Charge Modulation Research Articles

Development of a facial recognition model using optimized convolution neural network with Tiny-ML and fingerprint authentication for safe lock entry

Safe boxes have been used for centuries to protect valuable items, and their design and construction have evolved over time to improve security. In this study, we carried out the design and implementation of a facial recognition technology using optimized convolutional neural networks (CNNs) with TinyML and fingerprint. The facial recognition system is designed using pre-trained CNN architectures then optimized with TinyML to make it fit into resource constrained edge device, the fingerprint recognition is designed using ridge matching biometric algorithm which fits in perfectly into the microcontroller-based system. The safe box was fabricated using sheet metal and insulated using heat resistive material (fiber glass), components like OV2640 camera module, ESP32-S3, R305 Fingerprint sensor, 4.3 inches touch screen TFT display and a charging module to manage and charge the systems battery were used. The system was implemented to be a level two security and two-way verification system using secured Wi-Fi to access the system before the facial and fingerprint recognition functionality is activated, the sequence of operation can either be facial recognition before fingerprint recognition or fingerprint recognition before facial recognition. Evaluating the system’s facial recognition performance with confusion matrix, of all the optimized CNN architectures like VGGNet, SENet, RestNet, MobileNet-V2, EfficientNet-B0, SENet Architecture performed best outputting an accuracy of 98%, precision of 92%, also SENet unoptimized model performed same, MobileNet-V2 performed optimally in the inference speed test with a speed of 15ms/images with the fingerprint also evaluated using confusion matrix and perform with 98% accuracy. It was noticed that the inference speed of the unoptimized model is faster than that of the TinyML optimized model which is justifiable based on the processing clock speed, memory usage, GPU and architecture of the microcontroller/microprocessor. From the result obtained TinyML proves to be suitable mean for edge AI (artificial intelligence) and is recommended for future research and development.

Smart Infant Incubator

We propose a solution called "Smart Infant Incubator" which aims at enhancing the maintenance of new born in various hospitals to make it much better and safer. The main idea of the project is to implement an ESP32-based intelligent environment monitoring system in the incubator from which it measures the humidity and temperature data on the spot where the incubator is placed. The system uses sensors like DHT11 for live temperature and humidity readings, an intelligent alert system and it is integrated with the Rainmaker platform for remote monitoring. The power system is given special attention which includes a Li-ion cell and a charging module to charge the cell. Safety features such as overcharge protection for the battery are also added. The report gives a clear picture of the steps that were performed in the project to accomplish the goals and also the results and analysis of the project. The prototype can be very useful in improving the nursery wards where we will consider this technology to be integrated with the incubators which will be very useful in maintaining the newborns safely.

Revealing the Regulation Effect of Surface Charge at Aromatic Interface to Dynamic Conformational Changes of α‐Synuclein at Early Aggregation Stage

Comprehensive SummaryThe aggregation of α‐synuclein (α‐syn) is strongly influenced by membrane interfaces, but the mechanism of transition from monomers to oligomers at early aggregation stage is not clear. Here, we investigate the adsorption and structure changes of α‐syn on oppositely charged aromatic interfaces through in‐situ surface‐enhanced infrared absorption (SEIRA) spectroscopy and nano‐IR technique. The results show that the synergy of electrostatic and hydrophobic interactions leads to a “fast‐slow” two‐step aggregation pathway on negatively charged interface. Surface adsorption induces the formation of an extended helix structure and subsequently partial helix unwinding in NAC region, which enables the hydrophobic stacking between nearby NAC regions. Stable antiparallel β‐sheet rich aggregates are gradually emerging as further interactions of monomers with the fast formed “first layer”. Monomers electrostatically adsorb on positively charged interface by C‐terminus with NAC region and N‐terminus stretched in solvent, which serve as an aggregation core and induce further adsorption and gradual formation of aggregates with C‐terminus exposure. Our results demonstrate the modulation of surface charge and synergy of electrostatic and hydrophobic interactions on the interaction modes and aggregation pathways, which provide insights into dynamic conformation changes of α‐syn at early aggregation stage and imply the important role of spatial‐temporal heterogeneity of membranes in α‐synucleinopathies.

