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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,171 records · Page 65

Efficiency Limits of Evaporative Fabric Drying Methods

Cloth drying is a major consumer of energy, and most drying is conducted by evaporative methods. The evaporative drying energy efficiency limit is commonly assumed to be 100%: one unit of latent heat removed per unit of energy expended. However, this ignores the “free drying” available from unsaturated ambient air and the possible role of heat pumping. We demonstrate that efficiency limits for evaporative drying are fundamentally related to both drying rate and ambient psychrometric conditions. A relationship among efficiency, drying rate, and ambient conditions is quantified for several evaporative drying technologies, and a comparison among evaporative technologies is provided. In addition, a comparison is provided between efficiency limits and state of the art device performance. This research will help guide future research in the most promising directions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Efficient light harvesting and photon sensing via engineered cooperative effects

Abstract Efficient devices for light harvesting and photon sensing are fundamental building blocks of basic energy science and many essential technologies. Recent efforts have turned to biomimicry to design the next generation of light-capturing devices, partially fueled by an appreciation of the fantastic efficiency of the initial stages of natural photosynthetic systems at capturing photons. In such systems extended excitonic states are thought to play a fundamental functional role, inducing cooperative coherent effects, such as superabsorption of light and supertransfer of photoexcitations. Inspired by this observation, we design an artificial light-harvesting and photodetection device that maximally harnesses cooperative effects to enhance efficiency. The design relies on separating absorption and transfer processes (energetically and spatially) in order to overcome the fundamental obstacle to exploiting cooperative effects to enhance light capture: the enhanced emission processes that accompany superabsorption. This engineered separation of processes greatly improves the efficiency and the scalability of the system.

42 ENGINEERING↗

CMS event processing multi-core efficiency status

In 2015, CMS was the first LHC experiment to begin using a multi-threaded framework for doing event processing. This new framework utilizes Intel’s Thread Building Block library to manage concurrency via a task based processing model. During the 2015 LHC run period, CMS only ran reconstruction jobs using multiple threads because only those jobs were sufficiently thread efficient. Recent work now allows simulation and digitization to be thread efficient. In addition, during 2015 the multi-threaded framework could run events in parallel but could only use one thread per event. Work done in 2016 now allows multiple threads to be used while processing one event. In this presentation we will show how these recent changes have improved CMS’s overall threading and memory efficiency and we will discuss work to be done to further increase those efficiencies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Efficient Data-Driven Geologic Feature Characterization from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm

Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency and subjective human factors. We developed a novel data-driven geological feature characterization approach based on pre-stack seismic measurements. Our characterization method employs an efficient and accurate machine learning method to extract useful subsurface geologic features automatically. Specifically, we use kernel ridge regression to account for the nonlinear relationship between seismic data and geological features. We moreover employ kernel tricks to avoid the explicit nonlinear mapping and infinite dimension of feature space. Yet, the conventional kernel ridge regression can be computationally prohibitive because of the large volume of seismic measurements. We employ a data reduction technique in combination with the conventional kernel ridge regression method to improve the computational efficiency and reduce memory usage. In particular, we utilize a randomized numerical linear algebra technique, named Nyström method, to effectively reduce the dimensionality of the feature space without compromising the information content required for accurate characterization. We provide thorough computational cost analysis to show the efficiency of our new geological feature characterization methods. We validate the performance of our method in characterizing geologic fault zones because faults play an important role in various subsurface applications. Our numerical examples demonstrate that our new characterization method significantly improves the computational efficiency while maintaining comparable accuracy. Interestingly, we demonstrate that our approach yields a speedup ratio on the order of ~102 to ~103 in a multicore computational environment.

