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Curvature-Specific Coupling Electrode Design for a Stretchable Three-Dimensional Inorganic Piezoelectric Nanogenerator
Get PDFStructures such as 3D buckling have been widely used to impart stretchability to devices. However, these structures have limitations when applied to piezoelectric devices due to the uneven distribution of internal strain during deformation. When strains with opposite directions simultaneously affect piezoelectric materials, the electric output can decrease due to cancellation. Here, we report an electrode design tailored to the direction of strain and a circuit configuration that prevents electric output cancellation. These designs not only provide stretchability to piezoelectric nanogenerators (PENGs) but also effectively minimize electric output loss, achieving stretchable PENGs with minimal energy loss. These improvements were demonstrated using an inorganic piezoelectric material (PZT thin film) with a high piezoelectric coefficient, achieving a substantial maximum output power of 8.34 mW/cm3. Theoretical modeling of the coupling between mechanical and electrical properties demonstrates the dynamics of energy harvesting, emphasizing the electrode design. In vitro and in vivo experiments validate the device’s effectiveness in biomechanical energy harvesting. These results represent a significant advancement in stretchable PENGs, offering robust and efficient solutions for wearable electronics and biomedical devices. © 2024 The Authors. Published by American Chemical Society.TRUEsciescopu
Engineering self-healable and biodegradable ionic polyurethane with highly tribopositive behavior
No full textAccording to the development of human-oriented technology, triboelectric nanogenerators (TENGs) present great potential as a power source for self-powered sensors and wearable devices. Advanced next-generation TENGs require not only durability and stable production of electrical energy but also the ability to autonomously self-heal after mechanical damage and biodegradability. Here we report a self-healable, biodegradable, and high performance TENG using engineered ionic polyurethane (IPU). We utilized polycaprolactone-based PU to provide biodegradable properties and introduced imidazolium ionic liquids diol (IL) to facilitate self-healing through ion-dipole interaction. Imidazolium ionic liquid diol also improves triboelectric properties and improves capacitance by forming an electric double layer (EDL), contributing to improved output. These results suggest a high-performance TENG design methodology that can be applied to next-generation soft electronic devices. © 2024 Elsevier LtdFALSEsciescopu
Continuous tremor monitoring in Parkinson’s disease: A wristwatch-inspired triboelectric sensor approach
Get PDFParkinson's disease (PD) prevalence is projected to reach 12 million by 2040. Wearable sensors offer a promising approach for comfortable, continuous tremor monitoring to optimize treatment strategies. Here, we present a wristwatch-like triboelectric sensor (WW-TES) inspired by automatic watches for unobtrusive PD tremor assessment. The WW-TES utilizes a free-standing design with a surface-modified polytetrafluoroethylene (PTFE) film and a stainless-steel rotor within a biocompatible polylactic acid (PLA) package. Electrode distance is optimized to maximize the output signal. We propose and discuss the WW-TES working mechanism. The final design is validated for activities of daily living (ADLs), with varying signal amplitudes corresponding to tremor severity levels (“normal” to “severe”) based on MDS-UPDRS tremor frequency. Wavelet packet transform (WPT) is employed for signal analysis during ADLs. The WW-TES demonstrates the potential for continuous tremor monitoring, offering an accurate screening of severity and comfortable, unobtrusive wearability. © 2024 The Author(s)TRUEsciescopu
A Hybrid Recording System with 10kHz-BW 630mVPP84.6dB-SNDR 173.3dB-FOMSNDRand 5kHz-BW 114dB-DR for Simultaneous ExG and Biocurrent Acquisition
