Energy-efficient Information Research Articles

Perpendicular magnetic anisotropy modulated by interfacial magnetoelectric coupling in Fe4N/0.75Pb(Mg1/3Nb2/3)O3-0.25PbTiO3 multiferroic heterostructures

Electric-field-controlled magnetic anisotropy in ferromagnetic/PMN-PT multiferroic heterostructure attracts great interest due to its promising application for energy-efficient information storage. Herewith, we investigate the effect of ferroelectric polarization and interfacial oxidation on magnetic anisotropy in Fe4N/PMN-PT multiferroic heterostructure using first-principles calculations. The reversal of ferroelectric polarization produces a sizable increase in the perpendicular magnetic anisotropy of Fe4N/PMN-PT heterostructures while the interfacial oxidation changes the sign of the magnetic anisotropy. The modulation of magnetic anisotropy in Fe4N/PMN-PT heterostructure is attributed to the spin–orbit-coupled Pb p states induced by the magnetoelectric coupling effect. These results lay the foundation for realizing electric-field control of perpendicular magnetic anisotropy in multiferroic heterostructures.

Nano P(VDF-TrFE) doped polyimide alignment layers for twisted nematic liquid crystal devices

ABSTRACTThe rapid development of consumer electronics and portable devices imposes a great demand for energy efficient information display systems. Among the information display devices, liquid crystal display (LCD) devices stands in the front. The fabrication of energy-efficient LCD systems demands new material and techniques. In this work, the conventional polyimide alignment layer of twisted nematic liquid crystal device (TNLCD) was replaced with ferroelectric polymer nanoparticle doped alignment layer. Morphology of the alignment layer was analysed using field emission scanning electron microscopy (FESEM) and atomic force microscopy (AFM). The ferroelectric nature of the polymer alignment layer was studied using dynamic contact electrostatic force microscopy (DC-EFM). TNLCD cells are fabricated with this modified alignment layer and the switching characteristics are compared with the conventional TNLCD devices. The TNLCD with modified alignment layer has shown a reduction of 50% in threshold (Vthr) and 47% reduction in saturation voltage (Vsat).

Impact of imperfect channel estimation and antenna correlation on quantised massive multiple‐input multiple‐output systems

This study examines the uplink performance of large-constellation multi-user massive multiple-input multiple-output systems with low-resolution analogue-to-digital converters (ADCs) in the presence of channel correlation and imperfect channel state information (CSI). The base station (BS) employs a large number of antennas for multiplexing and demultiplexing co-channel users with each antenna element having a dedicated radio frequency chain and two low-resolution ADCs. While such ADCs cause data loss due to coarse quantisation, the large number of antennas can be exploited not only to alleviate such a problem but also to make it possible to utilise large-constellation modulation schemes. The results provide an insight into the trade-off between various performance metrics and the number of quantisation bits under a wide range of realistic conditions. It will be shown that 1-bit quantisation provides sufficient resolution with 100 BS antennas to communicate with ten user equipments using quadrature phase shift keying, but the number of quantisation bits must be increased for larger constellations particularly to overcome CSI mismatch and channel correlation. The results also consider the trade-off between average mutual information and power consumption of the low-resolution ADCs. It will be shown that 16-quantum amplitude modulation with 2-bit quantisation may provide a good compromise between energy efficiency and average mutual information.

Energy and spectral efficiency of secure massive MIMO downlink systems

Spectral efficiency, energy efficiency, and security are cornerstones for the upcoming 5G systems. In this study, the issue of how the energy and spectral efficiency of multiuser massive multiple-input multiple-output (Ma-MIMO) systems are affected in the presence of a secrecy constraint is addressed. The performance of the two most prominent linear precoding techniques, the matched filter (MF) and zero-forcing (ZF) precoders, for secure downlink multiuser Ma-MIMO in the presence of multi-antenna passive eavesdropper is investigated. The authors consider three performance metrics, namely, the achievable ergodic secrecy rate, the secrecy spectral efficiency (SSE), and the secrecy energy efficiency (SEE), assuming perfect and imperfect channel state information. The tradeoff between SSE and SEE is also studied. Moreover, the authors derive tight lower bounds on the achievable ergodic secrecy rate for MF and ZF precoding techniques. The derived lower bounds provide insights on the tradeoff between the SSE and SEE. It is shown that ZF precoder outperforms MF precoder at high transmit power, whereas at very low transmit power, MF outperforms ZF. Moreover, it is shown that using large number of transmit antennas can improve the SSE and the SEE with orders of magnitude compared to a single-input single-output system.

