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Electrochemical Strain Microscopy (ESM) is widely used to probe nanoscale ion dynamics in battery materials, particularly at grain boundaries, where ionic transport is often proposed to be localized. However, interpretation of ESM signals remains challenging because topography-induced artifacts can artificially enhance the measured response. Here, topographic crosstalk arising from contact stiffness variation induced by feedback-loop delay is quantitatively analyzed in Dual AC Resonance Tracking (DART)-ESM using ionically inactive single-crystal silicon as a reference material. Artificial trench structures are introduced to emulate grain-boundary-like topography commonly encountered in battery electrodes and solid electrolytes. Simple harmonic oscillator (SHO) analysis of contact-resonance dynamics shows that ESM amplitude enhancement can arise from contact stiffness variations independent of ionic motion. These silicon-based measurements provide a practical reference for identifying topographic crosstalk and estimating its magnitude. Reproducibility is confirmed across multiple silicon calibration samples and further validated in practical battery materials, including a graphite anode and a Na2Zn2TeO6 (NZTO) solid electrolyte, indicating that such artifacts are inherent to DART-ESM under practical measurement conditions. Cooling Cross-Section Polishing (CCP) effectively suppresses these artifacts by reducing surface roughness and stabilizing contact resonance. These results provide a practical framework for reliable interpretation of nanoscale electrochemical activity in battery materials.

Characteristic gas-based detection technology can facilitate the warning of lithium-ion battery thermal runaway with a high accuracy at an early stage. Microelectromechanical system (MEMS) metal-oxide-semiconductor (MOS) gas sensors have advantages of a low cost, a high accuracy, and low power consumption; therefore, they are ideal candidates for the lithium-ion battery thermal-runaway warning. MEMS MOS gas sensors are composed of a micro-hotplate and gas-sensitive materials. The micro-hotplate component strongly influences the device's mechanical and thermal properties. Initially, we used COMSOL to optimize the micro-hotplate component. Then, we fabricated the device based on the optimal micro-hotplate. Next, gas-sensitive materials made of ZnO and ZnO-Au were deposited on the micro-hotplate by radio-frequency magnetic sputtering. The self-made and commercial MEMS MOS sensors were integrated to form an electronic nose. The as-made electronic nose can classify hydrogen, ethylene, acetylene, methane, carbon monoxide, and ethanol with a maximum accuracy of 99.4% using gas response data acquired over only 20 s. The reported work can provide a solution for an early and accurate lithium-ion battery thermal runaway warning.

Cell inconsistency is an inherent challenge for lithium-ion batteries during long-term operation, necessitating the use of battery equalization systems (BESs). In such systems, real-time data communication is essential for ensuring accurate system coordination and effective equalization performance. This paper proposes a distributed BES based on the talkative power converter (TPC) technique, employing a bidirectional flyback converter as the core equalization unit. In the proposed approach, the converter not only transfers energy among distributed battery modules but also modulates data signals for communication. This dual-function design eliminates the need for additional communication hardware or dedicated signal transmission circuits, thereby reducing the overall system complexity. On this basis, a distributed equalization system and its communication channel model are developed. The system noise sources are then analyzed and a noise suppression strategy is proposed to improve the communication reliability. Furthermore, a practical communication protocol tailored to the distributed architecture is designed. Finally, a hardware prototype is constructed and tested, achieving real-time data communication at a rate of 8.33 kb/s. The results verify the feasibility of using switching-ripple-based power and signal dual modulation for communication within distributed BESs.

