Ultra-low Power Research Articles

Ultralow Energy Consumption and Fast Neuromorphic Computing Based on La0.1Bi0.9FeO3 Ferroelectric Tunnel Junctions.

Low-power and fast artificial neural network devices represent the direction in developing analogue neural networks. Here, an ultralow power consumption (0.8 fJ) and rapid (100 ns) La0.1Bi0.9FeO3/La0.7Sr0.3MnO3 ferroelectric tunnel junction artificial synapse has been developed to emulate the biological neural networks. The visual memory and forgetting functionalities have been emulated based on long-term potentiation and depression with good linearity. Moreover, with a single device, logical operations of "AND" and "OR" are implemented, and an artificial neural network was constructed with a recognition accuracy of 96%. Especially for noisy data sets, the recognition speed is faster after preprocessing by the device in the present work. This sets the stage for highly reliable and repeatable unsupervised learning.

Ultralow Power and Green TSCH-Based WSNs With Proactive Reduction of Idle Listening

Ultralow Power and Green TSCH-Based WSNs With Proactive Reduction of Idle Listening

A Universal Biocompatible and Multifunctional Solid Electrolyte in p-Type and n-Type Organic Electrochemical Transistors for Complementary Circuits and Bioelectronic Interfaces.

The development of soft and flexible devices for collection of bioelectrical signals is gaining momentum for wearable and implantable applications. Among these devices, organic electrochemical transistors (OECTs) stand out due to their low operating voltage and large signal amplification capable of transducing weak biological signals. While liquid electrolytes have demonstrated efficacy in OECTs, they limit its operating temperature and pose challenges for electronic packaging due to potential leakage. Conversely, solid electrolytes offer advantages such as mechanical flexibility, robustness against environmental factors, and ability to bridge the interface between rigid dry electronics systems and soft wet biological tissues. However, few systems have demonstrated generality and compatibility with a wide range of state-of-the-art organic mixed ionic-electronic conductors (OMIECs). This paper introduces a highly stretchable, flexible, biocompatible, self-healable gelatin-based solid-state electrolyte, compatible with both p- and n-type OMIEC channels while maintaining high performance and excellent stability. Furthermore, this nonvolatile electrolyte is stable up to 120°C and exhibits high ionic conductivity even in dry environment. Additionally, an OECT-based complementary inverter with a record-high normalized-gain of 228 V-1 and a corresponding ultralow static power consumption of 1 nW is demonstrated. These advancements pave the way for versatile applications ranging from bioelectronics to power-efficient implants.

SiC Double Trench MOSFET with Split Gate and Integrated Schottky Barrier Diode for Ultra-Low Power Loss and Improved Short-Circuit Capability

SiC Double Trench MOSFET with Split Gate and Integrated Schottky Barrier Diode for Ultra-Low Power Loss and Improved Short-Circuit Capability

Ultra-low-power consumption silicon electro-optic switch based on photonic crystal nanobeam cavity

Ultra-low-power consumption and high-speed integrated switches are highly desirable for future data centers and high-performance optical computers. In this study, we proposed an ultra-low-power consumption silicon electro-optic switch based on photonic crystal nanobeam cavities on a foundry platform. The proposed switch showed an ultra-low static-tuning power of 0.10 mW and a calculated dynamic switching power of 6.34 fJ/bit, with a compact footprint of 18 μm × 200 μm. Additionally, a 136-Gb/s four-level pulse amplitude modulation signal transmission experiment was carried out to verify the capability of the proposed electro-optic switch to support high-speed data transmission. The proposed device has the lowest static-tuning power consumption among silicon electro-optic switches and the highest data transmission rate. The results demonstrate the potential applications of this switch in high-performance optical computers, data center interconnects, optical neural networks, and programmable photonic circuits.