Precise Layer-by-Layer Assembly of Dual Quantum Dots Artificial Photosystems Enabling Solar Water Oxidation.

Quantum dots (QDs) colloidal nanocrystals are attracting enduring interest by scientific communities for solar energy conversion due to generic physicochemical merits including substantial light absorption coefficient, quantum confinement effect, enriched catalytically active sites, and tunable electronic structure. However, photo-induced charge carriers of QDs suffer from ultra-short charge lifespan and poor stability, rendering controllable vectorial charge modulation and customizing robust and stable QDs artificial photosystems challenging. Herein, tailor-made oppositely charged transition metal chalcogenides quantum dots (TMCs QDs) and MXene quantum dots (MQDs) are judiciously harnessed as the building blocks for electrostatic layer-by-layer assembly buildup on the metal oxides (MOs) framework. In these exquisitely designed LbL assembles MOs/(TMCs QDs/MQDs)n heterostructured photoanodes, TMCs QDs layer acts as light-harvesting antennas, and MQDs layer serves as electron-capturing mediator to relay cascade electrons from TMCs QDs to the MOs substrate, thereby yielding the spatially ordered tandem charge transport chain and contributing to the significantly boosted charge separation over TMCs QDs and solar water oxidation efficiency of MOs/(TMCs QDs/MQDs)n photoanodes. The relationship between interface configuration and charge transfer characteristics is unambiguously unlocked, by which photoelectrochemical mechanism is elucidated. This work would provide inspiring ideas for precisely mediating interfacial charge transfer pathways over QDs toward solar energy conversion.

The efficiency of dodecafluoro-2-methylpentan-3-one in suppressing NCM 811 lithium-ion battery fire

With the increase in the specific energy of lithium-ion batteries (LIBs), fire accidents occur more frequently; however, the effective and clean suppression of LIB fires remains a challenge. In the present work, the efficiency of dodecafluoro-2-methylpentan-3-one (C6F12O) in suppressing high energy density (HED) ternary LIB fires is experimentally investigated. It is found that C6F12O can efficiently extinguish the HED battery and its module fire. As the flow rate increases, the extinguishment time decreases and the peak temperature decreases, but the cooling efficiency for the long-term process is reduced. When the C6F12O spray can completely cover the thermal runaway (TR) area, its extinguishing and cooling effect is the best. For the HED module, the application of C6F12O effectively increases the TR trigger temperature, reduces the TR peak temperature, and decreases heat production. The application of water mist enhances the cooling of extinguished LIBs, the combination of C6F12O and water mist extends the TR propagation time of the fully charged LIB module to 1.4 times that without suppression, and the total TR heat production is reduced by 1423.1 kJ. These results provide guidance for the design of inhibitor volume fractions for HED LIB fires.

Smart Footstep Energy Harvesting System

This research paper introduces a novel approach to footstep energy harvesting by integrating piezoelectric sensors into flooring surfaces. The project aims to generate sustainable electrical power from footsteps, contributing to the development of energy-efficient systems. The proposed system incorporates a unique feature that enables users to easily identify and address sensor failures or damages. The core components of the system include piezoelectric sensors strategically placed in high-traffic areas, an Arduino microcontroller for signal processing and energy management, and a rechargeable battery for energy storage. A rectifier circuit is employed to convert AC signals generated by the sensors to DC, while a voltage regulator ensures a stable output voltage. The energy harvested is stored in the battery, which is connected to a USB charging module capable of charging electronic devices. To enhance the system's usability and maintenance, LEDs are integrated with each piezoelectric sensor. These LEDs act as indicators for sensor status, allowing users to visually identify any damaged or failed sensors. The Arduino code is designed to continuously monitor sensor values and activate the corresponding LED when a sensor falls below a predefined threshold, signaling a potential issue. This unique feature enhances user awareness, simplifies troubleshooting, and aids in the efficient maintenance of the energy harvesting infrastructure. The research focuses on the practical implementation of the system, exploring its effectiveness in real-world scenarios. Various aspects, such as energy generation efficiency, adaptability to different environments, and the ease of sensor failure identification, are evaluated through extensive experimentation. The paper discusses the system's potential applications, including sustainable power generation for small electronic devices and its integration into smart infrastructure. The proposed Smart Footstep Energy Harvesting System with Sensor Failure Identification addresses a crucial aspect of sustainability and smart infrastructure management. The findings from this research contribute to the growing field of energy harvesting technologies and pave the way for future developments in efficient, user-friendly, and maintainable footstep energy harvesting systems.