Injectable bioelectronics offer a minimally invasive approach to peripheral nerve stimulation but remain limited by onboard energy storage and fragile leads. Here, we present SEED, a leadless, battery-free bioelectronic interface engineered for percutaneous delivery through a standard 14-gauge needle. SEED (Stimulating Electrode for Electroceutical Delivery) operates in the magnetoquasistatic regime using low-frequency (65 kilohertz) resonant inductive coupling, externalizing waveform generation and control, enabling programmable neuromodulation without onboard active electronics. A spiral-helix electrode geometry promotes longitudinal nerve engagement while limiting off-target field spread. Benchtop and ex vivo characterization demonstrates precise, programmable control of stimulation frequency, pulse width, and amplitude under physiologically relevant conditions. In vivo validation in a rat sciatic nerve model confirms frequency-locked motor responses and graded neural recruitment following percutaneous deployment. SEED exhibits strong radiopacity and acoustic contrast, supporting compatibility with ultrasound and computed tomography for image-guided neuromodulation. This platform provides a scalable pathway toward minimally invasive bioelectronic therapies.

SiOx anodes are highly promising for next-generation lithium-ion batteries due to their superior theoretical capacity. However, issues such as drastic volume expansion and low initial Coulombic efficiency (ICE) impede their practical use. While macroporous architectures can mitigate these challenges, traditional fabrication often depends on tedious hard templating methods and significant organic solvent consumption. In this work, we report a sustainable, emulsion-self-templated and organic solvent-free strategy to synthesize a carbon-coated 3D macroporous SiOx/C composite (3DM-SiOx/C@C). Our approach uniquely integrates radical polymerization with a water-in-oil emulsion and sol-gel process, followed by chemical vapor deposition (CVD). The 3D macroporous framework is generated via in-situ emulsion droplets acting as self-templates, effectively eliminating the need for external sacrificial templates and toxic etchants. Notably, this organic solvent-free process achieves an exceptional precursor to (precursor + organic solvent) mass ratio of 1.0, contrasting sharply with conventional methods (0.0044-0.17). The resulting hierarchical structure, characterized by interconnected macropores and a uniform carbon coating, significantly enhances structural integrity and electronic conductivity. Electrochemical evaluations reveal that 3DM-SiOx/C@C exhibits an improved ICE of 74.32% and long-term cycling stability even at a high current density of 1.0 A g-1 compared to non-porous and uncoated counterparts. This integrated synthesis offers a green and scalable pathway for developing high-performance silicon-based anodes for large-scale energy storage.

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Photovoltaic (PV)-storage systems operating in weak grids are affected by high grid impedance, transient voltage disturbances, and measurement noise, which can degrade frequency regulation, increase converter current stress, and impose high-frequency current fluctuations on the battery. To address these issues, this paper proposes a multi-timescale transient-state sensing and signal-processing framework for grid-forming PV-hybrid storage systems. The proposed framework combines three coordinated functions. First, a frequency-domain HESS power-decoupling mechanism separates high-frequency transient power components and assigns them to the supercapacitor, while the battery mainly handles low-frequency energy variations. Second, a voltage-deviation-driven adaptive virtual inductance is introduced to increase the equivalent output impedance during voltage-sag events and reduce transient inrush current. Third, a noise-resilient frequency sensing strategy based on a filtered frequency derivative and a dead-band for false-trigger suppression is developed to reduce noise-induced false triggering in adaptive inertia and damping control. Comparative simulations indicate that under the tested weak-grid conditions, the proposed method reduces the transient inrush-current peak by 53.2%, decreases the maximum dynamic frequency deviation by approximately 75%, and improves the active-power regulation speed by more than 50%. These results indicate that the proposed sensing-oriented framework can improve transient response while reducing converter and battery current stress in PV-storage systems connected to high-impedance grids.