Thermoelectric energy harvesting associated with heat pipes for monitoring highways weather conditions

This work aims to develop a prototype for autonomously monitoring highway weather conditions using thermoelectric energy. The prototype utilizes solar thermal energy, heat absorbed by the asphalt and soil heat to generate, convert, manage, and store energy. The study investigates the optimal functioning of the thermoelectric generator, including utilizing the soil as a heat sink and incorporating passive thermal control devices like heat pipes. A commercial ultra-low power converter model LTC3108 was experimentally tested for efficient energy conversion. The monitoring system is designed to acquire readings from sensors measuring relevant climate parameters such as temperature, atmospheric pressure, and humidity, focusing on ultra-low power characteristics. The acquired data is transmitted via LoRa technology to a server for processing and analysis. The prototype generated 286.24 J of energy with a maximum temperature gradient of 4.25 ºC in the thermoelectric generator. The energy cost of transmitting a 40-byte message through the LoRaWAN module was 0.625 J. The proposed climate data acquisition circuit had a theoretical consumption of 17.69 J. Experimental tests with the LTC3108 converter, and a 0.22 F supercapacitor demonstrated successful data transmission. This work provides a solid foundation for future studies utilizing thermoelectric energy in highway applications, resulting in a prototype suitable for real-world road scenarios.

Fully tunable Fabry-Pérot cavity based on MEMS Sagnac loop reflector with ultra-low static power consumption

The Fabry-Pérot interferometer, a fundamental component in optoelectronic systems, offers interesting applications such as sensors, lasers, and filters. In this work, we show a tunable Fabry-Pérot cavity consisting of tunable Sagnac loop reflectors (SLRs) and phase shifters based on electrostatic microelectromechanical (MEMS) actuator. The fabrication process of the device is compatible with the standard wafer-level silicon photonics fabrication processes. This electrostatic actuation mechanism provides well-balanced, scalable pathways for efficient tuning methodologies. The extinction ratio of the continuously tunable SLRs’ reflectivity is larger than 20 dB. Full 2π phase shifting is achieved, and response times of all the components are less than 25 μs. Both actuators have extremely low static power, measuring under 20 fW and the energy needed for tuning is both below 20 pJ.

A 99.99% current efficiency fast transient response capacitor-less LDO with feedforward compensation technique based on small-signal gain stage

An ultra-low power capacitor-less LDO with feedforward compensation technique based on the small-signal gain stage and composite transient enhancement structure is proposed. The feedforward compensation technique based on the small-signal gain stage reaches a low frequency zero ,by utilizing the compensating effect of the zero to relieve the adverse effects of the pole, thereby enhancing the stability and performance of the circuit. Furthermore, the small gain stage can adjust the quiescent current consumption,contributing to a significant reduction in system energy consumption. The proposed composite transient enhancement structure can reduce the transition time of the circuit, adjust the gain of the circuit under different operating conditions to achieve precise gain control and improve the transient performance of the system. The proposed LDO is designed using SMIC 0.18um CMOS process. The simulation results show the total quiescent current is 0.94uA and the current efficiency is up to 99.99%. The extremely low FoM value of 0.04 represents a good transient performance. Synthesizing the comparison of various parameters, the superiority of this design can be clearly concluded.

Characterization of high-speed writing and reading operations of the superconducting memory cell

Abstract Superconducting memory cells that use flux quanta as their storage medium can achieve ultra-fast access times with ultra-low power consumption. However, the data signal generated by a flux quantum memory (FQM) cell is usually too weak and too fast to be measured directly. Here, we present a method to characterize the real-time operation of an FQM cell. The storage loop of the FQM cell, configured with a Nb/NbN X /Nb Josephson junction, was proven the capability to store multiple flux quanta. The readout was demonstrated by a superconducting quantum interference device composed of underdamped Nb/Al-AlO X /Nb Josephson junctions. The writing and reading operations were achieved by a short pulse ranging from 0.1 ns to 2.5 ns, and a constant bit error rate of ∼2.46% was measured for the fabricated FQM cell. The method presented here can be used to study real-time operation of an FQM cell in a direct manner.

Ultralow Power, Cleft Size-Adjustable and pH-Sensitive Hyaluronic Acid (HA) Biodevices for Acid-Sensing Ion Channels Emulation.