Direct Assessment of Defective Regions in Monolayer MoS2 Field-Effect Transistors through In Situ Scanning Probe Microscopy Measurements.

Implementing two-dimensional materials in field-effect transistors (FETs) offers the opportunity to continue the scaling trend in the complementary metal-oxide-semiconductor technology roadmap. Presently, the search for electrically active defects, in terms of both their density of energy states and their spatial distribution, has turned out to be of paramount importance in synthetic transition metal dichalcogenides layers, as they are suspected of severely inhibiting these devices from achieving their highest performance. Although advanced microscopy tools have allowed the direct detection of physical defects such as grain boundaries and point defects, their implementation at the device scale to assess the active defect distribution and their impact on field-induced channel charge modulation and current transport is strictly restrained. Therefore, it becomes critical to directly probe the gate modulation effect on the carrier population at the nanoscale of an FET channel, with the objective to establish a direct correlation with the device characteristics. Here, we have investigated the active channel in a monolayer MoS2 FET through in situ scanning probe microscopy, namely, Kelvin probe force microscopy and scanning capacitance microscopy, to directly identify active defect sites and to improve our understanding of the contribution of grain boundaries, bilayer islands, and defective grain domains to channel conductance.

Achievement of non-charge layer InGaAs/Si avalanche photodiodes by introducing a groove ring at the bonding interface

The avalanche photodiode (APD) is a prototypical example of a fast and high-gain detector, particularly in the infrared band, where it plays a crucial role in both military and civil optoelectronic devices. The combination of indium gallium arsenide (InGaAs) and silicon (Si) offers an ideal solution for achieving high-performance APDs. For traditional InGaAs/Si APDs, the incorporation of a p-Si charge modulation layer between InGaAs and Si is necessary for electric field modulation. This ensures that a high electric field is maintained in the multiplication layer while keeping it low in the absorption layer. However, the preparation of the p-Si charge modulation layer necessitates a tedious and expensive ion implantation process. Besides, the ion implantation process can also lead to material surface contamination that significantly affects the performance of the device. In this paper, an InGaAs/Si APD without the charge layer is reported. This approach is based on semiconductor direct bonding technology, wherein a groove ring is introduced into the bonding interface to replace the charge layer to regulate the electric field distribution. The electric field of the absorption layer and the multiplier layer is controlled by adjusting the number of grooved rings. By introducing 11 grooved rings into the bonding interface, we achieve a remarkable gain bandwidth product of 88.55 GHz. These findings hold significant implications for the future development of non-charge layer InGaAs/Si APDs with high-gain bandwidth products.

In Operando Study of Charge Modulation in MoS2 Transistors by Excitonic Reflection Microscopy.

Monolayers of transition metal dichalcogenides (2D TMDs) experience strong modulation of their optical properties when the charge density is varied. Indeed, the transition from carriers composed mostly of excitons at low electron density to a situation in which trions dominate at high density is accompanied by a significant evolution of both the refractive index and the extinction coefficient. Using optical interference reflection microscopy at the excitonic wavelength, this (n, κ)-q relationship can be exploited to directly image the electron density in operating TMD devices. In this work, we show how this technique, which we call XRM (excitonic reflection microscopy), can be used to study charge distribution in MoS2 field-effect transistors with subsecond throughput, in wide-field mode. Complete maps of the charge distribution in the transistor channel at any drain and gate bias polarization point (VDS, VGS) are obtained, at ∼3 orders of magnitude faster than with scanning probe techniques such as KPFM. We notably show how the advantages of XRM enable real-time mapping of bias-dependent charge inhomogeneities, the study of resistive delays in 2D polycrystalline networks, and the evaluation of the VDS vs VGS competition to control the charge distribution in active devices.

