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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-Intensity UV Exposure for the Rapid Screening of Silicon Photovoltaic Architectures

Advanced Si photovoltaic architectures incorporate different materials and processing pathways that influence degradation modes. Ultraviolet-induced degradation (UVID) is an understudied degradation mode for advanced cell architectures and is of increasing concern to industry due to growing adoption of UV-transparent encapsulation and bifacial technologies. In order to adopt new and evolving technologies confidently, novel component materials and processing techniques must be evaluated and designed for long-term stability, in addition to the conventional design focus on efficiency. In this work, a study protocol framework is presented for the rapid screening of unencapsulated devices against UVID. Unencapsulated passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) devices were aged under different UV irradiance intensities and measured via conventional nondestructive electrical characterization methods to assess performance degradation. Based on the results, protocol efficacy and recommendations for further study are discussed. As a result, this work is part of a broader effort to develop rapid screening processes that cut across architectures and exposure conditions to aid module manufacturers in vetting new materials choices for long-term stability.

Accelerated exposure↗
DOE OSTI2023

Interactive Power to Frequency Dynamics Between Grid-Forming Inverters and Synchronous Generators in Power Electronics-Dominated Power Systems

With increased attention on grid-forming inverters as a power system stabilizing device during high shares of inverter-based resource operations, there is a present need for a transparent and methodical investigation of the inverted and direct power to frequency control capabilities and impacts of these devices on emerging power systems. Here, analysis of the frequency dynamics of the droop-controlled grid-forming inverter and the synchronous generator illuminates the inverted active power-frequency relationship and the frequency response order reduction, forming the basis for novel, nonlinear frequency control approaches. Device-level electromagnetic transient domain simulations corroborate the order-reduction findings, establish that a properly designed dc-side system has a negligible impact on power transfer and will not impede frequency regulation, and confirm the primary frequency response improvement with nonlinear control. Simulations of the 9- and 39-bus test systems validate the order reduction and associated decoupling of the nadir and rate of change of frequency in larger networks. Oscillatory mode analysis confirms the grid-forming benefit of increased damping; decreased damping is observed at shares above 80%, but not at 100%. Finally, simulations on a validated Maui power system model with a 96% of inverter-based resources model yield a trend toward a first-order response.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing

High-performance computing (HPC) and the cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to computing resources, regardless of the underlying cloud or HPC service provider. Bridging HPC and cloud advancements, XaaS presents a unified architecture built on performance-portable containers. Here, our converged model concentrates on low-overhead, high-performance communication and computing, targeting resource-intensive workloads from climate simulations to machine learning. XaaS lifts the restricted allocation model of Function as a Service (FaaS), allowing users to benefit from the flexibility and efficient resource utilization of serverless computing while supporting long-running and performance-sensitive workloads from HPC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Isolating Insecurely: A Call to Arms for the Security and Privacy Community During the Time of COVID-19

The privacy question is one that has only begun to be addressed. While on one hand, many of the staunchest privacy advocates have argued for relaxation of privacy controls in order to develop better tests, “back to work” protocols, and vaccines and other treatments, the same advocates point out that any loss of privacy for the public good should be temporary, transparent, necessary, proportionate, and follow a due process. What should solutions look like for data gathering, sharing, use, and disposal; or for protocols requiring strong individual identity verification and validation?

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Verifying the Computational Integrity of Power Grid Controls with Zero-Knowledge Proof

The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources with rising dependence on communication infrastructure. A common assumption made for most existing distributed/decentralized controllers is that local controllers would faithfully follow the designated controller dynamics based on the data received from communication channels. However, with increased probability of cyberattacks on Operational Technology infrastructure, such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. In this work, we leverage a cryptography technology known as zero-knowledge scalable transparent arguments of knowledge (zk-STARK) to verify the computational integrity of power grid control algorithms, with projected linear dynamics-based control schemes as the initial proof-of-concept test case. The method presented here converts the cybersecurity challenge of data integrity for grid control into a subset of computational integrity.

computational integrity↗
DOE OSTI2025

Balancing Trade-offs: Adaptive Differential Privacy in Interpretable Machine Learning Models

In the advancing field of machine learning, balancing accuracy, interpretability, and privacy represents a significant challenge. The problem is exacerbated by the widespread deployment of pre-trained models locally in diverse applications, which could lead to various amounts of privacy leakage. Conventional Differential Privacy strategies, in which uniform noises are applied to model gradients, guarantee data privacy at the expense of accuracy and interpretability. This paper introduces a Feature-Sensitive Adaptive Differential Privacy (FADP) framework with a unique noise-adding strategy. Noises are adaptively added based on feature importance clustering, where important features are considered for interpretability. By employing a unique masking technique, FADP selectively preserves crucial features with minimal noise interference, maintaining accuracy while enhancing interpretability. The FADP framework addresses the limitations of traditional DP methods by preserving critical channels and improving interpretability — a vital requirement in machine learning applications that demand transparency in model decisions. Through comprehensive testing, FADP is shown to balance the trade-offs among accuracy, privacy, and interpretability, marking a substantial advancement in the field of privacy-preserving machine learning.