58 GEOSCIENCES↗

Simple, efficient and open-source CRISPR/Cas9 strategy for multi-site genome editing in Populus tremula × alba

Although the CRISPR/Cas9 system has been successfully used for crop breeding, its application remains limited in forest trees. Here, we describe an efficient gene editing strategy for hybrid poplar, (Populus tremula × alba INRA clone 717-1B4) based on the Golden Gate MoClo cloning. To test the system efficiency for generating single gene mutants, two single guide RNAs (sgRNAs) were designed and incorporated into the MoClo Tool Kit level 2 binary vector with the Cas9 expression cassette to mutate the SHORT ROOT (SHR) gene. Moreover, we also tested its efficiency for introducing mutations in two genes simultaneously by expressing one sgRNA targeting a single site of the YUC4 gene and the other sgRNA targeting the PLT1 gene. For a robust evaluation of the approach, we repeated the strategy to target the LBD12 and LBD4 genes simultaneously, using an independent construct. We generated hairy roots by Agrobacterium rhizogenes-mediated leaf transformation. Sequencing results confirmed the CRISPR/Cas9-mediated mutation in the targeted sites of PtaSHR. Biallelic and homozygous knockout mutations were detected. A deletion spanning both target sites and small insertions/deletions were the most common mutations. Out of the 22 SHR alleles sequenced, 21 were mutated. The phenotype’s characterization showed that transgenic roots with biallelic mutations for the SHR gene lacked a defined endodermal single cell layer, suggesting a conserved gene function similar to its homolog in Arabidopsis Arabidopsis thaliana (L.) Heynh. Sequencing results also revealed the high efficiency of the system for generating double mutants. Biallelic mutations for both genes in the yuc4/plt1 and lbd12/lbd4 roots were detected in three (yuc4/plt1) and two (lbd12/lbd4) out of four transgenic roots evaluated. A small deletion or a single nucleotide insertion at the single target site was the most common mutations. This CRISPR/Cas9 strategy arises as a rapid, simple and standardized gene-editing tool to evaluate the gene role in essential developmental programs such as radial cell differentiation of poplar roots.

59 BASIC BIOLOGICAL SCIENCES↗

Advancing quantum simulations of the nuclear shell model with Gray-code–based resource-efficient protocols

Background: Some of the computational limitations in solving the nuclear many-body problem could be overcome by utilizing quantum computers. The nuclear shell-model calculations providing deeper insights into the properties of atomic nuclei are one such case with high demand for resources, as the size of the Hilbert space grows exponentially with the number of particles involved. Quantum algorithms are being developed to overcome these challenges and advance such calculations. Purpose: To develop quantum circuits for the nuclear shell-model, leveraging the capabilities of noisy intermediate-scale quantum (NISQ) devices. Here, we aim to minimize resource requirements (specifically in terms of qubits and gates) and strive to reduce the impact of noise by employing relevant mitigation techniques. Methods: We achieve noise resilience by designing an optimized Ansatz for the variational quantum eigensolver (VQE) based on Givens rotations and incorporating qubit-ADAPT-VQE in combination with variational quantum deflation (VQD) to compute ground and excited states, incorporating the zero-noise extrapolation mitigation technique. Furthermore, the qubit requirements are significantly reduced by mapping the basis states to qubits using Gray-code encoding and generalizing transformations of fermionic operators to efficiently represent many-body states. Results: By employing the resource-efficient protocols, we achieve the ground and excited state energy levels of 38 Ar and 6 Li with better accuracy. These energy levels are presented for noiseless simulations, noisy conditions, and after applying noise mitigation techniques. Results are compared for Jordan-Wigner and Gray-code encoding using VQE, qubit-ADAPT-VQE, and VQD. Conclusions: Our work highlights the potential of resource-efficient protocols to leverage the full potential of NISQ devices in scaling the nuclear shell model calculations, offering a pathway toward more complex quantum simulations in nuclear physics. This approach establishes a framework for studying other nuclear systems with improved quantum resource efficiency, marking a significant advancement in applying quantum computing to realistic nuclear physics applications.