The burgeoning implantable biodevices have unlocked new frontiers in healthcare, promising personalized monitoring strategies tailored to specific needs. Herein, hyaluronic acid (HA) is harnessed to create fully biocompatible, acidity-sensitivity and cleft-adjustable neuromorphic devices. These HA-biodevices exhibit remarkable sensitivity to pH variations, effectively mimicking biological acid-sensing ion channels (ASICs) through protonation reactions between electronegative atoms and hydrogen ions, even at ultralow driving voltage (5mV). They can monitor joint cartilage acidity by tracking changes in proton concentration and successfully diagnose the onset of arthritis. Furthermore, by adjusting the synaptic device's cleft distance, which determines responsiveness, power efficiency and plasticity, HA-based neuromorphic devices can be tailored to meet the unique demands of various implantation sites, providing both high-sensitivity and low-heat dissipation, thus broadening their application scopes. Moreover, the HA-biodevices maintain stable performance across various bending degrees, up to a curvature radius of 7.5mm, with flexibility and deformation resilience enabling installation on joints of varying curvatures. The combination of all-biocompatibility, high sensitivity, low heat dissipation, ultralow low power (2 pW), and extraordinary deformation tolerance paves the way for the development of versatile, multipurpose medical monitoring devices with immense potential in the field of healthcare.

Gate all around carbon nanotube field effect transistor espoused discrepancy cascode pass transistor adiabatic logic for ultra-low power application

Advances in wearable technology, IoT, and mobile applications have increased the demand for ultra-low-power electronic devices. Adiabatic Logic Circuit (ALC) is a design technique utilized in digital circuits to decrease the power consumption by decreasing the dynamic power dissipation. Current technologies face challenges in achieving both high performance and ultra-low power consumption. This research work introduces a novel approach in digital circuit design, specifically the Gate All-around Carbon Nanotube Field Effect Transistor with Discrepancy Cascode Pass Transistor Adiabatic Logic (GAA-CNTFET-DCPTAL), tailored for ultra-low power applications. This design operates efficiently with a four-phase Power Clock (PC) and demonstrates remarkable performance by achieving operation frequencies of up to 1 GHz while minimizing energy dissipation. GAA-CNTFET provides superior electrostatic control and high carrier mobility, reducing leakage currents and enhancing switching speeds. Simultaneously, Discrepancy Cascode Pass Transistor Adiabatic Logic (DCPTAL) uses adiabatic logic principles and a cascode structure to minimize energy dissipation during switching events. The technology node of proposed model is 10 nm. The software used for assessment is HSPICE is used for the simulation and validation of the proposed design. The proposed GAA-design attains 25.36 %, 14.28 %, and 16.06 % lower average power analyzed with existing techniques, such as Design with Evaluation of Clocked Differential Adiabatic Logic Families for the applications of low Power (DE-CDAL-LPA), Adiabatic logic-base strong ARM comparator for ultra-low power applications (AL-SARM-ULPA) and Analysis of 2PADCL Energy Recovery Logic for Ultra Low Power VLSI Design for SOC with Embedded Applications (2PADCL-ULP-VLSI) respectively.

Ultralow Power Consumption Coaxial-Structured Electrophoretic Display Fibers with Stretchability and Environmental Adaptability

Ultralow Power Consumption Coaxial-Structured Electrophoretic Display Fibers with Stretchability and Environmental Adaptability

Ultralow Power In-Sensor Neuronal Computing with Oscillatory Retinal Neurons for Frequency-Multiplexed, Parallel Machine Vision.

In-sensor and near-sensor computing architectures enable multiply accumulate operations to be carried out directly at the point of sensing. In-sensor architectures offer dramatic power and speed improvements over traditional von Neumann architectures by eliminating multiple analog-to-digital conversions, data storage, and data movement operations. Current in-sensor processing approaches rely on tunable sensors or additional weighting elements to perform linear functions such as multiply accumulate operations as the sensor acquires data. This work implements in-sensor computing with an oscillatory retinal neuron device that converts incident optical signals into voltage oscillations. A computing scheme is introduced based on the frequency shift of coupled oscillators that enables parallel, frequency multiplexed, nonlinear operations on the inputs. An experimentally implemented 3 × 3 focal plane array of coupled neurons shows that functions approximating edge detection, thresholding, and segmentation occur in parallel. An example of inference on handwritten digits from the MNIST database is also experimentally demonstrated with a 3 × 3 array of coupled neurons feeding into a single hidden layer neural network, approximating a liquid-state machine. Finally, the equivalent energy consumption to carry out image processing operations, including peripherals such as the Fourier transform circuits, is projected to be <20 fJ/OP, possibly reaching as low as 15 aJ/OP.