Farhad Riya, Farhin [University of Tennessee, Knox↗
DOE OSTI2020

LCOE*: Re-Thinking LCOE for Photovoltaic Systems

Solar industry is working towards reducing the levelized cost of energy (LCOE). The LCOE formulation includes various implicitly connected cost and physical design parameters. This entails complex cost analyses by economists, and electrical analysis and energy yield calculations of solar farms by device physicists/technologists. The standard formulation requires a constant exchange of information to optimize the design of a specific farm. In this paper, we present a fundamental reformulation of LCOE (in terms of LCOE*) to deconvolve the cost vs. energy yield analysis so that economists and technologists can work independently towards minimizing LCOE. We validate our LCOE* formulation by comparing LCOE calculated by the traditional vs. new method. We further provide a global analysis of LCOE* as an illustrative example. This LCOE* will accelerate new technology development (e.g. bifacial PV) by allowing a rapid and transparent analysis of its cost-performance trade-off.

14 SOLAR ENERGY↗
DOE OSTI2020

Understanding Measurement Artifacts Causing Inherent Cation Gradients in Depth Profiles of Perovskite Photovoltaics with TOF-SIMS

Time-of-flight secondary-ion mass spectrometry (TOF-SIMS) is one of the few techniques that can obtain chemical information from the hybrid organic-inorganic perovskite solar cells (PSCs) in one dimension (standard depth profiling), two dimensions (high-resolution 100-nm imaging), as well as three dimensions (tomography combining high-resolution imaging with depth profiling). We have very recently developed thermo-mechanical methods to cleave perovskite samples at the back transparent conducting oxide/PSC interface. This allowed for depth-profiling from the back of the device to the front. The resultant profiles answered the lingering question of the apparent A-site cation gradient typically seen in TOF-SIMS depth profiles. In fact, this gradient is a measurement artifact due to beam damage that the community should be informed of as TOF-SIMS data become more commonly employed. Methods of mitigating this artifact by altering the measurement conditions are also presented.

14 SOLAR ENERGY↗
DOE OSTI2020

Combinatorial Study of MZO Emitters for CdTe-Based Solar Cells

Precise band alignment at the front interface of CdTe-based solar cells is necessary to reduce photoexcited charge carrier recombination and to enable higher energy conversion efficiencies. Magnesium zinc oxide is not only transparent but also offers the ability to tune the conduction band offset with CdTe at the front of the device stack. In this work, we describe reactive sputtering of Mg 1-x Zn x O using metal targets and its application in CdTe photovoltaics. Combinatorial libraries of Mg 1-x Zn x O were created to tune the conduction band alignment for the optimal performance of CdTe solar cells. Band gap variation of more than 0.4 eV is achieved across a 3-inch substrate. Kelvin probe measurements demonstrate variance of work function across the substrate. Device performance is optimized at band gaps of 3.5 eV for the CdTe device processing conditions employed in this study.

14 SOLAR ENERGY↗
DOE OSTI2020

Luminescence from Poly-Si Films and its Application to Study Passivating-Contact Solar Cells

In recent years, polycrystalline silicon (poly-Si) based passivating-contact solar cells have received tremendous attention from the solar research community due to its excellent surface passivation and high carrier conductivity. However, the poly-Si films are not transparent to all wavelengths of the solar spectrum. There is often some parasitic absorption in these films. From a different standpoint, as they absorb some light, they can luminesce. This phenomenon provides us with unique opportunities to investigate optoelectronic properties of the films in a fast, contactless, and nondestructive manner. In this work, we report the luminescence phenomenon from poly-Si films used in passivating-contact solar cells. We then utilize this phenomenon to report a range of applications for solar cells including studies of carrier transport behaviors and hydrogenation inside the films.