Physics - Nuclear physics and radiation physics↗

Efficient electron cyclotron current drive regime for plasma current start-up in fusion reactors

We report an accessibility enhanced efficient fundamental X-mode electron cyclotron heating (ECH) current start-up regime was identified for a reactorlike toroidal magnetic field range which has more than 100 times higher current drive efficiency compared to more conventional ECH methods for the relevant start-up temperature range. Very high current drive efficiency is possible due to the strong cyclotron interaction only with unidirectional passing electrons constrained by the wave accessibility conditions. This efficient electron cyclotron current drive regime may help facilitate the design of innovative economical solenoid-free tokamak fusion reactor systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Observation of Efficient Lower Hybrid Current Drive at High Density in Diverted Plasmas on the Alcator C-Mod Tokamak

Here, efficient lower hybrid current drive (LHCD) is demonstrated at densities up to $\bar{n}_e$ ≈ 1.5 x 10 20 m –3 in diverted plasmas on the Alcator C-Mod tokamak by operating at increased plasma current - and therefore reduced Greenwald density fraction. This density exceeds the nominal “LH density limit” at $\bar{n}_e$ ≈ 1.0 x 10 20 m –3 reported previously, above which an anomalous loss of current drive efficiency was observed. The recovery of current drive efficiency to a level consistent with engineering scalings is correlated with a reduction in density shoulders and turbulence levels in the far scrape-off layer. Concurrently, rf wave interaction with the edge and/or scrape-off-layer plasma is reduced, as indicated by a minimal broadening of the wave frequency spectrum measured at the plasma edge. These results have important implications for sustaining steady-state tokamak operation and indicate a pathway forward for implementing efficient LHCD in a reactor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Does sink efficiency unequivocally characterize how grain boundaries impact radiation damage?

The role of grain boundaries in limiting irradiation damage in nanocrystalline materials is often correlated with the grain boundary sink efficiency. Here, we demonstrate on a tungsten material system (which has very distinct vacancy and interstitial mobilities) that sink efficiency does not unequivocally describe how grain boundaries impact irradiation damage. Rather, it reflects a particular defect diffusion equation that can change if any of the bulk conditions change. Even when denuded zone formation does not occur and grain boundaries have zero sink efficiencies, grain boundaries still impact the performance of nanocrystalline materials under irradiation by acting as a saturable defect storage site. However, denuded zone formation can occur under a necessary requirement of extra defect recombination at the grain boundaries (which, for example, is not possible when vacancy migration does not occur). These insights provide answers to several outstanding questions regarding the sink efficiency of a grain boundary and assist in parametrizing the role of grain boundaries in limiting irradiation damage in nanocrystalline materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Arithmetic Primitives for Efficient Neuromorphic Computing

Neuromorphic computing is steadily gaining popularity in many scientific and engineering disciplines. However, one of the biggest problems that has prevented widespread usage of neuromorphic computing is the lack of efficient encoding methods. Traditional encoding methods such as binning, rate encoding, and temporal encoding are based on unary encoding and generate a large number of spikes for certain applications, making them less energy efficient. Lack of better encoding methods has also prevented preprocessing operations from being carried out on neuromorphic computers. As a result, over 99% of the time can be spent on data preprocessing and data transfer operations in some cases, leading to an inefficient workflow. In this paper, we present preliminary results that would enable us to efficiently encode data and perform basic arithmetic operations on neuromorphic computers. First, we present a neuromorphic approach for the two’s complement encoding of numbers and leverage it to devise addition and multiplication circuits, which could be used in preprocessing operations on neuromorphic computers. We test our approach on the SuperNeuroMAT simulator. Our results indicate that two’s complement is a highly efficient encoding method in terms of time, space, and energy complexity and that the addition and multiplication circuits produce accurate results on two numbers having arbitrary precision.