Design and Analysis of a Power-Efficient Dynamic Comparator with an Improved Transconductance in Ultra-low Power SAR ADC Applications

Design and Analysis of a Power-Efficient Dynamic Comparator with an Improved Transconductance in Ultra-low Power SAR ADC Applications

Energy-Efficient Reservoir Computing Based on Solution-Processed Electrolyte/Ferroelectric Memcapacitive Synapses for Biosignal Classification.

The classification of critical physiological signals using neuromorphic devices is essential for early disease detection. Physical reservoir computing (RC), a lightweight temporal processing neural network, offers a promising solution for low-power, resource-constrained hardware. Although solution-processed memcapacitive reservoirs have the potential to improve power efficiency as a result of their ultralow static power consumption, further advancements in synaptic tunability and reservoir states are imperative to enhance the capabilities of RC systems. This work presents solution-processed electrolyte/ferroelectric memcapacitive synapses. Leveraging the synergistic coupling of electrical double-layer (EDL) effects and ferroelectric polarization, these synapses exhibit tunable long- and short-term plasticity, ultralow power consumption (∼27 fJ per spike), and rich reservoir state dynamics, making them well-suited for energy-efficient RC systems. The classifications of critical electrocardiogram (ECG) signals, including arrhythmia and obstructive sleep apnea (OSA), are performed using the synapse-based RC system, demonstrating excellent accuracies of 97.8 and 80.0% for arrhythmia and OSA classifications, respectively. These findings pave the way for developing lightweight, energy-efficient machine-learning platforms for biosignal classification in wearable devices.

Study on the phase transformation mechanism and influencing factors of inorganic condensable particulate matter from coal-fired power plants

In this study, the concentration of inorganic ions (SO42−, NH4+, NO3− and NO2−) and morphological characteristics of condensable particulate matter (CPM) were investigated to elucidate the formation mechanism of inorganic CPM from ultra-low emission coal-fired power plants. The concentration of inorganic ions increased with the increase of H2O content and concentration of inorganic gaseous contaminants (SO2, NOX and NH3), and decrease of condensation temperature, indicating the enhancement of heterogenous reaction in the saturated flue gas. Furthermore, NOX and SO2 could undergo redox reactions, leading to an elevation in the concentration of SO42− and NO3−. Additionally, the introduction of NH3 resulted in increased concentrations of SO42−, NO3−, and NO2−, highlighting the significant role of NH3 neutralization in CPM nucleation. The condensation of SO3/sulfuric acid aerosols was enhanced under saturation conditions, and SO2 and SO3/sulfuric acid aerosols could contribute synergistically to the formation of SO42−. Moreover, morphological analysis revealed the presence of both well-aggregated solid CPM and dispersed liquid CPM, confirming the formation of inorganic CPM during fast condensation. Furthermore, the detected CPM were composed of S and O, which identified the significant role of sulfates in the inorganic CPM. These findings provide valuable insights for the control of inorganic CPM in flue gas systems.

Characterising Skin Electrical Impedance Using Tape Stripping Methods: A Bioelectrical Study of a Porcine Model.

Background Recent advancements in ultra-low power electronics and wireless devices have facilitated the widespread adoption of wearable technology for fitness and health monitoring, paving the way for personalized medicine. Microneedle-based devices, comprising small epidermal patches that penetrate the skin's stratum corneum to potentially access biomarkers in the extracellular fluid of the viable epidermis, represent a promising innovation in this field. Objectives This project aimed to develop and validate a novel method to evaluate microneedle engagement in the skin in real-time. To our knowledge, there are no studies published to date that have characterized the electrical impedance of stratum corneum and epidermis using the tape stripping method to selectively remove cell layers. Additionally, no studies have been published comparing the electrical impedance of fresh to frozen-thawed porcine skin. The objective of this study was to develop and validate a novel method to evaluate microneedle engagement in skin, in real-time, that does not require processing of the tissue. Methods A tape stripping technique was employed to selectively remove the stratum corneum from fresh and frozen-thawed porcine skin samples which were then electrically characterized using an excitation frequency of 5 kHz with a peak Voltage of 1 V. Results This study demonstrated a mean impedance reduction of 97.08 ± 1.3 % for fresh porcine skin, and 98.04 ± 0.3 % for frozen-thawed porcine skin when transitioning from the surface stratum corneum to the viable epidermis. The correlation between the reduction of impedance and the number of tape strips across all 18 test sites was significant (r = 0.98, p < 0.00001). However, comparing the skin impedance of the fresh and frozen-thawed specimens showed poor equivalence, with the frozen-thawed sites approximately 5.5 times the impedance of the fresh sites before any tape stripping, and 4.19 times greater after 30 tape strips. Conclusions These findings suggest that monitoring for an interelectrode impedance decrease of greater than 95% between two projections of a microneedle device could provide a rapid and effective evaluation of skin engagement, crucial for advancing the development and clinical application of microneedle-based technologies in personalized medicine. The study also underscores the impact of the freeze-thaw process on the mechanical and electrical properties of skin, which is crucial for standardizing testing protocols.

