Ultra-low Energy Consumption Research Articles

Research on the Key Technology of the Heat Insulation and Sound Insulation of the Ultra-low Energy-consumption Green Floating Floor

At present, since global energy is becoming increasingly tight, it is imperative to develop green buildings and promote green technology. At the same time, it can also be integrated into the atmosphere of joint construction of green “Belt and Road” and the construction of Green Silk Road to make the green infrastructure build a harmonious and livable habitat for humanity. In terms of key technology of heat-insulation and sound insulation of the ultra-low energy-consumption green floating floor, analyzing and studying from status of research and development at home and abroad, sound insulation design of building, the design of the surface layer floating structure, technical characteristics of heat insulation and sound insulation of floating floor and moisturizing and sound insulation technology of floating floor, the advantages of ultra-low energy consumption green floating floor insulation are obtained finally.

Vesti: Energy-Efficient In-Memory Computing Accelerator for Deep Neural Networks

To enable essential deep learning computation on energy-constrained hardware platforms, including mobile, wearable, and Internet of Things (IoT) devices, a number of digital ASIC designs have presented customized dataflow and enhanced parallelism. However, in conventional digital designs, the biggest bottleneck for energy-efficient deep neural networks (DNNs) has reportedly been the data access and movement. To eliminate the storage access bottleneck, new SRAM macros that support in-memory computing have been recently demonstrated. Several in-SRAM computing works have used the mix of analog and digital circuits to perform XNOR-and-ACcumulate (XAC) operation without row-by-row memory access and can map a subset of DNNs with binary weights and binary activations. In the single array level, large improvement in energy efficiency (e.g., two orders of magnitude improvement) has been reported in computing XAC over digital-only hardware performing the same operation. In this article, by integrating many instances of such in-memory computing SRAM macros with an ensemble of peripheral digital circuits, we architect a new DNN accelerator, titled Vesti . This new accelerator is designed to support configurable multibit activations and large-scale DNNs seamlessly while substantially improving the chip-level energy-efficiency with favorable accuracy tradeoff compared to conventional digital ASIC. Vesti also employs double-buffering with two groups of in-memory computing SRAMs, effectively hiding the row-by-row write latencies of in-memory computing SRAMs. The Vesti accelerator is fully designed and laid out in 65-nm CMOS, demonstrating ultralow energy consumption of $ for CIFAR-10 classification at 1.0-V supply.

Broadband telecom emission from InP/InGaAs nano-ridge lasers on silicon-on-insulator substrate

Nanolasers directly grown on silicon substrates are ideal light sources for silicon-based photonic integrated circuits, benefiting from an ultra-small footprint and ultra-low energy consumption. However, constructing a compact laser source that covers a wide emission range is still challenging, especially for data-communication applications in the near-infrared region. Here, we explain a wavelength tuning strategy for InP/InGaAs nano-ridge lasers grown on silicon-on-insulator wafers through experimental measurements and detailed simulations. A wide tuning range of over 200 nm is achieved via tailoring the length of the on-chip Fabry-Perot nano-ridge lasers with identical epitaxial structures. With extensive mode and gain analyses of the nano-ridge lasers, we attribute the broadband tuning scheme to the enhanced band filling effect and the significant gain shift under high excitation levels. Our study provides a fresh perspective for the design of telecom nano-scale light emitters.

Fast-cured UV-LED polymer materials filled with high mineral contents as wear-resistant, antibacterial coatings

Development of ultraviolet (UV) curing technique has greatly expanded the preparation and application of polymer composite coatings due to its unique characteristics of high efficiency curing and controllable operation. However, the inevitable hazards of high pressure mercury lamps, as well as difficulty resulting from large amount of heat release when coating products, greatly limit the practical application and development of such curing coatings. Herein, a series of novel controllable, fast-cured coatings filled with high mineral contents were successfully designed and synthesized based on progressive ultraviolet light emitting diode (UV-LED) technology with ultra-low energy consumption. Due to the addition of a large number of opaque mineral particles, a new polymerization mechanism for the system was proposed and verified. Inorganic particle fillers (μm-level) can produce various degrees of reflective or refractive points, thus effectively reducing the barrier effect of the filling particles and realizing a much deeper solidification. Silver nanoparticles (AgNPs) were then combined with this composite material to fabricate a long-term antibacterial interior wall base-coating without interference with the curing effects. More importantly, the various effects of reactants of polymeric composite coatings with high inorganic mineral content for such UV-LED curing systems (365 nm) were brought to as comprehensive a conclusion as possible. This coating remained stable over a 15-week period against bacteria with the bactericidal coefficient of approximately 99.5% for E. coli and about 97% for S. aureus. We believe that proposed applicable polymerization mechanism will greatly enrich the current UV polymerization system, especially for polymer composite material with high mineral contents, and our designed wear resistance, high-hardness, and long-term antibacterial coating will also have great application prospects in many practical fields.