Wurm, Ahna↗

A 194nW Energy-Performance-Aware loT SoC Employing a 5.2nW 92.6% Peak Efficiency Power Management Unit for System Performance Scaling, Fast DVFS and Energy Minimization

A self-powered IoT system-on-chip (SoC) reduces power to sub-μw and employs multiple power-management techniques to trade-off ultra-low power (ULP), higher performance, smaller energy harvester footprint, and longer operating lifetime. Minimum Energy Point Tracking (MEPT) [1]–[4] keeps an SoC operating at the minimum energy point (MEP) to enhance system lifetime. Previous sample-and-hold MEPT schemes need frequent voltage comparisons and a high-frequency clock that increases power [2]. Current-ratio-based MEPT relies on specialized CMOS technology for body-bias tuning [3]. A switched-capacitor-based MEPT can achieve energy minimization at a targeted performance [4], but it uses a 30MHz clock witμW power consumption and low power efficiency. For ULP IoT applications, SoCs need to have ultra-low quiescent power, high efficiency for energy delivery, performance scaling based on available energy, and energy minimization to increase system lifetime. In this work, we propose an ULP IoT SoC with a triple-mode power management unit (PMU) that integrates energy-performance scaling, event-driven fast DVFS, and MEPT features to improve the system energy efficiency, as shown in Fig. 13.8.1. This work achieves a minimum 194nW power consumption for the SoC and 5.2nW quiescent power for the PMU with a 92.6% peak efficiency and >10 4 dynamic range. The timing waveform in Fig. 13.8.1 (bottom), demonstrates the transition of the three modes including energy aware (EA), performance aware (PA), and MEPT based on event priority and input voltage level which reflects the energy availability. As such, the system energy consumption and performance could be well-balanced based on both the input and output conditions.

self-powered IoT system-on-chip (SoC)↗

Energy-Efficient and Secure S-Box circuit using Symmetric Pass Gate Adiabatic Logic

Differential Power Analysis (DPA) attack is considered to be a main threat while designing cryptographic processors. In cryptographic algorithms like DES and AES, S-Box is used to indeterminate the relationship between the keys and the cipher texts. However, S-box is prone to DPA attack due to its high power consumption. In this paper, we are implementing an energy-efficient 8-bit S-Box circuit using our proposed Symmetric Pass Gate Adiabatic Logic (SPGAL). SPGAL is energy-efficient as compared to the existing DPAresistant adiabatic and non-adiabatic logic families. SPGAL is energy-efficient due to reduction of non-adiabatic loss during the evaluate phase of the outputs. Further, the S-Box circuit implemented using SPGAL is resistant to DPA attacks. The results are verified through SPICE simulations in 180nm technology. SPICE simulations show that the SPGAL based S-Box circuit saves upto 92% and 67% of energy as compared to the conventional CMOS and Secured Quasi-Adiabatic Logic (SQAL) based S-Box circuit. From the simulation results, it is evident that the SPGAL based circuits are energy-efficient as compared to the existing DPAresistant adiabatic and non-adiabatic logic families. In nutshell, SPGAL based gates can be used to build secure hardware for lowpower portable electronic devices and Internet-of-Things (IoT) based electronic devices.

Kumar, Dinesh↗

Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level

Neuromorphic computing is non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing contributes effectively in this research. Here in this paper, we present a memristive neuromorphic system for improved power and area efficiency. Our particular mixed-signal approach implements neural networks with spiking events in a synchronous way. Moreover, the use of nano-scale memristive devices saves both area and power in the system. We also provide device-level considerations that make the system more energy-efficient. The proposed system additionally includes synchronous digital long term plasticity, an online learning methodology that helps the system train the neural networks during the operation phase and improves the efficiency in learning considering the power consumption and area overhead.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Monolithic Two-Terminal All-Perovskite Tandem Solar Cells with Power Conversion Efficiency Exceeding 21%

Monolithic two-terminal (2-T) all-perovskite tandem solar cells are a promising candidate for the next generation solar cells with ultrahigh efficiency and low fabrication cost. Here, we report on the fabrication of 2-T all-perovskite tandem solar cells consisting of solution-processed wide-bandgap and low-bandgap perovskite subcells connected by a vacuum processed interconnection layer. We employed a bulk-passivation strategy to enlarge the grain size, increase carrier mobilities, reduce electronic disorder, and suppress trap-assisted recombination in the low bandgap mixed Sn-Pb perovskite films, which leads to improved performance of low bandgap perovskite solar cells with an absorber thickness over 750 nm. This advance in high-quality low-bandgap perovskite layers enables the fabrication of efficient 2-T all-perovskite solar cells with power conversion efficiencies of more than 21% and decent stability. Our approach provides a suitable pathway to realize ultra-high efficiency 2-T all-perovskite tandem solar cells.