No full textAs the precise acquisition of continuous ExG (ENG, ECG, etc.) and biocurrent (chemical, PPG, etc.) signals provides further insights into chronic health conditions [1,2], a lowpower readout system capable of simultaneously recording ExG and biocurrent signals with high precision is beneficial (Fig. 33.11.1(a)). Such a system requires BW>5kHz, noise floor ~100nV/√Hz, and FOMSNDR>170dB to cover the entire ExG spectrum. Also, an input range (IR)>100mVPP is necessary to prevent saturation. Likewise, for biocurrent acquisition, a system has to meet BW>1kHz, noise floor ~1pArms/√Hz, and DR>100dB to detect small charge perturbations without saturation from large baseline currents. Extensive effort has been conducted to design a simultaneous V & I monitoring system (Fig. 33.11.1(b)). For instance, [1] allows the design of a simultaneous V & I monitoring system based on simple integration of individual readout schemes. However, this system consumes power >100μW and is unsuitable for simultaneous ExG and biocurrent signals due to the limited BW. Although [2] achieves wide BW for both signals, it cannot record V & I simultaneously due to the time-division manner and also has narrow IRs. On the other hand, [3] employing frequency division, achieves simultaneous readout while consuming low power. However, it is vulnerable to artifacts, while the BW of each V & I readout limits the other. This paper presents a simultaneous V & I recording system using a single 2nd-order continuous-time ΔΣ modulator (CT-DSM). Such simultaneous recording is achieved by using a highly linear hybrid GmC integrator with a triplet VCObased quantizer, where the differential voltage and single-ended current are combined into differential and common mode signals (Fig. 33.11.1 (c)). © 2024 IEEE
Constraints on the subsecond modulation of striatal dynamics by physiological dopamine signaling
No full textDopaminergic neurons play a crucial role in associative learning, but their capacity to regulate behavior on subsecond timescales remains debated. It is thought that dopaminergic neurons drive certain behaviors by rapidly modulating striatal spiking activity; however, a view has emerged that only artificially high (that is, supra-physiological) dopamine signals alter behavior on fast timescales. This raises the possibility that moment-to-moment striatal spiking activity is not strongly shaped by dopamine signals in the physiological range. To test this, we transiently altered dopamine levels while monitoring spiking responses in the ventral striatum of behaving mice. These manipulations led to only weak changes in striatal activity, except when dopamine release exceeded reward-matched levels. These findings suggest that dopaminergic neurons normally play a minor role in the subsecond modulation of striatal dynamics in relation to other inputs and demonstrate the importance of discerning dopaminergic neuron contributions to brain function under physiological and potentially nonphysiological conditions. © The Author(s), under exclusive licence to Springer Nature America, Inc. 2024.FALSEsciescopu
Self-Powered Pyroelectric Warmth Sensor for Robotic Integration and Materials Recognition
No full textThis work presents the self-powered warmth sensor based on the pyroelectric effect. Pyroelectric materials are generally used for energy harvesting and temperature sensing. For the first time, we showcase warmth sensing using the pyroelectric effect. The pyroelectric tactile sensor comprises a lead zirconate titanate (PZT) attached to a Peltier heater. When the heated pyro-sensor contacts a cooler object, there is an instant drop in sensor temperature due to the conduction heat loss. Such temperature drop generates pyroelectric current, and different materials produce distinguishable outputs, as the temperature change depends on the heat transfer rate. As a result, direct sensing of warmth depends on not only the temperature but also the thermal properties of the object and distinguishing different materials using the pyro-sensor integrated robotic gripper. © 2024 IEEE
Antibacterial Immunonegative Coating with Biocompatible Materials on a Nanostructured Titanium Plate for Orthopedic Bone Fracture Surgery
Get PDFPeriprosthetic infections resulting from bacterial biofilm formation following surgical bone fracture fixation present important clinical challenges. Conventional orthopedic implant materials, such as titanium, are prone to biofilm formation. This study introduces a novel surface for orthopedic titanium plates, optimized for clinical application in human bone fractures. Leveraging nanostructure-based surface coating technology, the plate achieves an antibacterial/immunonegative surface using biocompatible materials, including poloxamer 407, epigallocatechin gallate, and octanoic acid. These materials demonstrate high biocompatibility and thermal stability after autoclaving. The developed plate, named antibacterial immunonegative surface, releases antibacterial agents and prevents adhesion between human tissue and metal surfaces. Antibacterial immunonegative surface plates exhibit low cell toxicity, robust antibacterial effects against pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa, high resistance to biofilm formation on the implant surface and surrounding tissues, and minimal immune reaction in a rabbit femoral fracture model. This innovation holds promise for addressing periprosthetic infections and improving the performance of orthopedic implants. © 2024 Jeong-Won Le et al.TRUEsciescopuskc