14 SOLAR ENERGY↗
DOE OSTI2020

Oxidative Segregation of Group V Dopants in CdTe Solar Cells

Transparent conductive oxides are used in many technologies and it is important to understand their interfacial chemical reactions. Here, we use recently developed thermomechanical cleaving and X-ray photoelectron spectroscopy to probe oxidation states at the SnO 2 interface of CdTe solar cells. We show that tin oxide promotes the formation of nanometer-scale oxides of tellurium and sulfur, largely during CdCl 2 /O 2 activation. Surprisingly, in copper-doped devices, relatively low temperature anneals (180-260 degrees C) to diffuse and activate copper acceptors also cause significant oxidation changes at the front interface, providing a heretofore missing aspect of how back contact processes can modify device transport, recombination, and performance. For Group V-doped devices, this same oxidation process causes segregation of the dopants to the SnO 2 interface in their oxidized states, implying that adjacent regions in the absorber have been depleted of dopants. Intriguingly, we demonstrate that because of their layered, van der Walls-bonded crystal structure, spatially segregated Group V oxides may represent a mechanically weak layer in a finished device.

14 SOLAR ENERGY↗
DOE OSTI2021

Copper Electrode on Flexible Substrate by Intense Pulsed Light Sintering of Microsized Copper Particles

Metal electrodes deposited in a grid pattern onto flexible polymer substrates have been shown to be a viable alternative to replace indium tin oxide (ITO) as the transparent anode for organic photovoltaics. copper may be a better alternative in terms of cost and stability for large area low-cost solar modules, specifically on roll-to-roll platforms. These customized electrode patterns can be fabricated from copper nanoparticles through various printing techniques applicable to solution phase processing. The Intense Pulsed Light (IPL) technique has been used to sinter copper nanoparticles (~100nm) to fabricate conductive copper electrodes on flexible polymer substrates. However, compared to nanosized (~100 nm) copper particles, microsized (~2 um) copper is much cheaper. In this work, microsized (~2 um) copper is used to produce high conductive copper inks. The conductivity of the print can be adjusted through the use of surfactant. IPL sintering was optimized to obtain high conductivity copper films. In conclusion, several microscopic and electrical spectroscopic characterization techniques such as scanning electron microscopy (SEM), x-ray diffraction (XRD), 4-point probe resistivity measurements were employed to characterize the copper electrodes.

14 SOLAR ENERGY↗
DOE OSTI2023

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↗
DOE OSTI2025

Design of MARCO, the New Solenoidal Detector Magnet for the ePIC Experiment at BNL

MARCO is the new superconducting solenoid for ePIC, the general-purpose detector capable of delivering the full scientific scope of the Electron-Ion Collider at Brookhaven National Laboratory. Here, this 3.84 m long solenoid, with a bore diameter of 2.84 m, will provide a magnetic field of 2.0 T at the center with a nominal current of 4 kA at 4.5 K, for a total stored energy of 45 MJ. Its conductor is a NbTi Rutherford in Copper Channel (RICC), specially designed to stand the high mechanical loads induced by the magnetic field. Its copper stabilizer will assure the protection in case of quench. The coils are wound into six layers inside a thin external mandrel in brass, with a triple role of mechanical reinforcement, cryogenic support for the thermosiphon circuit and quench-back propagator. With a cold mass average radial thickness of just 7 cm, the magnet fulfills all the criterions of transparency for the particles directed to the hadronic calorimeter forecast around the cryostat. In this paper, the design of MARCO is presented, with a specific focus on the magnetic and quench analysis.

Calvelli, Valerio [Commissariat a l'Energie Atomiq↗
DOE OSTI2023

A Blockchain-Enabled Sustainable Safety Management Framework for Connected Vehicles

The notion of an intelligent transportation system (ITS) aims to boost the performance of transportation networks, which has gained more and more traction in both academic and commercial circles. ITS is a constantly evolving vision that combines cutting-edge transportation approaches with new information, communication, computers, and other technology. ITS should discover consequence routes to enhance the sustainability, safety, and trustworthiness of the entire transportation system utilizing emerging technologies. In this paper, a sustainable safety management framework for connected vehicles is proposed by integrating blockchain. It introduces smart transportation equipment called an AI-enabled vehicle smart device (AVSD) for vehicular communications. AVSD can reduce energy consumption by decreasing the computational costs in vehicular communications. Smart contracts are used to identify vehicles automatically and establish secure communication among vehicles and emergency service stations (ESSs) like hospitals, police stations, and fire stations. The experiment results show that the proposed framework provides a communication environment for sustainable safety and security using the introduced smart transportation device. In conclusion, the proposed blockchain-enabled sustainable safety management framework has the potential to improve safety and sustainability in the transportation industry by creating a secure, decentralized, and transparent platform for managing safety data and promoting safe and sustainable driving behaviors.

