fairness and efficiency consequences transparent. We demonstrate how the proposed framework can be applied for principled allocations of water, transportation, and energy resources.
Data for manuscript "Pupil‐based arousal self-regulation: Impact on physiological and affective responses to emotional stimuli"
Item type: Dataset
Imhof, Jenny; Raschle, Nora; Wenderoth, Nicole; et al. (2026)
A Comprehensive Analytical Approach to Introspect Efficient Miniaturized Circuit-Level Designs for Biomedical Signal Acquisition: A Tutorial Brief
Item type: Journal Article
Mohammad, Umar; Zhang, Ying; Zada, Muhammad; et al. (2026)
Health care technology is advancing rapidly, transforming diagnostics through compact, non-invasive, and user-friendly biomedical devices. For instance, diabetes diagnosis that once required significant blood volume can now be achieved in seconds using a nano-pinch sample. Recent developments in portable and wearable systems have minimized the need for invasive procedures, enabling continuous, real-time monitoring, especially among aging populations. This growing demand underscores the need for compact, energy-efficient, and affordable biomedical systems seamlessly integrated into daily life. This tutorial brief provides an in-depth analytical perspective on low-noise, low-cost, and low-power circuit-level design strategies for next-generation biomedical devices. Challenges and escape-out methods for low-noise design implementations are broadly discussed in this work. The study consolidates noise-reduction techniques, such as correlated double sampling and multi-stage amplifier configurations, and highlights their impact on signal integrity, power efficiency, and scalability. It also addresses design trade-offs and cost considerations, offering a practical framework for researchers developing efficient analog front-end architectures for wearable and implantable biomedical applications. Finally, the results presented in this work were carried out in Cadence Virtuoso using 65nm CMOS TSMC technology node.