14 SOLAR ENERGY↗

High Efficiency 6-Junction Solar Cells for the Global and Direct Spectra

We show 6-junction inverted metamorphic solar cells with high efficiencies under both the global and direct spectrum, and discuss improvements to device components. High voltage AlGaInP subcells are demonstrated on GaAs substrates miscut 2° towards (111)B by using Sb surfactant to reduce atomic ordering. This miscut enables high voltage and low dislocation density GaInAs subcells by using atomically-ordered GaInP-based graded buffers. One-sun efficiencies of 39.2 ± 1.3% under the global spectrum and 39.4 ± 1.1% direct spectrum have been demonstrated by using these high voltage subcell components. For high efficiency under the concentrated direct spectrum, low resistance is also necessary, which requires a challenging and nonintuitive optimization of tunnel junctions and heterobarriers. Increasing the thickness of a (Al)GaInAs spacer layer between the back surface fields (BSF) and tunnel junctions (TJ) of latticemismatched subcells reduces nonlinear resistance, which implies a detrimental interaction between the BSF and TJ. Concentrator devices with optimized spacer layers show reduced effective resistance and maintain fill factor > 75% at 1100 suns. Device efficiencies under the concentrated direct spectrum peak at 47.1 ± 3.2% at 143 suns.

41 EE - Solar Energy Technologies Office (EE-4S)↗

12.3% Efficient Lifted-Off and Reconstructed As-Doped CdTe Thin Film Solar Cell

CdTe:As devices grown by MOCVD in the superstrate configuration have been reconfigured to a substrate structure, by employing a cleaving and reconstruction technique. Indium and aluminium doped Zinc oxide (IZO and AZO) layers were used as the transparent front interface without a metal grid. A substrate efficiency of 12.3% was realized with AZO front contact, retaining 80% of the superstrate device efficiency and an impressive approximately 99% of the open-circuit voltage. The IZO-based substrate device on the other hand performed at approximately 69 % retained efficiency. The crucial role of front interfaces is highlighted by the two contacts used here. The results in this work show promise for the development of highly efficient substrate CdTe:As devices.

II-VI semiconductor materials↗

Parallel elastic elements improve energy efficiency on the STEPPR bipedal walking robot

This study describes how parallel elastic elements can be used to reduce energy consumption in the electric motor driven, fully-actuated, STEPPR bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively-engaging springs for hip adduction and ankle flexion predict benefits for three different flat ground walking gaits: human walking, human-like robot walking and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a fully actuated bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data shows that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dynamic Virtual Chunks: On Supporting Efficient Accesses to Compressed Scientific Data

Data compression could ameliorate the I/O pressure of data-intensive scientific applications. Unfortunately, the conventional wisdom of naively applying data compression to the file or block brings the dilemma between efficient random accesses and high compression ratios. File-level compression barely supports efficient random accesses to the compressed data: any retrieval request need trigger the decompression from the beginning of the compressed file. Block-level compression provides flexible random accesses to the compressed blocks, but introduces extra overhead when applying the compressor to each and every block that results in a degraded overall compression ratio. This paper extends our prior work that introduces virtual chunks offering efficient random accesses to the compressed scientific data without sacrificing the compression ratio. Virtual chunks are logical blocks pointed at by appended references without breaking the physical continuity of the file content. These references allow the decompression to start from an arbitrary position (efficient random accesses), while no per-block overhead is introduced because the file’s physical entirety is retained (high compression ratio). One limitation of virtual chunk is it only supports static references. This paper presents the algorithms, analysis, and evaluations of dynamic virtual chunks to deal with the cases where the references are updated dynamically.

I/O compression performance optimization↗