Miniaturization of adiabatic quantum-flux-parametron circuits by adopting offset buffers

Adiabatic quantum-flux-parametron (AQFP) logic is one of the most promising superconductor logic families as a candidate to achieve future energy-efficient high-performance information processing systems. The static power of AQFP logic is zero because of ac flux bias, and the switching energy is ∼zJ at 5 GHz due to adiabatic switching. In this study, we propose a design method using offset buffers to reduce the dimension of AQFP circuits; in particular, we focus on the reduction in the horizontal dimension (which is parallel to excitation current) because in AQFP circuits the horizontal dimension tends to be greater than the vertical dimension (which is perpendicular to excitation current). Offset buffers are buffers with offset input signals. The use of offset buffers enables us to eliminate constant cells (which generate constant 0 s and 1 s) from some logic gates, so that the horizontal dimension of logic gates such as AND and OR gates can be significantly reduced. We designed AND and OR gates with offset buffers, and demonstrated them with wide operating margins. Then, we designed and demonstrated a 4–16 decoder using the AND gate with an offset buffer. We found that the horizontal dimension and area of a 4–16 decoder can be reduced by 33% and 26%, respectively, via the use of offset buffers.

Triplon band splitting and topologically protected edge states in the dimerized antiferromagnet

Search for topological materials has been actively promoted in the field of condensed matter physics for their potential application in energy-efficient information transmission and processing. Recent studies have revealed that topologically invariant states, such as edge states in topological insulators, can emerge not only in a fermionic electron system but also in a bosonic system, enabling nondissipative propagation of quasiparticles. Here we report the topologically nontrivial triplon bands measured by inelastic neutron scattering on the spin-1/2 two-dimensional dimerized antiferromagnet Ba2CuSi2O6Cl2. The excitation spectrum exhibits two triplon bands that are clearly separated by a band gap due to a small alternation in interdimer exchange interaction, consistent with a refined crystal structure. By analytically modeling the triplon dispersion, we show that Ba2CuSi2O6Cl2 is the first bosonic realization of the coupled Su-Schrieffer-Heeger model, where the presence of topologically protected edge states is prompted by a bipartite nature of the lattice.

Transition Metal Dichalcogenide-Based Field-Effect Transistors for Analog/Mixed- Signal Applications

Transition metal dichalcogenides (TMDs), such as MoS2, MoSe2, MoTe2, WS2, WSe2, etc., have been considered as the most promising candidates for energy-efficient information processing at ultrascaled devices due to their decent energy gap of around 1–2 eV and single-atomic thickness. Even though there are many efforts to explore their performance for digital applications, their performance considerations for analog/mixed-signal applications are still unexplored. In this regard, we have assessed the analog/RF performance of TMD-based field-effect transistors (TMD-FETs) and investigated their benefits over graphene-FET and black phosphorous-FETs. The performance analysis is done by an in-house developed code, which involves the self-consistent solutions of 2-D Poisson’s equation and nonequilibrium Green’s function (NEGF) formalism. The results show that MoS2-FET can offer high intrinsic gain with the intrinsic cutoff frequency and maximum oscillation frequency in terahertz range. However, the significant degradation in high-frequency performance of MoS2-FET is observed in the presence of external resistances and parasitic capacitances. The cutoff frequency has found a few hundreds of gigahertz range in the presence of all parasitic conditions. It has also found that, among TMD-FETs, WSe2-FET could be a promising candidate for analog/RF integrated circuits with a higher drive current, intrinsic gain, cutoff frequency, and maximum oscillation frequency.

Засоби підтримки прийняття рішень для визначення пріоритетності виконання енергозберігаючих проектів

Розроблено структуру засобів підтримки прийняття рішень під час визначення пріоритетності виконання енергозберігаючих проектів. Визначено, що для ефективної роботи системи підтримки прийняття рішень під час визначення пріоритетності виконання енергозберігаючих проектів у склад системи повинні входи такі засоби: збирання та зберігання інформації про енергоефективність підприємства; числового оцінювання критеріїв вибору; модель і програмні засоби визначення пріоритетності виконання енергозберігаючих проектів; прогнозування енергоефективності підприємства з врахуванням реалізації енергозберігаючого проекту; візуалізації результатів моделювання. Розроблено модель визначення пріоритетності виконання енергозберігаючих проектів, яка ґрунтується на методі аналізу ієрархій і враховує взаємодію та взаємозалежність критеріїв вибору проекту. Сформовано перелік економічних, технічних, виробничих, екологічних і організаційних критеріїв для вибору інвестиційних енергозберігаючих проектів. Показано, що розроблення моделі визначення пріоритетності виконання інвестиційних енергозберігаючих проектів виконується за п'ять етапів: на першому етапі здійснюється відображення задачі визначення пріоритетності виконання інвестиційних енергозберігаючих проектів у вигляді трирівневого дерева ієрархій; на другому етапі проводиться експертне числове оцінювання економічних, технічних, виробничих, екологічних і організаційних критеріїв вибору; на третьому етапі формується матриця попарних порівнянь та обчислюються власний вектор і вектор пріоритетів для другого рівня ієрархії; на четвертому етапі формується матриця попарних порівнянь і обчислюються вектор пріоритетів для кожного енергозберігаючого проекту; на п'ятому етапі обчислюється вектор глобальних пріоритетів. Розроблено програмні засоби для автоматизації процесу обчислення вектора глобальних пріоритетів. Розроблено з використанням Sankey діаграм, засоби візуалізації вектора глобальних пріоритетів і вектора пріоритетів проектів. Запропоновано для визначення впливу результатів виконання інвестиційного енергозберігаючого проекту на енергоефективність підприємства використовувати нейромережеве прогнозування.