Learning-enabled flexible job-shop scheduling for scalable smart manufacturing
No full textIn smart manufacturing systems (SMSs), flexible job-shop scheduling with transportation constraints (FJSPT) is essential to optimize solutions for maximizing productivity, considering production flexibility based on automated guided vehicles (AGVs). Recent developments in deep reinforcement learning (DRL)-based methods for FJSPT have encountered a scale generalization challenge. We propose the Heterogeneous Graph Scheduler (HGS), a novel DRL-based method that provides near-optimal solutions regardless of the scale of operations, machines, and vehicles. HGS modifies the disjunctive graph to model FJSPT as a heterogeneous graph of operations, machines, and vehicles, dynamically representing processes and transportation. It involves a structure-aware heterogeneous graph encoder to enhance scale generalization, using multi-head attention to aggregate messages locally and integrate them globally. A three-stage decoder for end-to-end decision-making outputs the scheduling solution by selecting nodes with the highest likelihood of minimizing makespan. Our evaluation with benchmark datasets shows HGS outperforms traditional dispatching rules, metaheuristics, and existing DRL-based methods, demonstrating superior makespan performance and scale generalization. Moreover, as the scale increases, HGS achieves the best solutions across all instances. © 2024 The Society of Manufacturing EngineersFALSEsciescopu
Retinoic acid modulation of granule cell activity and spatial discrimination in the adult hippocampus
Get PDFRetinoic acid (RA), derived from vitamin A (retinol), plays a crucial role in modulating neuroplasticity within the adult brain. Perturbations in RA signaling have been associated with memory impairments, underscoring the necessity to elucidate RA’s influence on neuronal activity, particularly within the hippocampus. In this study, we investigated the cell type and sub-regional distribution of RA-responsive granule cells (GCs) in the mouse hippocampus and delineated their properties. We discovered that RA-responsive GCs tend to exhibit a muted response to environmental novelty, typically remaining inactive. Interestingly, chronic dietary depletion of RA leads to an abnormal increase in GC activation evoked by a novel environment, an effect that is replicated by the localized application of an RA receptor beta (RARβ) antagonist. Furthermore, our study shows that prolonged RA deficiency impairs spatial discrimination—a cognitive function reliant on the hippocampus—with such impairments being reversible with RA replenishment. In summary, our findings significantly contribute to a better understanding of RA’s role in regulating adult hippocampal neuroplasticity and cognitive functions. Copyright © 2024 Yeo, Park, Kim, Rah, Shin, Oh, Jang, Lee, Yoon and Oh.TRUEsciescopu
Age-based Optimal Design for Ensuring Data Freshness in Edge Computing-enabled Monitoring Networks
No full textWireless monitoring networks, edge computing-enabled networks, internet-of-things, age of information, sensing coverage, AoI violation probability, task splittingI. INTRODUCTION 1
1.1 Outline and Contributions 3
1.1.1 Chapter 2 3
1.1.2 Chapter 3 4
1.1.3 Chapter 4 4
II. Ensuring Data Freshness for Wireless Monitoring Networks 6
2.1 Contribution of This Chapter 6
2.2 System Model 7
2.2.1 Network Model 7
2.2.2 Error-tolerable Sensing (ETS) Coverage 9
2.3 Spectral Efficiency Analysis 11
2.3.1 Preliminaries 11
2.3.2 η-Coverage Probability 13
2.3.3 Average ETS Coverage 18
2.4 Average Energy Consumption Minimization 20
2.5 Numerical Results 26
2.5.1 Conclusion 31
III. Age-based Task Splitting for Edge Computing-enabled Networks 34
3.1 Contribution of This Chapter 34
3.2 Network Model 34
3.2.1 Latency Model 36
3.2.2 Successful Offloading Probability 37
3.3 Optimal Task Splitting Algorithm 38
3.3.1 Problem Formulation 38
3.3.2 Optimization of µ with Fixed ρ 39
3.3.3 Optimization of ρ with Fixed µ 40
3.3.4 Algorithm convergence and complexity 41
3.4 Numerical Results 42
3.5 Conclusion 44
IV. CONCLUSIONS 46
References 47DoctordCollectio