42 ENGINEERING↗
DOE OSTI2020

Customizable Scale-Out Key-Value Stores

Enterprise KV stores are often not well suited for HPC applications, and thus cumbersome end-to-end KV design customization is required to meet the needs of modern HPC applications. To this end, in this article we present bespoKV, an adaptive, extensible, and scale-out KV store framework. bespoKV decouples the KV store design into the control plane for distributed management and the data plane for local data store. For the control plane, bespoKVprovides pre-built modules, called controlets, supporting common distributed functionalities (e.g., replication, consistency, and topology) and their various combinations. This decoupling allows bespoKV to take a user-provided single-server KV store, called a datalet, and transparently enables a scalable and fault-tolerant distributed KV store service. The resulting distributed stores are also adaptive to consistency or topology requirement changes and can be easily extended for new types of services. Such specializations enable innovative uses of KV stores in HPC applications, especially for emerging applications that utilize KV-friendly workloads. We evaluate bespoKV in a local testbed as well as in a public cloud settings. Experiments show that bespoKV-enabled distributed KV stores scale horizontally to a large number of nodes, and performs comparably and sometimes 1.2× to 2.6× better than the state-of-the-art systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Automatic Generation of High-Performance Convolution Kernels on ARM CPUs for Deep Learning

In this work, we present FastConv, a template-based code auto-generation open source library that can automatically generate high-performance deep learning convolution kernels of arbitrary matrices/tensors shapes. FastConv is based on the Winograd algorithm, which is reportedly the highest performing algorithm for the time-consuming convolution layers of convolutional neural networks. ARM CPUs cover a wide range designs and specifications, from embedded devices to HPC-grade CPUs. The leads to the dilemma of how to consistently optimize Winograd-based convolution solvers for convolution layers of different shapes. FastConv addresses this problem by using templates to auto-generate multiple shapes of tuned kernels variants suitable for skinny tall matrices. As a performance portable library, FastConv transparently searches for the best combination of kernel shapes, cache tiles, scheduling of loop orders, packing strategies, access patterns, and online/offline computations. Auto-tuning is used to search the parameter configuration space for the best performance for a given target architecture and problem size. The experiments with layer-wise evaluation on the VGG--16 model confirms a 1.25x performance gains is got by tuning the Winograd library. Integrated comparison results shows 1.02x to 1.40x, 1.14x to 2.17x, and 1.22x and 2.48x speedup is achieved over NNPACK, Arm NN, and FeatherCNN on the Kunpeng 920 beside few cases. Furthermore, problem size performance portability experiments with various convolution shapes shows that FastConv achieves 1.2x to 1.7x speedup and 2x to 22x speedup over NNPACK and ARM NN inference engine using Winograd on Kunpeng 920 . CPU performance portability evaluation on the VGG--16 show an average speedup over NNPACK of 1.42x, 1.21x, 1.26x, 1.37x, 2.26x, and 11.02x is observed on Kunpeng 920, Snapdragon 835, 855, 888, Apple M1, and AWS Graviton2, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

funcX: Federated Function as a Service for Science

Here, funcX is a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. Unlike centralized FaaS systems, funcX decouples the cloud-hosted management functionality from the edge-hosted execution functionality. funcX's endpoint software can be deployed, by users or administrators, on arbitrary laptops, clouds, clusters, and supercomputers, in effect turning them into function serving systems. funcX's cloud-hosted service provides a single location for registering, sharing, and managing both functions and endpoints. It allows for transparent, secure, and reliable function execution across the federated ecosystem of endpoints-enabling users to route functions to endpoints based on specific needs. funcX uses containers (e.g., Docker, Singularity, and Shifter) to provide common execution environments across endpoints. funcX implements various container management strategies to execute functions with high performance and efficiency on diverse funcX endpoints. funcX also integrates with an in-memory data store and Globus for managing data that may span endpoints. We motivate the need for funcX, present our prototype design and implementation, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than 130000 concurrent workers. We show that funcX's container warming-aware routing algorithm can reduce the completion time for 3,000 functions by up to 61% compared to a randomized algorithm and the in-memory data store can speed up data transfers by up to 3x compared to a shared file system.

97 MATHEMATICS AND COMPUTING↗