This work presents the realization of a compact and embedded impedance-based sensor system for the characterization of lithium-ion batteries by means of electrical impedance spectroscopy (EIS). The analog magnitude-ratio and phase-difference detection (MRPDD) method is implemented and extended through a generalized formulation that models the shunt element as a frequency-dependent impedance and compensates the parasitic contributions of the printed circuit board. This reformulation corrects magnitude and phase errors introduced by the measurement hardware without increasing the overall complexity. The prototype comprises two main functional blocks: current-mode excitation and voltage-mode measurement. The excitation stage uses an operational transconductance amplifier and a power MOSFET to generate a voltage-controlled current source, whereas the sinusoidal voltage signal is generated by means of a direct digital synthesizer. The measurement chain relies on differential acquisition using instrumentation amplifiers and analog magnitude/phase detection based on the AD8302 vector detector under microcontroller control. The proposed method has been first validated by simulations using both a linear RC equivalent model and an extended Randles-type battery-equivalent model, and then experimentally characterized using a linear RC equivalent model of the device under test. Measurements show that the generalized formulation recovers the ideal impedance response in the presence of parasitic effects, both in the shunt device and in the printed circuit board. In the experimental validation with the RC model, a magnitude error of 1.65% is obtained at 1 kHz, which is adopted as the upper frequency limit for battery characterization, even though operation up to 10 kHz is possible. Phase measurements revealed that the input capacitive coupling of the vector detector, conceived for operation in the RF range, requires an adaptation for appropriate operation in the intended frequency range. The prototype has been also applied to the characterization of a commercial lithium-ion 18650 cell, enabling the measurement of battery impedance and the analysis of its dependence on the state-of-charge and on the discharge current.

Wireless sensor networks (WSNs) deployed for seismic monitoring must sustain long-term operation under strict energy constraints, where premature node failure degrades spatial coverage and detection reliability. This paper presents a safety-constrained reinforcement learning framework for transmission scheduling in energy-harvesting seismic WSNs. The proposed approach integrates Proximal Policy Optimisation (PPO) with action masking and a runtime guard-layer safety filter that enforces battery-preservation and load-balancing constraints without retraining. The guard layer intercepts policy actions and substitutes safe alternatives when constraint violations are detected, using a scoring function that combines battery headroom with network-wide load equity. Experiments across three network scales (10, 15, and 30 nodes) with solar energy harvesting demonstrate that the guard-enhanced PPO achieves 99.46% transmission success at 30 nodes while maintaining 66.47% node survival-a 58.3% improvement in survival over the highest-reward baseline (Closest) at the cost of only a 6.2% reduction in cumulative reward. Crucially, the guard-enhanced policy outperforms the unconstrained PPO baseline simultaneously on cumulative reward (+11.4%), transmission success (+0.8 pp), and node survival (+15.4%), demonstrating that hard safety constraints, when properly aligned with the system's energy model, provide both performance and safety gains rather than a fundamental trade-off. Sensitivity analysis across event rates (pevent=0.5 and 0.9) confirms that the guard layer's advantage persists under both moderate and extreme monitoring conditions. Analysis across scales reveals distinct operational regimes: at 10 nodes, heuristic baselines are near-optimal; at 30 nodes, learned policies dominate, and safety filtering becomes critical for sustained operation.

Variability in poststroke language outcomes remains insufficiently explained by established clinical system neuroscience concepts. This study examined whether damage to neurotransmitter-informed structural networks is associated with poststroke language impairment. Two openly available cohorts of patients with left-hemispheric stroke were analyzed: the Washington Stroke Cohort (St. Louis), including patients after a first symptomatic stroke (acute phase), and the Aphasia Recovery Cohort (South Carolina), focusing on chronic recovery. Language performance was assessed cross-sectionally using either a comprehensive language battery (Washington Stroke Cohort; 1-2 weeks poststroke) or the Western Aphasia Battery-Revised (Aphasia Recovery Cohort; chronic stage). Individual stroke lesion masks were embedded into normative connectomes weighted by positron-emission tomography-derived density maps of 16 neurotransmitter receptors/transporters. Partial least squares regression and adjusted linear regressions (age, sex, lesion volume, and time poststroke) identified predictors of language functioning. Two hundred seventy patients were included. Washington Stroke Cohort (n=44): mean age, 54.2&#xb1;12.3 years; 45.5% female; median, 12 days poststroke (interquartile range, 10-14). Aphasia Recovery Cohort (n=226): mean age, 57.8&#xb1;11.2 years; 38.4% female; and median, 721 days poststroke (interquartile range, 403-1765). Across both cohorts, partial least squares analyses converged on a neurochemical profile in which damage to networks related to serotonergic (5-HT1a and 5-HT2a) and dopaminergic (D1) receptor distributions showed the strongest associations with poorer language performance. Damage to 5-HT1a and D1 networks remained significant in fully adjusted models, improving fit over covariate-only models (all PFDR<0.001; Washington Stroke Cohort: &#x2206;AIC5-HT1a=1.77 and &#x2206;AICD1=0.96; Aphasia Recovery Cohort: &#x2206;AIC5-HT1a=25.29 and &#x2206;AICD1=19.96). The disruption of large-scale serotonergic (5-HT1a) and dopaminergic (D1) networks is associated with language impairment in acute to subacute and chronic stroke. Neurotransmitter-related network damage, based on normative positron-emission tomography-derived maps serving as a structural proxy of neurotransmitter systems, explained additional variability beyond clinical variables and lesion burden, providing a neurochemically informed network framework for understanding variability in poststroke aphasia. However, given the indirect nature of the measures, implications for clinical translation and targeted rehabilitation strategies remain preliminary.