Quantum spin liquid signatures in monolayer 1T-NbSe2

Quantum spin liquids (QSLs) are in a quantum disordered state that is highly entangled and has fractional excitations. As a highly sought-after state of matter, QSLs were predicted to host spinon excitations and to arise in frustrated spin systems with large quantum fluctuations. Here we report on the experimental observation and theoretical modeling of QSL signatures in monolayer 1T-NbSe2, which is a newly emerging two-dimensional material that exhibits both charge-density-wave (CDW) and correlated insulating behaviors. By using scanning tunneling microscopy and spectroscopy (STM/STS), we confirm the presence of spin fluctuations in monolayer 1T-NbSe2 by observing the Kondo resonance as monolayer 1T-NbSe2 interacts with metallic monolayer 1H-NbSe2. Subsequent STM/STS imaging of monolayer 1T-NbSe2 at the Hubbard band energy further reveals a long-wavelength charge modulation, in agreement with the spinon modulation expected for QSLs. By depositing manganese-phthalocyanine (MnPc) molecules with spin S = 3/2 onto monolayer 1T-NbSe2, new STS resonance peaks emerge at the Hubbard band edges of monolayer 1T-NbSe2. This observation is consistent with the spinon Kondo effect induced by a S = 3/2 magnetic impurity embedded in a QSL. Taken together, these experimental observations indicate that monolayer 1T-NbSe2 is a new promising QSL material.

Modulation of charge in C9N4 monolayer for a high-capacity hydrogen storage as a switchable strategy

Modulation of charge in C9N4 monolayer for a high-capacity hydrogen storage as a switchable strategy

Heterostructures by Templated Synthesis of Layered Double Hydroxide to Modulate the Electronic Structure of Nickel Sites for a Highly Efficient Oxygen Evolution Reaction

The design and development of highly efficient electrocatalysts for oxygen evolution reaction (OER) are critical for renewable energy generation. Ni‐based electrocatalysts are widely used in the water electrolysis process. In this work, heterostructure consisting of selenides and layered double hydroxides (LDH) named (Co, Ni)Se4@NiFe‐LDH, are prepared by an LDH‐based strategy, in which the electronic structure of Ni active sites is regulated by interfacial electron interaction. The (Co, Ni)Se4@NiFe‐LDH shows an optimized charge distribution of Ni sites and excellent catalytic activity. The effective charge modulation results in lowering the energy barrier of OOH* intermediate formation and adequate adsorption strength of the intermediates on Ni‐active sites, which improves the kinetics of OER. Specifically, the (Co, Ni)Se4@NiFe‐LDH only requires an overpotential of 237 mV to reach the current density of 10 mA cm−2 under alkaline conditions. The results of this work demonstrate that reasonable engineering of heterostructure is an effective strategy to improve the intrinsic property of OER electrocatalysts for water splitting.

NMR study of charge density wave phase in the kagome metal RbV3Sb5

The mechanism of charge-density-wave (CDW) phase in one-dimensional lattices can be well described in theory. Whether similar mechanism works in two-dimensional systems is still a mystery. In this work, we employed 51V solid-state nuclear magnetic resonance (NMR) spectroscopy combined with first-principles computations to probe atomic structure and electronic properties at V sites in a quasi-two-dimensional crystal RbV3Sb5. Clear evidence of the CDW phase transition was observed from the temperature-dependent 51V NMR measurements. The sharp transition of 51V Knight shifts and electric field gradients (EFG) across the CDW transition supports the view that energy gap is formed by the nesting of partial Fermi surface in accompany with the superlattice formation. The calculated EFG parameters were also compared with our experiments, and the results suggest that the charge modulation of the CDW order is inverse Star-of-David pattern.

Optimal scheduling of electric-hydrogen integrated charging station for new energy vehicles

In this paper, a novel model of electric-hydrogen integrated charging station (ICS) is proposed, which is composed of battery swapping station (BSS) and hydrogen station (HS). The BSS model, which mainly includes user adaptive response model, battery allocation and scheduling strategy, is established to realize the reasonable management and allocation of batteries. The HS model mainly includes hydrogen production module, hydrogen storage module, hydrogen charging module, fuel cell module and hydrogen scheduling strategy to optimize scheduling from hydrogen production to use. In addition, the BSS can provide energy for HS, and both BSS and HS can feed back the stored energy to the power system during peak load, which is beneficial to the stable operation of the power system. Simulation shows the rationality and correctness of the proposed optimization model. The proposed model and optimization strategy can improve the flexibility and economy of ICS, and help the power system to cut peak and fill valley.