Spatially Arranged Sparse Recurrent Neural Networks for Energy Efficient Associative Memory.

The development of hardware neural networks, including neuromorphic hardware, has been accelerated over the past few years. However, it is challenging to operate very large-scale neural networks with low-power hardware devices, partly due to signal transmissions through a massive number of interconnections. Our aim is to deal with the issue of communication cost from an algorithmic viewpoint and study learning algorithms for energy-efficient information processing. Here, we consider two approaches to finding spatially arranged sparse recurrent neural networks with the high cost-performance ratio for associative memory. In the first approach following classical methods, we focus on sparse modular network structures inspired by biological brain networks and examine their storage capacity under an iterative learning rule. We show that incorporating long-range intermodule connections into purely modular networks can enhance the cost-performance ratio. In the second approach, we formulate for the first time an optimization problem where the network sparsity is maximized under the constraints imposed by a pattern embedding condition. We show that there is a tradeoff between the interconnection cost and the computational performance in the optimized networks. We demonstrate that the optimized networks can achieve a better cost-performance ratio compared with those considered in the first approach. We show the effectiveness of the optimization approach mainly using binary patterns and apply it also to gray-scale image restoration. Our results suggest that the presented approaches are useful in seeking more sparse and less costly connectivity of neural networks for the enhancement of energy efficiency in hardware neural networks.

Exploration of VCSEL ultra-low biasing scheme for pulse generation

The generation of optical pulses at ultra low bias level, thus low energy cost, is explored in a commercial microcavity semiconductor laser in view of testing the principle of energy efficient information encoding in potential integrated schemes. Sequences of regular, highly nonlinear pulses with acceptable amplitude stability are obtained from a commercial device as potential sources of bits where the information is added by post-treatment (pulse removal). A discussion on the energy expenditure per bit is offered, together with the optimal frequency for pulse generation, which is found to lie slightly below the above-threshold value declared by the manufacturer.

Nonvolatile Electric‐Field Control of Ferromagnetic Resonance and Spin Pumping in Pt/YIG at Room Temperature

AbstractElectric‐field‐controlled magnetism is of importance in realizing energy efficient, dense and fast information storage and processing. Strain‐mediated converse magneto‐electric (ME) coupling between ferromagnetic and ferroelectric heterostructure shows promise for realizing electric‐controlled magnetism at room temperature and is attracting a number of recent investigations. However, such ME‐effect studies have mainly focus on magnetic metals. In this work, high quality yttrium iron garnet (Y3Fe5O12 (YIG)) films are deposited directly onto (100)‐oriented single‐crystal Pb (Mg1/3Nb2/3)0.7Ti0.3O3 (PMN‐PT) substrates by means of magnetron sputtering. The electric‐field‐induced polarization switching and lattice strain in the PMN‐PT substrate results in two distinct magnetization states in the YIG film that are nonvolatile and electrically reversible. Because of the direct contact between the YIG and the PMN‐PT substrate, an efficient ME coupling and an almost 90° rotation of the easy axis of the YIG film can be realized. Furthermore, the electric‐field‐controlled hysteresis loop‐like ferromagnetic resonance field shifts and spin pumping signals are observed in Pt/YIG/PMN‐PT heterostructures. Thus, the obstacle is overcome via growing high‐quality YIG thin films directly onto PMN‐PT substrates and an efficient manipulation of magnetism and pure spin current transport by electric field is thereby realized. These findings are instructive for future low‐power magnetic insulator‐based spintronic devices.