Objective Cognitive impairment is a major non-motor manifestation of Parkinson's disease (PD), and mood disorders, including depression and anxiety, are increasingly recognized as potentially modifiable contributors to cognitive decline. However, studies simultaneously evaluating the individual and combined effects of depression and anxiety on specific cognitive domains in PD remain limited. Methods One hundred forty-nine patients with early-to-mid-stage PD were stratified by depression (BDI &#x2265; 14) and anxiety (BAI &#x2265; 8) status. Cognitive performance was evaluated using the Seoul Neuropsychological Screening Battery (SNSB). Group differences were analyzed using ANCOVA, adjusting for education, H-Y stage, and MDS-UPDRS motor scores, followed by Bonferroni correction for multiple testing. Results After adjustment for covariates, depression was associated with impaired verbal recognition memory (p = 0.009), although this did not survive Bonferroni correction. Conversely, anxiety-related deficits immediate visual recall (p = 0.006) and inhibitory executive control (p = 0.016) remained robustly significant even after rigorous correction. Patients with comorbid depression and anxiety exhibited the most pervasive cognitive impairment, including statistically resilient deficits in both visual memory and frontal executive function (all adjusted p < 0.05). Conclusion Depression and anxiety exert distinct yet additive detrimental effects on cognition in early PD. While anxiety and comorbid symptoms show robust associations with visuospatial and executive deficits, the impact of isolated depression appears less statistically stable under conservative thresholds. These findings underscore the importance of early neuropsychiatric screening and targeted intervention, which may be associated with the maintenance of cognitive health in PD.

Studies have documented overheating, fire and explosion (OFE) incidents related to the use of lithium-ion batteries in electronic nicotine delivery systems (ENDS). These incidents can lead to property damage, injuries and even death. Most incidents are not reported to the US Food and Drug Administration, and those that are reported frequently lack sufficient information to convey the acute risks and pinpoint mitigation strategies. A convenience sample of 6010 adults who used ENDS completed a self-administered online survey about their ENDS device and battery, use behaviours and any experience of OFE incidents. The data were calibrated to estimate population-level statistics for US adults who use ENDS. Approximately half the respondents reported experiencing an OFE incident. About one-third reported having experienced a serious OFE incident (ie, overheating that caused visible damage to the device/battery, other property damage or burns; fire; explosion). A total of 4.8% of respondents who used ENDS reported that they or someone else had experienced an injury because of a serious OFE incident, and 1.1% reported that medical care was required. Given the prevalence of OFE incidents and potential risk factors, our findings suggest incidents are underreported and reporting systems could capture them in greater detail. Complete information on the device characteristics, use behaviours and outcomes associated with incidents may inform preventive actions by individuals, public education and regulatory activities.