Research on control strategy of rapid preheating for power battery in electric vehicle at low temperatures

Due to cold weather conditions, it is not advisable to use the remaining capacity of the power battery to heat it. Instead, the battery can only be preheated during charging when the battery power is almost consumed up. The traditional positive temperature coefficient (PTC) heating system combines the cockpit air conditioning and heating system with the low-temperature preheating system for the power battery cells. The PTC controller is integrated into the air conditioning control system. However, this integration requires the air conditioning to be activated in order to preheat the power battery. As a result, there is energy waste during the charging process. To address the aforementioned issues, this article proposes a rapid preheating system that utilizes an independent liquid circuit equipped with a high-voltage heater. The system achieves a preheating time of 2000 s for a ternary lithium battery with a capacity of 73kWh and a rated voltage of 770 V. Another important finding is that fluctuations in the current of the battery management system (BMS) occur during the rapid preheating process, leading to uncontrolled battery charging and discharging. The battery rapid preheating control strategy has been redesigned to rapidly heat the battery system by disconnecting the rapid charging relay of the high-voltage circuit, thereby prevents over-discharge and overcharge of the power battery. Experiments have shown that the BMS current increases or decreases in a stepwise manner, as expected by the design. The average temperature of the battery pack during onboard charge module slow charging and direct current fast charging is below 35 °C, and the maximum temperature difference is less than 6 °C. The proposed rapid preheating system and improved battery charging architecture can shorten the charging time and reduce energy consumption. This advancement will open up new possibilities for power battery protection and contribute to the development of lithium-ion batteries for electric vehicles at low temperatures.

Nonmetal Atom Doping Induced Orbital Shifts and Charge Modulation at the Edge of Two-Dimensional Boron Carbonitride Leading to Enhanced Photocatalytic Nitrogen Reduction.

Electronic structure, particularly charge state analysis, plays a crucial role in comprehending catalytic mechanisms. This study focuses on metal-free boron carbonitride (BCN) nanosheets as a case study to investigate the impact of heteroatom doping on the charge state of active sites at the edge of two-dimensional (2D) metal-free nanomaterials. Our observations revealed that the doping induces a shift in the frontier py orbital near the Fermi level, accompanied by alterations in its charge state. These changes provide insights into the nitrogen adsorption descriptors and the critical hydrogenation step, ultimately leading to the proposal of a competitive charge transfer mechanism. Additionally, this exploration has led to the screening of five BCN-type structures (P@T1-C1, S@T1-B1, O@T1-B1, P@T1-B1C2, and P@T1-B1C3) with promising nitrogen reduction reaction (NRR) performances. The BCN structure (S@T1-B1) exhibited the lowest NRR overpotential reaching -0.2 V, which is associated with the proposed charge competition mechanism. Furthermore, the investigation delves into the key step hydrogenation mechanism, descriptors, and volcano diagrams of the conformational relationships. In addition, the proposed doping strategy endows the 2D-BCN with more sensitivity toward the solar spectrum, suggesting its application as a potential photocatalyst. Overall, this study establishes a strong foundation for the advancement of nonmetal-atom-doped BCN nanosheets in nitrogen reduction applications, while also providing a versatile framework for fine-tuning edge-site activity within the broader context of two-dimensional photo/electrocatalytic materials.