A study of citywide urban residential energy information system for the building energy efficiency management: a cluster model of seven typical cities in China

The lack of empirical data demonstrating the relationship between influencing factors and building energy performance is one of the primary barriers in energy efficiency management. A citywide residential energy information database and the data-based analytical methodology help increase the knowledge about the local real estate situation, explore energy efficiency opportunities and measures, financial investment, and market trend in the local building stocks, and make the reasonable policies as well. Few databases were established in USA and Europe only covering the building information and energy use, while there are lack of an indices system and database of building energy efficiency information in China. Therefore, in this study, a definition of urban residential energy information system is suggested, covering the parameters of building characteristics, household characteristics, possession and operation of domestic appliances, indoor thermal environment, climate condition, energy market, economic level, municipal infrastructure, and energy use consequence. Consequently, a database is developed to collect the raw data in seven typical cities in China. A classification model is established by Quantitative Theory III to classify and characterize the urban residential energy use systems into three different city groups, and suggestions are made to guide the energy efficiency work for different city groups. The case study is a good example to demonstrate the methodology and the analysis provided a helpful reference for the citywide building energy efficiency management.

Energy Efficient Designs of Sustainable Buildings in Urban Environment.

The Developing communities in their path for rapid development is endeavoring to make all necessary and appropriate measures to enhance the efficiency of energy utilization and increase the beneficiation of the energy resources. The energy production, transmission, distribution and utilization efficiency becomes a vital factor and measure of national development. Governmental organizations were established earlier to be responsible for energy planning and efficient utilization, information dissemination and capacity building as well as devising the necessary codes and standards. Throughout the Nation Energy resources are widely used and consumption rates are in general exceeding the International accepted values. Energy rationalization and audit exercises were developed and monitored by Governmental authorities, Universities and Research centers through the past two decades with a definitive positive energy reduction and beneficiation. The development of the relevant codes for Residential and Commercial Energy Efficiency in Building is underway through the governmental bodies responsible for the research, training and development in the building Technology sector and is the umbrella under which the National and Unified Arab Codes are developed and issued.

Nanomagnetic Particle-Based Information Processing

Understanding the physics of spintronic devices in the 3-nm size range can pave the way to next-generation energy-efficient information processing devices. To build a spin computer, a layer of 3-nm CoFe 2 O 4 nanoparticles was sandwiched as a central layer into the standard spin-transfer torque magnetic tunneling junction (STT-MTJ) stack. With further focused ion beam (FIB) trimming, a dual-layer junction consisting of one or more nanoparticles separating two CoFeB ferromagnetic layers was turned into a two-terminal spintronic device. The measured room-temperature electron transport through the device showed a staircase effect reminiscent of a single electron transport, which in addition depended on the relative orientations of the magnetic states of the ferromagnetic layers and the high-anisotropy ferrimagnetic nanoparticle. Besides having the staircase steps, the V-I curve indicated switching of the nanoparticles magnetization through the STT effect at currents of above 0.05 uA. The magnetoresistance (MR) curve of this device with the magnetic field applied perpendicular to the junction had an anomalous oscillatory field dependence in a relatively low field range of below 100 Oe.

Tailoring coupling between light and spin waves with dual photonic–magnonic resonant layered structures

We report on judiciously designed stratified periodic structures of magnetic dielectric materials with a localized defect layer, which are able to concurrently confine light and spin waves in the same ultra-small defect region for a long time period, thus resulting in enhanced photon–magnon interaction and large dynamic optical frequency shift. Our results for a specific realization of such a one-dimensional, so-called photomagnonic, crystal magnetized at saturation perpendicular to the interfaces, obtained by means of rigorous calculations using scattering-matrix techniques, show that the inherently weak coupling between visible/near-infrared light and GHz-frequency spin waves can be greatly increased leading to strong modulation of the optical field through multi-magnon exchange mechanisms. Such novel multifunctional composite materials offer a promising platform for tailoring light–spin-wave coupling in view of fast and energy-efficient spin-optical information processing applications.

Neuronal Synchronization Can Control the Energy Efficiency of Inter-Spike Interval Coding

The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that synchronization dynamically boosts sensory processing, others failed to find significant synchronization levels in such tasks. We attempt to understand both lines of evidence within a coherent theoretical framework. We conceptualize synchronization as an independent control parameter to study how the postsynaptic neuron transmits the average firing activity of a presynaptic population, in the presence of synchronization. We apply the Berger-Levy theory of energy efficient information transmission to interpret simulations of a Hodgkin-Huxley-type postsynaptic neuron model, where we varied the firing rate and synchronization level in the presynaptic population independently. We find that for a fixed presynaptic firing rate the simulated postsynaptic interspike interval distribution depends on the synchronization level and is well-described by a generalized extreme value distribution. For synchronization levels of 15% to 50%, we find that the optimal distribution of presynaptic firing rate, maximizing the mutual information per unit cost, is maximized at ~30% synchronization level. These results suggest that the statistics and energy efficiency of neuronal communication channels, through which the input rate is communicated, can be dynamically adapted by the synchronization level.