Highly efficient, visible active TiO2/CdS/ZnS photocatalyst, study of activity in an ultra low energy consumption LED based photo reactor

Nano Titania is the promising material for the photocatalytic process used in the minimization of the organic pollutant. However, there is need to enhance its absorption and surface properties to design a material having high efficacy. In this study, we report the synthesis of binary and ternary TiO2 nano-composites using the CdS and ZnS nanoparticles by adopting the low temperature two-step hydrothermal approach. The synthesized materials were characterized by using XRD, UV-DRS, FESEM, HRTEM, XPS and BET surface area analyzer. The photocatalytic activity was evaluated by taking the Rhodamine B (RhB) as model pollutant by employing an ultra low LED photo reactor. It was found that, the ternary TiO2/CdS/ZnS composite containing 10% ZnS and 20% CdS in wt. ratio showed the best activity towards the removal of RhB. The enhanced activity was due to improvement in the absorbance in the visible region and formation of heterojunction, which enhanced the lifetime of photoinduced charged species by the reduction in charge recombination. Reactive species, prominently responsible for degradation was identified by the scavenger action. The degradation pathway by which the RhB degraded is also discussed and found that degradation pathway altered with pH of solution.

Scanning near-field optical microscopy based phase-change optical memory

A novel concept of scanning near-field optical microscopy based phase-change optical memory was proposed to avoid excessive temperature inside the capping layer of probe-based phase-change memory without impairing its attractive storage attributes. An indium tin oxide medium was chosen to be the capping layer of the designed device and its optical properties for different wavelengths and thicknesses were computed by first-principle calculations. Combining these calculated parameters with a developed thermo-optical model, the recording process of the proposed optical memory was investigated and its potential for providing ultra-high density, ultra-fast switching speed, ultra-low energy consumption, and superior thermal stability was theoretically demonstrated.

Investigation of room temperature ferromagnetism in transition metal doped BiFeO3

Spintronic functionality in ferromagnetic materials is a next-generation technique, to be used in data storage, high-frequency communications, and logic devices with minimum energy consumption. Ultra-low energy consumption in high-speed logic devices can be envisioned by inducing ferromagnetic behavior into room temperature multiferroic materials. However, there is a scarcity of room temperature multiferroic materials which have a definite spin degree of freedom. To fully exploit these technological challenges, we introduce the induced ferromagnetism in bismuth ferrite (BiFeO3, BFO) by doping transition metal (Cr, Ni, Co) elements. Our investigation initiates with the experimental study on chemically synthesized BiFe(1−x)MxO3 samples where x = 0.0625 (6.25%) and M = Cr, Ni and Co. Experimental findings are verified by theoretical simulation using density functional theory (DFT + U) and gauge including projector augmented wave (GIPAW) based calculation. All the experimental studies are done at room temperature while the theoretical verification using DFT is carried to understand the underlying mechanism behind the magnetic behavior of doped BiFeO3. It is done by optimizing the structural parameters comparable to the room temperature values. Microstructural and magnetic properties are studied using x-ray diffraction (XRD), transmission electron microscopy (TEM) and Vibrating sample magnetometer (VSM). All these experimental studies confirm the structural changes and induced ferromagnetism with doping. X-ray photoelectron spectroscopy (XPS) verified the reason behind this ferromagnetic property on the basis of oxygen vacancy content. Electron paramagnetic resonance (EPR) spectroscopy shows the tuning of Δg values due to enhanced magnetization.The density of states (DOS) calculations were performed on BFO (band-gap 1.89 eV) after structural optimization using DFT + U method, confirm our experimental findings. Magnetic moment values change drastically with doping elements (M), i.e. almost negligible for BFO (antiferromagnetic) to maximum (2.85 μB/f.u.) for Ni-doped sample. We also compute the EPR g-tensor using GIPAW method to confirm the tuning of Δg values due to enhanced magnetization. These results can highlight the impact and importance of suitable transition element doping to induce the room temperature ferromagnetism in BiFeO3.

