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This release links it to the Zenodo repository. 

This release links it to the Zenodo repository. 

When a gas is overvolted at or near atmospheric pressure, it results in a streamer discharge formation. Electrode geometries exert significant impact on the electrical breakdown of gases by altering the spatial profile of the electric field. In many applications the efficient generation of radicals is critical and is determined by the characteristics of the streamer discharge. We examine the effect of electrode geometry on the streamer characteristics and the production of radicals. This is performed for three different electrode geometries: plane–plane, pin–plane, and pin–pin. A two-dimensional rotationally symmetric fluid model is used for the streamer discharge simulation in the hydrogen/air gas mixture. The spatial profile of electron density and the electric field for point electrodes show significant differences when compared to plane electrodes. However, the efficiency of radical generation shows similar trends for the electrode configurations studied. We also present the results of spatial electrical energy density distribution which in turn determines spatial excited species distribution. These results can inform the design of specific applications. 

Abstract Autonomous robots are increasingly deployed for long-term information-gathering tasks, which pose two key challenges: planning informative trajectories in environments that evolve across space and time, and ensuring persistent operation under energy constraints. This paper presents a unified framework, , that addresses both challenges through adaptive ergodic search and energy-aware scheduling in multi-robot systems. Our contributions are two-fold: (1) we model real-world variability using stochastic spatiotemporal environments, where the underlying information evolves continuously over space and time under process noise. To guide exploration, we construct a target information spatial distribution (TISD) based on clarity, a metric that captures the decay of information in the absence of observations and highlights regions of high uncertainty; and (2) we introduce ( ), an online scheduling method that enables persistent operation by coordinating rechargeable robots sharing a single mobile charging station. Unlike prior work, our approach avoids reliance on preplanned schedules, static or dedicated charging stations, and simplified robot dynamics. Instead, the scheduler supports general nonlinear models, accounts for uncertainty in the estimated position of the charging station, and handles central node failures. The proposed framework is validated through real-world hardware experiments, and feasibility guarantees are provided under specific assumptions.[Code: https://github.com/kalebbennaveed/mEclares-main.git][Experiment Video: https://www.youtube.com/watch?v=dmaZDvxJgF8] 

Abstract Biochar is well-accepted as a viable climate mitigation strategy to promote agricultural and environmental benefits such as soil carbon sequestration and crop productivity while reducing greenhouse gas emissions. However, its effects on soil microbial biomass carbon (SMBC) in field experiments have not yet been thoroughly explored. In this study, we collected 539 paired globally published observations to study the impacts of biochar on SMBC under field experiments. Our results suggested an overall positive impact of biochar (21.31%) on SMBC, varying widely with different climate conditions, soil types, biochar properties, and management practices. Biochar application exhibits significant impacts under climates with mean annual temperature (MAT) < 15 °C and mean annual precipitation (MAP) between 500 and 1000 mm. Soils of coarse and fine texture, alkaline pH (SPH), soil total organic carbon (STC) content up to 10 g/kg, soil total nitrogen (STN) content up to 1.5 g/kg, and low soil cation exchange capacity (SCEC) content of < 5 cmol/kg received higher positive effects of biochar application on SMBC. Biochar produced from crop residue, specifically from cotton and maize residue, at pyrolysis temperature (BTM) of < 400 °C, with a pH (BPH) between 8 and 9, low application rate (BAP) of < 10 t/ha, and high ash content (BASH) > 400 g/kg resulted in an increase in SMBC. Low biochar total carbon (BTC) and high total nitrogen (BTN) positively affect the SMBC. Repeated application significantly increased the SMBC by 50.11%, and fresh biochar in the soil (≤ 6 months) enhanced SMBC compared to the single application and aged biochar. Biochar applied with nitrogen fertilizer (up to 300 kg/ha) and manure/compost showed significant improvements in SMBC, but co-application with straw resulted in a slight negative impact on the SMBC. The best-fit gradient boosting machines model, which had the lowest root mean square error, demonstrated the relative importance of various factors on biochar effectiveness: biochar, soil, climate, and nitrogen applications at 46.2%, 38.1%, 8.3%, and 7.4%, respectively. Soil clay proportion, BAP, nitrogen application, and MAT were the most critical variables for biochar impacts on SMBC. The results showed that biochar efficiency varies significantly in different climatic conditions, soil environments, field management practices, biochar properties, and feedstock types. Our meta-analysis of field experiments provides the first quantitative review of biochar impacts on SMBC, demonstrating its potential for rehabilitating nutrient-deprived soils and promoting sustainable land management. To improve the efficiency of biochar amendment, we call for long-term field experiments to measure SMBC across diverse agroecosystems. Graphical Abstract