Spike-timing-dependent plasticity learning of coincidence detection with passively integrated memristive circuits

Spiking neural networks, the most realistic artificial representation of biological nervous systems, are promising due to their inherent local training rules that enable low-overhead online learning, and energy-efficient information encoding. Their downside is more demanding functionality of the artificial synapses, notably including spike-timing-dependent plasticity, which makes their compact efficient hardware implementation challenging with conventional device technologies. Recent work showed that memristors are excellent candidates for artificial synapses, although reports of even simple neuromorphic systems are still very rare. In this study, we experimentally demonstrate coincidence detection using a spiking neural network, implemented with passively integrated metal-oxide memristive synapses connected to an analogue leaky-integrate-and-fire silicon neuron. By employing spike-timing-dependent plasticity learning, the network is able to robustly detect the coincidence by selectively increasing the synaptic efficacies corresponding to the synchronized inputs. Not surprisingly, our results indicate that device-to-device variation is the main challenge towards realization of more complex spiking networks.

Thermally Tunable Hybrid Photonic Architecture for Nonlinear Optical Circuits

Integrated photonic systems are a leading solution for fast and energy-efficient information processing. We develop a thermally tunable hybrid photonic platform for implementation of coherent optical networks applicable to dedicated computing and machine learning. The hybrid architecture comprises gallium arsenide (GaAs) photonic crystal cavities, silicon nitride (SiNx) grating couplers and waveguides, and chromium (Cr) microheaters on an integrated photonic chip. We utilize the band-edge nonlinearity in GaAs photonic crystal cavity for switching at 6 ps time scale. The cavities are evanescently connected to a common bus waveguide, separating the computation and communication layers. To synchronize the operating frequency, we design metal microheaters that locally, continuously, and reversibly tune photonic crystal cavities to a common resonance. We demonstrate 7 nm tunability range with no significant quality factor deterioration. By coupling the free-space light to the photonic chip, we demonstrate the ...

Cross-layer efforts for energy-efficient computing: towards peta operations per second per watt

As Moore’s law based device scaling and accompanying performance scaling trends are slowing down, there is increasing interest in new technologies and computational models for fast and more energy-efficient information processing. Meanwhile, there is growing evidence that, with respect to traditional Boolean circuits and von Neumann processors, it will be challenging for beyond-CMOS devices to compete with the CMOS technology. Exploiting unique characteristics of emerging devices, especially in the context of alternative circuit and architectural paradigms, has the potential to offer orders of magnitude improvement in terms of power, performance, and capability. To take full advantage of beyond-CMOS devices, cross-layer efforts spanning from devices to circuits to architectures to algorithms are indispensable. This study examines energy-efficient neural network accelerators for embedded applications in this context. Several deep neural network accelerator designs based on cross-layer efforts spanning from alternative device technologies, circuit styles, to architectures are highlighted. Application-level benchmarking studies are presented. The discussions demonstrate that cross-layer efforts indeed can lead to orders of magnitude gain towards achieving extreme-scale energy-efficient processing.

A novel enhanced bat optimization based energy efficiency and imperfect channel state information in cooperative MIMO‐AF systems

SummaryEnergy Efficiency (EE) is a vital design standard for the future generation of communication systems. Similarly, cooperative communication is extremely efficient for improving the performance of such systems. Current research presents a relay precoding optimization algorithm in order to resolve EE problem in the Multiple‐Input‐Multiple‐Output (MIMO) Amplify‐And‐Forward (AF) Relay Networks containing correct Channel State Information (CSI) only. With the intension of focus on imperfect, this work presents a novel design of MIMO AF Relay Networks under Imperfect CSI (ICSI) by taking Channel Estimation (CE) errors and feedback delay errors, deprived of taking the straight link from source to destination. For this reason, we present a Hidden Semi Markov Model (HSMM) under ICSI, in which the source and destination based relay links are identified through destination. After that, we implement an Enhanced Bat Optimization (EBO) algorithm to enhance the EE of MIMO relay‐based non‐regenerative cooperative communication systems by means of improving the source and relay precoders by taking relay and direct links into consideration. Simulation outcomes prove that the EE‐ EBO optimization is capable of enhancing the outcomes of MIMO‐AF systems while matched up with direct/relay link with EE precoding optimization and precoding optimization algorithms.