Oxide Neuromorphic Transistors Gated by Polyvinyl Alcohol Solid Electrolytes with Ultralow Power Consumption.

Neuromorphic devices and systems with ultralow power consumption are important in building artificial intelligent systems. Here, indium tin oxide (ITO)-based oxide neuromorphic transistors are fabricated using poly(vinyl alcohol) (PVA)-based proton-conducting electrolytes as gate dielectrics. The electrical performances of the transistors can be modulated with the ITO channel thickness. Fundamental synaptic functions, including excitatory postsynaptic current, paired-pulse facilitation, and multistore memory, are successfully emulated. Most importantly, the PVA-gated neuromorphic devices demonstrate ultralow energy consumption of ∼1.16 fJ with ultrahigh sensitivity of ∼5.4 dB, as is very important for neuromorphic engineering applications. Because of the inherent environmental-friendly characteristics of PVA, the devices possess security biocompatibility. Thus, the proposed PVA-gated oxide neuromorphic transistors may find potential applications in "green" ultrasensitive neuromorphic systems and efficient electronic biological interfaces.

Electric field control of Néel spin–orbit torque in an antiferromagnet

Electric field control of spin-orbit torque in ferromagnets1 has been intensively pursued in spintronics to achieve efficient memory and computing devices with ultralow energy consumption. Compared with ferromagnets, antiferromagnets2,3 have huge potential in high-density information storage because of their ultrafast spin dynamics and vanishingly small stray field4-7. However, the manipulation of spin-orbit torque in antiferromagnets using electric fields remains elusive. Here we use ferroelastic strain from piezoelectric materials to switch the uniaxial magnetic anisotropy in antiferromagnetic Mn2Au films with an electric field of only a few kilovolts per centimetre at room temperature. Owing to the uniaxial magnetic anisotropy, we observe an asymmetric Néel spin-orbit torque8,9 in the Mn2Au, which is used to demonstrate an antiferromagnetic ratchet. The asymmetry of the Néel spin-orbit torque and the corresponding antiferromagnetic ratchet can be reversed by the electric field. Our finding sheds light on antiferromagnet-based memories with ultrahigh density and high energy efficiency.

(Keynote) Silicon-Organic Hybrid Photonics: Integration of Electro-Optical Polymers in a Photonic Integrated Circuit Technology

In this work, we present recent results on the hybrid integration of electro-optical organic materials in a photonic integrated circuit (PIC) technology. We review some of the identified challenges regarding process compatibility and present preliminary results on the integration of organic materials in a PIC technology using a 0.25 µm SiGe BiCMOS pilotline. Here, we are focusing on electro-optical applications towards high-speed modulators with ultra-low energy consumption.

Technical Study on the Rock Wool/Polyurethane Composite Insulation Board and Its External Insulation System for Ultra-low Energy Consumption Buildings

Ultra-low energy consumption buildings refer to the buildings which adapt to the climate characteristics and natural conditions, use the envelope structure with high thermal insulation and air tightness performance as well as efficient fresh air heat recovery technology to minimize the heating and cooling demand of buildings, and make full use of renewable energy to provide comfortable indoor environment with less energy consumption. As a key part of the ultra-low energy consumption building technology system, the external wall heat transfer coefficient K value is much higher than the external wall heat transfer coefficient required by the current ordinary energy-saving buildings in China. In order to achieve the thermal insulation performance required by the ultra-low energy consumption buildings, higher requirements are put forward for the thermal insulation materials and external thermal insulation system of building envelope. In this research, a new type of thermal insulation material for external wall of buildings which combines rigid polyurethane and rock wool is developed, and its application technology in ultra-low energy consumption building external wall thermal insulation system is also studied.