Missing-cell defects in QCA wires: The ground and excited electronic states perspectives

Quantum Cellular Automata (QCA) technology offers promising prospects for designing molecular electronic circuits that operate at high frequencies and with ultra-low power consumption. QCA wires serve as crucial conduits for digital data transmission between logic gates. A series of QCA cells arranged sequentially forms these wires, with data written or read using paired nanogap electrodes. In this study, employing a simplified full-basis quantum mechanical model, we investigate the impact of single and double missing cells on the response function and output voltage of wires implemented within the two-dot QCA architecture. The electronic coupling between the quantum dots within each QCA cell stands out as a critical structural parameter influencing both the nonlinearity of the response function and the level of output voltage. Ground state analyses of wires affected by missing-cell defects suggest that employing QCA cells with weak electronic coupling could potentially enhance fault tolerance. However, examination of excited states reveals that reducing electronic coupling may compromise the thermal robustness of such defective QCA wires.

Light-Adapted Optoelectronic-Memristive Device for the Artificial Visual System.

With the development of artificial intelligence systems, it is necessary to develop optoelectronic devices with photoresponse and storage capacity to simulate human visual perception systems. The key to an artificial visual perception system is to integrate components with both sensing and storage capabilities of illumination information. Although module integration components have made useful progress, they still face challenges such as multispectral response and high energy consumption. Here, we developed a light-adapted optoelectronic-memristive device integrated by an organic photodetector and ferroelectric-based memristor to simulate human visual perception. ITO/P3HT:PC71BM/Au as the light sensor unit shows a high on/off ratio (Iph/Id) reaching ∼5 × 104 at 0 V. The memristor unit, consisting of ITO/CBI@P(VDF-TrFE)/Cu, has a RON/ROFF ratio window of ∼106 under 0.05 V read voltage and ultralow power consumption of ∼1 pW. Moreover, the artificial visual perception unit shows stable light-adapted memory windows under different wavelengths of irradiation light (400, 500, and 600 nm; they meet the spectral range of human visual recognition) and can clearly identify the target image ("T" shape) because of the apparent contrast, which results from the high ROFF/RON ratio values. These results provide a potential design strategy for the development of intelligent artificial vision systems.

Ultra Low Power Consumption Optoelectronic Logic Operation of CuO/BaTiO3 Heterojunction Photodetector with Tunable Internal Electric Field Based on Poling Effect

AbstractThe study presents a novel self‐powered ultraviolet (UV) photodetector harnessing both polarization fields and photovoltaic effects, enabling the realization of ultra‐low power, reconfigurable optoelectronic logic gates. The approach is demonstrated on a CuO/BaTiO3 heterojunction photodetector. The behavior of the photodetector is augmented by the poling effect, aligning the internal electric field of the BaTiO3 through the application of a robust external electric field, thereby facilitating the implementation of optoelectronic logic gates. In the unpoled state, the “XOR” and “OR” logic gates operated at voltages of 750 and −500 µV, respectively. However, upon poling up state, the “XOR” logic gate exhibits reduced operation voltage, operating at 500 µV, while the “OR” logic gate implements clarity at −500 µV. In the unpoled state the “AND” logic gate does not operate; however, upon poling in the downward direction, it operated at −500 µV. The achievement demonstrates successful ultra‐low‐power logic operations, utilizing voltages in the hundreds of micron scale, under a 310 nm wavelength and a light intensity of 0.52 mW·cm−2. Furthermore, controllable polarization electric fields in BaTiO3 enable the operation of “AND” logic gate in the unpoled state, presenting a promising avenue for future research in optoelectronic logic gate design.