This study examined long-term neuromuscular and multidirectional speed development in elite youth badminton players and evaluated whether developmental stage influences adaptation trajectories during systematic training. Thirty athletes were monitored over 16 months with repeated assessments at five time points and stratified into Younger (8-14 years) and Older (15-22 years) developmental groups. A comprehensive test battery assessed explosive strength, reactive strength, musculotendinous stiffness, and badminton-specific multidirectional speed. Data acquisition was performed using a multi-sensor approach, including force-platform-based jump analysis, accelerometry-based systems, and electronic timing gates, enabling the objective, high-resolution, and repeatable monitoring of neuromuscular performance. Significant time effects were observed across all sensor-derived performance variables (p < 0.001), indicating robust improvements in speed, power, and neuromuscular efficiency. Adaptation trajectories were predominantly linear, with no evidence of performance plateauing. Although older athletes maintained higher absolute performance levels, Time &#xd7; Group interactions were largely absent, demonstrating parallel improvement rates across developmental stages rather than a catch-up effect in younger players. Linear mixed models confirmed equivalent improvement slopes despite baseline differences, and adjustment for body mass attenuated but did not eliminate age-group differences in jump performance. Exploratory analyses revealed substantial inter-individual variability, identifying responder phenotypes independent of age. These findings indicate that systematically progressed training supports sustained, linear neuromuscular adaptation across youth badminton development and highlight the importance of long-term, individualized monitoring over age-based expectations of accelerated responsiveness.

Calcium metal batteries represent a promising frontier for high-energy-density energy storage, yet their practical application is hindered by sluggish kinetics and unstable electrolyte-metal interfaces. Here, we report an electrolyte design strategy based on an asymmetric solvation effect by a hybrid Ca2+/Na+ organoborate electrolyte that simultaneously regulates solvation chemistry and interphase formation. By introducing monovalent co-cations and strongly coordinating tetra(3,3,3-trifluoropropoxy)borate anion, an asymmetric solvation structure is constructed in which electrochemically active Ca2+ occupies an off-center position. This configuration significantly breaks the centrosymmetry of the Ca2+ solvation sheath, leading to an intensified dipole moment and a disruption of the uniform electrostatic shielding, which selectively activates the Ca2+ for efficient desolvation. Consequently, dense Ca deposition (>10&#xa0;mA h cm-2) is achieved with low overpotential, high reversibility (&#x223c;95%), and long-term stability. Interfacial analysis reveals that the asymmetric solvation environment drives preferential anion decomposition, yielding a polymeric-polycrystalline interphase composed of CaH2/CaO and boron-containing polymeric ether species that effectively protects the Ca anode. When paired with cathodes under a restricted negative-to-positive ratio of 7.2, the Ca/Na/Btfp electrolyte enables stable full-cell operation to exceed 57 cycles. This strategy is also transferable to Mg metal battery, highlighting its potential as a general electrolyte design principle for multivalent metal batteries.

In modern society, non-physical social factors, such as the mere presence of others, significantly influence mental and physical health; however, the underlying biological mechanisms remain poorly understood. This study investigated the impact of non-physical social stimuli on behavioral and physiological states using an "adjacent housing" model that excludes direct physical contact. Here, 'stress-like phenotype' refers specifically to behavioral and physiological alterations-such as suppressed body weight gain and increased locomotor activity-that partially overlap with those reported in established rodent stress models, in the absence of direct physiological corroboration. Male C57BL/6N mice were housed for three weeks adjacent to cages containing either a single male ICR mouse (Experiment 1) or a single male C57BL/6N mouse (Experiment 2). The control group was housed adjacent to a cage of group-housed C57BL/6N mice. Following the exposure period, body weight, weight gain rate, grip strength, and thermal nociception were measured. A comprehensive behavioral battery was also conducted, including the light/dark transition, open field, social interaction, social avoidance, tail suspension, and forced swim tests. In Experiment 1, mice housed adjacent to an ICR neighbor exhibited a significant reduction in body weight and weight gain rate compared to the control group. Furthermore, these mice showed a significant increase in total distance traveled during the open field and social interaction tests, suggesting altered locomotor or exploratory activity. However, no significant changes were observed in grip strength, thermal nociception, social avoidance, or depressive-like behaviors. In Experiment 2, no significant physiological or behavioral alterations were detected across any of the measured parameters. These findings demonstrate that the presence of a neighboring individual can influence the physiological and behavioral profiles of mice in a strain-dependent manner, even in the absence of physical contact. This study highlights the biological impact of non-contact social environments and underscores the critical importance of housing configurations in shaping behavioral phenotypes in laboratory animals.