Scanning probe memory with patterned amorphous carbon layer

The write and readout performances of a novel patterned probe memory using amorphous carbon film is investigated by a newly developed electrical switching model based on the modified Poole–Frenkel mechanism. According to this model, the optimized media stack consists of a 40 nm titanium nitride underlayer and amorphous carbon cells with the dimension of 5 × 5 × 5 nm3, isolated by a silicon dioxide region with a width of 3 nm. The capability of the designed device to provide ultra-high density, utmost reading contrast, ultra-low energy consumption and superb anti-thermal/readout interference was demonstrated, thus making it superior to any reported probe memories to date.

Unusual Behaviors of Electric-Field Control of Magnetism in Multiferroic Heterostructures via Multifactor Cooperation.

Electric-field control of magnetism (EFCM) is very important for the exploration of high-density, fast, and nonvolatile random-access memory with ultralow energy consumption. Here, we report the electric-field-induced ferroelectric phase transitions in Pb(Mg1/3Nb2/3)0.82Ti0.18O3 (PMN-0.18PT) and symmetry breaking of EFCM behaviors for corresponding directions in multiferroic heterostructures composed of amorphous ferromagnetic Co40Fe40B20 (CoFeB) and PMN-0.18PT. We uncover a new mechanism behind the unusual phenomena, involving coupling between CoFeB and PMN-0.18PT via complex cooperation of electric-field-induced ferroelectric phase transitions, competition of different ferroelectric domains, and internal electric field in PMN-0.18PT. The deterministic EFCM with reversible and nonvolatile nature opens up a new avenue for exploring EFCM in multiferroic heterostructures and is also significant for applications.

Discussion on the Intelligent Design of Ultra-Low Energy Consumption Passive Buildings

With the continuous development of science and technology and the gradual improvement of modern building technology, people pay more and more attention to the introduction of advanced technology in architectural design, such as the application of intelligent technology. With the increasingly severe environmental situation, people are increasingly demanding the environmental performance and green performance of buildings. The establishment of ultra-low energy consumption passive buildings has become one of the key construction contents of construction projects. This paper mainly analyzes the design points and architectural forms of related buildings from the perspective of intelligent control.

Fully Printed All-Solid-State Organic Flexible Artificial Synapse for Neuromorphic Computing.

Nonvolatile, flexible artificial synapses that can be used for brain-inspired computing are highly desirable for emerging applications such as human-machine interfaces, soft robotics, medical implants, and biological studies. Printed devices based on organic materials are very promising for these applications due to their sensitivity to ion injection, intrinsic printability, biocompatibility, and great potential for flexible/stretchable electronics. Herein, we report the experimental realization of a nonvolatile artificial synapse using organic polymers in a scalable fabrication process. The three-terminal electrochemical neuromorphic device successfully emulates the key features of biological synapses: long-term potentiation/depression, spike timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow energy consumption. The artificial synapse network exhibits an excellent endurance against bending tests and enables a direct emulation of logic gates, which shows the feasibility of using them in futuristic hierarchical neural networks. Based on our demonstration of 100 distinct, nonvolatile conductance states, we achieved a high accuracy in pattern recognition and face classification neural network simulations.

Multilayered Ag NP-PEDOT-Paper Composite Device for Human-Machine Interfacing.

Flexible pressure sensors have attracted increasing interest because of their potential applications on wearable sensing devices for human-machine interface connections, but challenges regarding material cost, fabrication robustness, signal transduction, sensitivity improvement, detection range, and operation convenience still need to be overcome. Herein, with a simple, low-cost, and scalable approach, a flexible and wearable pressure-sensing device fabricated by utilizing filter paper as the solid support, poly(3,4-ethylenedioxythiophene) to enhance conductivity, and silver nanoparticles to provide a rougher surface is introduced. Sandwiching and laminating composite material layers with two thermoplastic polypropylene films lead to robust integration of sensing devices, where assembling four layers of composite materials results in the best sensitivity toward applied pressure. This practical pressure-sensing device possessing properties such as high sensitivity of 0.119 kPa-1, high durability of 2000 operation cycles, and an ultralow energy consumption level of 10-5 W is a promising candidate for contriving point-of-care wearable electronic devices and applying it to human-machine interface connections.