Smart Motorcycle Helmet: Utilizing CNN for Multi-Task Learning

Enhancing road safety through education and enforcement relies on automated motorcycle helmet detection via video surveillance. However, existing methods encounter challenges like tracking individual motorcycles and distinguishing riders from passengers. To overcome these limitations, we propose a CNN-based multi-task learning (MTL) method. Our approach focuses on identifying and tracking individual motorcycles, particularly emphasizing rider-specific helmet use. We introduce the HELMET dataset, containing 91,000 annotated frames from 10,006 motorcycles across 12 observation sites in Myanmar, serving as a benchmark for future detection techniques. Leveraging concurrent visual similarity learning and helmet use classification, our MTL approach achieves enhanced efficiency and accuracy, operating at over 8 FPS on consumer hardware. With a weighted average F-measure of 67.3% for detecting riders and helmet use, our method underscores deep learning's accuracy and resource efficiency in gathering critical road safety data. Furthermore, we present an intelligent motorcycle helmet equipped with infrared transceivers, an image sensor, an embedded computation module, a charging module, a microphone, and earphones. Designed for large vehicle approach notification, the helmet utilizes image recognition modes for both day and night conditions. Experimental results demonstrate successful vehicle registration plate recognition for large trucks/buses, achieving up to 75% accuracy during the day and 70% at night. In real-time, the proposed intelligent motorcycle helmet detects approaching large vehicles within a 5-meter distance.

Charge Transport in Sub‐Monolayer Networks of a Naphthalene‐Diimide‐Based Copolymer

AbstractSub‐monolayer networks of the electron‐transporting semiconducting polymer poly([N,N’‐bis(2‐octyldodecyl)‐naphthalene‐1,4,5,8‐bis(dicarboximide)−2,6‐diyl]‐alt‐5,5′‐(2,2′‐bithiophene)) (P(NDI2OD‐T2)) are realized through judicious choice of spin‐coating solvent and control of solution concentration. These sub‐monolayer networks provide a platform to study the effects of surface coverage, network connectivity, and orientational order on charge transport. It is found that charge transport through semiconducting polymer networks depends not only on the coverage/concentration of the material but also on the nature of the conduction paths themselves. Down to 40% surface coverage, current measured in a field‐effect architecture decreases in line with the decrease in surface coverage, but drops precipitously below a surface coverage of 40%. Below 40% surface coverage, there is a marked decrease in network connectivity (quantified through the branching point density) and a decrease in orientational order. Furthermore, an increase in the density of dangling branches (dead ends) is also seen with decreasing surface coverage. Additional supporting data in the form of grazing incidence wide‐angle X‐ray scattering (GIWAXS), optical spectroscopy, and charge modulation spectroscopy are presented, which help to establish that long‐range interconnectivity rather than local morphology dominates charge transport in P(NDI2OD‐T2) sub‐monolayers as well as thin films.

Evaluation of Electromagnetic Exposure in Wireless Power Transfer Systems for Electric Vehicles

In wireless power transfer (WPT) systems, the electromagnetic fields generated by a charging module may exceed the limits set by international safety guidelines. This is a matter of concern for the safety of users of high-power WPT systems, such as electric vehicles (EVs). To address this issue, this study designed a stationary WPT system for EV charging. Furthermore, the dosimetry of the system was evaluated for two exposure scenarios. Electromagnetic field data obtained using the electromagnetic field analysis tool were employed to derive the induced quantities in the human body using the impedance method. In addition, the obtained results were compared to the values recommended by international guidelines (International Commission on Non-Ionizing Radiation Protection).

Nanoscale visualization and spectral fingerprints of the charge order in ScV6Sn6 distinct from other kagome metals

Charge density waves (CDWs) in kagome metals have been tied to many exotic phenomena. Here, using spectroscopic-imaging scanning tunneling microscopy and angle-resolved photoemission spectroscopy, we study the charge order in kagome metal ScV6Sn6. The similarity of electronic band structures of ScV6Sn6 and TbV6Sn6 (where charge ordering is absent) suggests that charge ordering in ScV6Sn6 is unlikely to be primarily driven by Fermi surface nesting of the Van Hove singularities. In contrast to the CDW state of cousin kagome metals, we find no evidence supporting rotation symmetry breaking. Differential conductance dI/dV spectra show a partial gap Δ1CO ≈ 20 meV at the Fermi level. Interestingly, dI/dV maps reveal that charge modulations exhibit an abrupt phase shift as a function of energy at energy much higher than Δ1CO, which we attribute to another spectral gap. Our experiments reveal a distinctive nature of the charge order in ScV6Sn6 with fundamental differences compared to other kagome metals.