Sleep-dependent memory consolidation (SDMC), the process by which sleep supports the transfer of memories into long-term storage, declines with age but remains underexplored in older adults with subjective cognitive decline and mild cognitive impairment. Traditional SDMC assessments are typically conducted in lab settings, with limited evidence for feasibility to do these assessments at home for this clinical population. To address this, we co-designed the Sleep Memories app, which assesses overnight memory for a previously validated 32-item word-pairs task. This pilot study first explored the feasibility and acceptability of the app, including willingness to participate. Second, we explored various demographic, clinical, and subjective sleep factors associated with task completion and SDMC performance in a memory clinic sample. Within an 8-month period, we invited 141 older adults aged 50 years and above (mean 71.27, SD 7.51 y) from the Healthy Brain Ageing clinic, a specialist brain health and memory clinic in Sydney, to pilot the Sleep Memories app. Of these, 76 (mean 70.19, SD 7.75) agreed to participate. All participants underwent a full neuropsychological test battery, medical assessment, and mood assessment. Sixty-eight participants completed at least 1 test of the word-pairs task. The word-pairs task completion rate for all trials was over 50%. There was 57% (39/68) completion of both evening and morning delayed recall tests. Lower willingness to participate was associated with lower global cognitive scores, poorer sleep behavior, and clinical factors. Higher task completion was associated with greater education and greater anxiety levels. User feedback indicated that the app was well-accepted and liked, although some participants reported minor technical difficulties. These findings support the feasibility of mobile app-based SDMC assessment in older adults at risk of cognitive decline and underscore the importance of considering individual characteristics (eg, subjective sleep factors, clinical characteristics, and education) when designing digital SDMC tools.

Patient-reported outcome measures (PROMs) are commonly used to monitor lower urinary tract symptoms attributed to benign prostatic hyperplasia (LUTS/BPH). However, there is limited evidence on patients' perspectives on integrating PROMs into clinical practice and on best practices to improve their implementation to better meet patient needs. The aim of this study is to explore patients' experiences completing PROMs during routine BPH management, and to develop patient-informed strategies for PROM implementation in urologic care. Virtual semi-structured telephone interviews were conducted with English-speaking patients aged 50 years or older with BPH who attended outpatient urology clinics between May and October 2025. Patients were purposively sampled based on the type of treatment received (medical or surgical). Interview data were analyzed using interpretive description. Themes were synthesized inductively, and practical implementation strategies were developed from participants' suggestions. Twenty patients participated (12 received medical treatment and 8 received surgical treatment). Four themes emerged regarding patient perspectives on PROM use in routine care: (1) Perceived benefits-patients viewed PROMs as valuable tools for tracking symptom progression, prompting self-reflection, and facilitating communication among the clinical care team; (2) Questionnaire content-patients questioned the relevance of specific domains, particularly the non-specificity of the PROMIS pain scales as well as mental health, and sexual health items; (3) Perceived barriers-participants criticized the excessive volume of questionnaires; and (4) Considerations for PROM Integration-participants emphasized the importance of visible follow-up actions based on PROM results. Practical recommendations for PROM integration in routine clinical practice included: (1) enhancing patient understanding of PROMs by providing a brief rationale prior to survey administration; (2) implementing a patient-preference PROM workflow in the electronic health record (EHR); and (3) providing tangible actions based on PROM results, such as summarizing scores in plain language and incorporating results into discussions during visits. This study provides patient-informed insights into the implementation of a broad PROM battery in LUTS/BPH care. Participants emphasized that PROMs are more acceptable when their purpose is clearly explained and when responses are visibly discussed or acted upon in care. Future research should examine how these patient-informed strategies can be operationalized within clinical workflows and integrated with clinician, administrator, and EHR perspectives to support sustainable PROM use in routine practice.