Scale up of Microbial Fuel Cell Stack System for Residential Wastewater Treatment in Continuous Mode Operation

The most important operational expense during wastewater treatment is electricity for pumping and aeration. Therefore, this work evaluated operational parameters and contaminant removal efficiency of a microbial fuel cell stack system (MFCSS) that uses no electricity. This system consists of (i) septic tank primary treatment, (ii) chamber for secondary treatment containing 18 MFCs, coupled to an energy-harvesting circuit (EHC) that stores the electrons produced by anaerobic respiration, and (iii) gravity-driven disinfection (sodium hypochlorite 5%). The MFCSS operated during 60 days (after stabilization period) and it was gravity-fed with real domestic wastewater from a house (5 inhabitants). The flow rate was 600 ± 100 L∙d−1. The chemical oxygen demand, biological oxygen demand, total nitrogen and total phosphorous were measured in effluent, with values of 100 ± 10; 12 ± 2; 9.6 ± 0.5 and 4 ± 0.2 mg∙L−1, and removal values of 86%, 87%, 84% and 64%, respectively. Likewise, an EHC (ultra-low energy consumption) was built with 6.3 V UCC® 4700 µF capacitors that harvested and stored energy from MFCs in parallel. Energy management was programmed on a microcontroller Atmega 328PB®. The water quality of the treated effluent complied with the maximum levels set by the Mexican Official Standard NOM-001-SEMARNAT-1996-C. A cost analysis showed that MFCSS could be competitive as a sustainable and energy-efficient technology for real domestic wastewater treatment.

3D Neuromorphic Wireless Power Transfer and Energy Transmission Based Synaptic Plasticity

Energy consumption combined with scalability and 3D architecture is a fundamental constraint for brain-inspired computing. Neuromorphic architectures including memristive, spintronic, and floating gate metal–oxide–semiconductors achieve energy efficiency while having challenges of 3D design and integration, wiring and energy consumption problems for architectures with massive numbers of neurons and synapses. There are bottlenecks due to the integration of communication, memory, and computation tasks while keeping ultra-low energy consumption. In this paper, wireless power transmission (WPT)-based neuromorphic design and theoretical modeling are proposed to solve bottlenecks and challenges. Neuron functionalities with nonlinear activation functions and spiking, synaptic channels, and plasticity rules are designed with magneto-inductive WPT systems. Tasks of communication, computation, memory, and WPT are combined as an all-in-one solution. Numerical analysis is provided for microscale graphene coils in sub-terahertz frequencies with unique neuron design of coils on 2D circular and 3D Goldberg polyhedron substrates as a proof-of-concept satisfying nonlinear activation mechanisms and synaptic weight adaptation. Layered neuromorphic WPT network is utilized to theoretically model and numerically simulate pattern recognition solutions as a simple application of the proposed system design. Finally, open issues and challenges for realizing WPT-based neuromorphic system design are presented including experimental implementations.

Silicon-Organic Hybrid Photonic Devices in a Photonic Integrated Circuit Technology

In this work, we present recent results on the hybrid integration of electro-optical organic materials in a photonic integrated circuit (PIC) technology. We review some of the identified challenges regarding process compatibility and present experimental results on the integration of organic materials in a PIC technology using a 0.25 μm SiGe BiCMOS pilotline. Here, we are focusing on electro-optical applications toward high-speed modulators with ultra-low energy consumption.

CO2 Adsorption on Premodified Li/Al Hydrotalcite Impregnated with Polyethylenimine

In this study, Li/Al hydrotalcite (HT) was treated with calcination and potassium hydroxyl-ethanol to form bcHT (basic-modified calcined hydrotalcite). This material was then polyethylenimine (PEI)-functionalized to create a new sorbent that has ultralow energy consumption. Various methods were applied to characterize the sorbent, including N2 adsorption–desorption, Fourier transform infrared spectroscopy, X-ray diffraction, and scanning electron microscopy. CO2 adsorption capacity, which was affected by PEI loadings and adsorption temperatures, was assessed with the CO2 adsorption isotherms and cyclic CO2 adsorption–desorption performance. Results showed that the optimal CO2 adsorption capacity of 1.723 mmol/g was reached when operating with temperature of 323 K and PEI loading of 40%. The Freundlich model was applied to provide optimal correlations with the experimental data, and the correlation coefficients reached 0.997. The average isosteric heat of CO2 adsorption was calculated to be 67.492 kJ/mol. ...