Older patients with heart failure (HF) often present with multiple age-related conditions, but these are commonly evaluated in isolation. We aimed to describe the prevalence, overlap, and prognostic implications of physical dysfunction, cachexia, and dysphagia in older patients with HF. We conducted a single-center retrospective study enrolling hospitalized patients with HF aged &#x2265;65 years who were ambulatory at discharge. Complications at discharge were defined as follows: physical dysfunction was defined as a Short Physical Performance Battery score &#x2264;9, cachexia according to the Asian Cachexia Working Group, and dysphagia as a Food Intake Level Scale score &#x2264;8. Patients were categorized by the number of complications (0-3). The outcome was 1-year all-cause mortality. Among 468 patients (median age 81 years; 43.2% female), physical dysfunction, cachexia, and dysphagia were identified in 50.2%, 43.2%, and 19.4% of patients, respectively. The proportion of patients with 0, 1, 2, and 3 complications was 33.4%, 30.1%, 26.9%, and 9.6%, respectively. In Cox regression analysis, a higher number of complications was associated with higher mortality (hazard ratio 1.97; 95% confidence interval 1.35-2.87; P<0.001). Adding the number of complications to a pre-existing risk model increased the area under the curve from 0.684 to 0.779 (P<0.001). Concurrent assessment of physical function, cachexia, and dysphagia provides incremental prognostic information beyond established risk predictors in older patients with HF.

Experimental validation delivers five quantified outcomes. First, optical pheromone detection achieves 88.7% &#xb1; 0.6% accuracy (n = 150, 95% CI), and the dual-modality combined channel achieves 86.1% &#xb1; 0.9% (n = 200), with robustness confirmed under 50/60 Hz flicker interference, rapid 200-1200 lux light transitions (485 ms settling), and reflective glare spots. Second, the MQ-135 chemical channel calibration holds R2 &#x2265; 0.999 across temperatures of 15-35 &#xb0;C and humidity of 30-90%, with maximum voltage drift of 0.093 V at the highest temperature. Third, 3.2&#xd7; CNN inference speedup through 8-bit quantisation runs at 15 FPS within 1.8 W. Fourth, peripheral subsystems draw a measured mean of 1.19 W &#xb1; 0.02 W (n = 60, 95% CI); the complete per-robot system, including the Jetson Orin Nano compute rail, draws 6.15 W &#xb1; 0.09 W, enabling six-hour missions from the 55.08 Wh battery. Fifth, localisation across ten trials yields the mean position error 0.074 m and RMSE 0.081 m with 97.5% map coverage; physical multi-robot tests with 5-8 robots confirm map convergence times of 120-210 steps with collision rates below 0.042 per robot per step. To the best of our knowledge, no prior physical swarm platform has simultaneously demonstrated this combination of capabilities under comparable constraints.

The development of high-performance cathode materials represents a crucial strategy for enhancing the overall electrochemical performance of aqueous alkaline zinc batteries. The rational design of electrode microstructure and chemical composition can synergistically boost the electrochemical reaction activity, ion/electron transport kinetics, and structural stability. In this work, a composite cathode material, FLG@NixS6/Co4S3/Ni-Co(OH)2, was successfully synthesized via an electrochemical codeposition method. The engineered architecture offers abundant electrochemically active sites, well-defined ion diffusion pathways, and continuous electron conduction networks. Moreover, the strong interaction among the constituent phases effectively regulates and accelerates the redox reaction kinetics. When integrated into an aqueous alkaline zinc battery, the device attains a high specific capacity of 385 mAh g-1 at 2 A g-1, excellent rate capability (287 mAh g-1 at 80 A g-1), a gravimetric energy density of 590 Wh kg-1, a power density of 128.57 kW kg-1, and remarkable cycling stability, with 100% capacity retention maintained after 20,000 cycles. Overall, this study proposes a scalable and rational composite strategy for designing high-performance electrode materials for next-generation electrochemical energy storage systems.