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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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DOE OSTI2020

ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists

Recently, advances in machine learning and artificial intelligence have been playing more and more critical roles in a wide range of areas. For the last several years, industries have shown that how learning from data, identifying patterns and making decisions with minimal human intervention can be extremely useful to their business (e.g., image classification, recommending a product to a customer, finding friends in a social network, predicting customers actions, etc.). These success stories have been motivating scientists who study physics, chemistry, materials, medicine, and many other subjects, to explore a new pathway of utilizing machine learning techniques like regression and classification for their scientific activities. However, most existing machine learning tools, systems, and methodologies have been developed for programming experts but not for scientists (or any users) who have no or little knowledge of programming. ASCENDS is a toolkit that is developed to assist scientists (or any persons) who want to use their data for machine learning tasks, more specifically, correlation analysis, regression, and classification. ASCENDS does not require programming skills. Instead, it provides a set of simple but powerful CLI (Command Line Interface) and GUI (Graphic User Interface) tools for non-data scientists to be able to intuitively perform advanced data analysis and machine learning techniques. ASCENDS has been implemented by wrapping around opensource software including Keras, TensorFlow, and scikit-learn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Online Learning and Pricing for Network Revenue Management with Reusable Resources

We consider a price-based network revenue management problem with multiple products and multiple reusable resources. Each randomly arriving customer requests a product (service) that needs to occupy a sequence of reusable resources (servers). We adopt an incomplete information setting where the firm does not know the price-demand function for each product and the goal is to dynamically set prices of all products to maximize the total expected revenue of serving customers. We propose novel batched bandit learning algorithms for finding near-optimal pricing policies, and show that they admit a near-optimal cumulative regret bound of $O(J\sqrt{XT})$, where J, X, and T, are the numbers of products, candidate prices, and service periods, respectively. As part of our regret analysis, we develop the first finite-time mixing time analysis of an open network queueing system (i.e., the celebrated Jackson Network), which could be of independent interest. Our numerical studies show that the proposed approaches perform consistently well.

42 ENGINEERING↗
DOE OSTI2019

Integrated Solutions for Optimized Performance (ISOP) Final Technical Report

The goal of this project was to demonstrate technical feasibility of an integrated approach for deep energy retrofits by packaging innovative technologies with smart communicating controls that represent the next generation of energy efficiency. The integrated solutions for optimized performance (ISOP) package integrates (i) advanced lighting and plug load controls; (ii) intelligent daylight harvesting through automated self-powered shades and window films; (iii) advanced HVAC controls sequences (ASHRAE Guideline (GDL) 36); and (iv) fault detection and diagnosis (FDD) and continuous commissioning (CCx) using advanced analytics. These technologies address energy use across multiple building end uses that represent more than 60% of the energy consumption in all commercial buildings. The project was structured to be implemented over three budget periods: Budget Period 1 scope included site selection, project design, site-specific customization of technology packages, procurement of technologies, initiation of installation of technologies, the development of a measurement and verification plan and collection of pre-retrofit data collection. The first year go/no-go decision was based on securing host sites representing 250,000 sq. ft. of occupied operational spaces, savings analysis, technology procurement and initiation of installation. Budget Period 2 planned to complete technology installations and initiate data collection of post-retrofit performance data. The second year go/no-go was to be the completion of technology installations and commissioning, metering and data collecting to support the requirements laid out in site specific M&V plans. Budget Period 3 planned to collect and analyze post-retrofit performance data and provide data and reporting to support energy efficiency rebate programs. After the team completed activities planned for Budget Period 1, the team reached a Go/No-Go Decision Point. At that point, TRC recommended that DOE discontinue the project without prejudice due to challenges with securing demonstration sites to meet the full 250,000 sf of occupied operational spaces and DOE concurred. In Budget Period 1, the TRC team developed criteria to recruit and evaluate potential demonstration host sites. TRC worked with Princeton University, the project demonstration partner, to identify buildings on their campus as potential candidates for the demonstration. Following the selection of demonstration sites, the TRC team customized energy technology packages according to the needs and characteristics of each site. TRC defined technology specifications, identified vendors, and conducted analysis to estimate energy and cost savings potential. The project team then developed schedules for technology procurement processes and scheduled for installation at all selected demonstration sites. The project team worked with Princeton University and DOE to develop an approach to verify energy savings achieved through measurement and verification (M&V) 2.0 methods. Princeton University initiated open bids to procure the necessary materials and installation contractors. Bid results came back higher than estimates due to a couple of factors – lack of familiarity of the bidders with the proposed technologies and lack of local trained installers to execute the installation of these new measures. Due to the higher bids, projects no longer met the internal cost-effectiveness criteria used by Princeton to proceed with procurement of the full suite of technologies as proposed in ISOP. Princeton had already procured parts of the ISOP package as part of a campus-wide initiative for FDD and lighting retrofits, but with the higher costs for other ISOP components, Princeton could no longer commit to the full ISOP package on the selected sites. Based on this, the team reached the Go/No-Go decision point, where they decided not to proceed with the project. Princeton is separately installing portions of the ISOP package where they individually meet Princeton’s payback criteria but on a different schedule than would have been needed for the DOE ISOP project. The team has learned several lessons from project progress in the first budget period. The team will utilize these lessons in future projects, as should any team which proceeds with a project around the ISOP technology. The first lesson is that more information about the proposed sites is required earlier in the process (perhaps even at the proposal stage) in order to have a successful demonstration. Technical details not evident earlier in the process (such as the TLED limitations for ALCS) can derail project execution. The second lesson is that pricing of emerging technologies is highly variable due to lack of familiarity of local installers and distributor with the proposed technologies as well as alternate bids using products they were more familiar with, but that cost more than the ones proposed by TRC. Finally, the last major lesson is that the host site’s internal project criteria is of critical importance. Based on these higher installed costs and lack of an informed installer base for the products proposed for this project, the project does not meet Princeton’s simple payback goals of five years.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Advanced Control Methods for Particle Accelerators (ACM4PA) 2019

Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible. The purpose of this workshop was to consider tuning and optimization challenges of a wide range of particle accelerators including linear proton accelerators such as the Los Alamos Neutron Science Center (LANSCE), rings such as the Advanced Photon Source (APS) synchrotron, free electron lasers (FEL) such as the Linac Coherent Light Source (LCLS) and LCLS-II, the European X-ray Free Electron Laser (EuXFEL), the Swiss FEL, and the planned MaRIE FEL, and plasma wake- eld accelerators such as FACET, FACET-II, and AWAKE at CERN. One major challenge is an the ability to quickly create very high quality, extremely intense, custom current and energy pro le beams while working with limited real time non-invasive diagnostics and utilizing time-varying uncertain initial beam distributions and accelerator components. Currently, a few individual accelerator labs have been developing and applying their own diagnostics tools and custom control and ML algorithms for au- tomated machine tuning and optimization. The goal of this workshop was to bring together a group of accelerator physicists and accelerator related control and ML experts in order to de ne which controls and diagnostics would be most useful for existing and future accelerators and to create a plan for developing a new family of algorithms that can be shared and maintained by the community.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Demand Response Optimization and Management System for Real-TIme (DROMS-RT)

To design and demonstrate DROMS-RT, a highly distributed Demand Response Optimization and Management System for Real-Time (DROMS-RT) power flow control to support large scale integration of distributed renewable generation into the grid. AutoGrid developed a novel control and communications platform to allow highly dispatchable demand response (DR) services in time frames suitable for providing ancillary services to the transmission grid. These services will be substantially less expensive and more efficient than other forms of ancillary services options currently available to manage the intermittency associated with large-scale renewable integration. DROMSRT successfully leveraged Automated Demand Response (ADR) by fundamentally re-thinking the architecture of the DR platform from the ground up and by developing innovative new technologies in a number of areas related to DR. DROMS-RT leveraged the low-cost, open, interoperable DR signaling technology, OpenADR, and low-cost, internet-protocol based telemetry solutions to reduce the cost of hardware. This allowed DROMS-RT to provide dynamic price signals to millions of OpenADR clients. Statistically rigorous signal processing techniques were developed to reliably detect even small load reductions in the presence of noisy baseline profiles. Novel forecasting engines based on modern online machine learning algorithms enabled accurate individualized forecasts for customer loads in the presence of dynamic pricing signals, and a real-time decision engines enabled continuous optimization and optimal dispatch of DR resources across a large portfolio of heterogeneous loads that respond at varying time-scales. Moreover, the real-time optimization conducted by the decision engine can utilize grid physics to maximize load reduction at the transmission system in addition to the distribution sites, for more efficient grid operation. Finally, the Software-as-a-Service (SaaS) availability of the DROMS-RT platform has reduced the cost of deployment and enable participation of small commercial and residential customers in DR who otherwise would not be able to do so.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Further Support of the Development of Advanced Multilayer Optics Coatings for X-Ray Imaging

The Smithsonian Astrophysical Observatory (SAO) is working with Lawrence Livermore National Laboratory (LLNL) to develop Wolter-I optics for x-ray imaging applications at energies of 15-50 keV and above for National Nuclear Security Administration (NNSA) facilities. SAO work includes R&D on advanced multilayer coatings as well as fabrication and testing of Wolter multilayer coated optics. It also includes delivery of custom 3.05-meter focal length Wolter optics with response at energies of interest to Sandia National Laboratories and LLNL. The optics are fabricated using an electroform nickel replication technique which has been used to fabricate optics for X-ray astronomy satellites over the past two decades. This technique starts with a figured, polished mandrel from which the optics are replicated. To carry this technique over to fabricate optics for NNSA facilities, several additional barriers had to be overcome to deposit multilayer coatings on integral optics with radii as small as 25 mm. These breakthroughs allow fabrication of optics which meet the spatial and spectral specifications required by NNSA facilities. During this present contract period SAO delivered four custom optics to LLNL with spectral response at or near the Kα line of silver, 22.16 keV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Distributed Photovoltaic Economic Impact Analysis in Indonesia

Like other countries in the region, the Government of Indonesia aims to increase its use renewable energy in the near term from various technologies, including grid-connected distributed photovoltaics (DPV). While little DPV has been installed to date, the policy landscape has been shifting over the past few years with recent pronouncements from the state-run utility Perusahaan Listrik Negara (PLN) and the Ministry of Energy and Mines (MEMR) that have begun to provide a more supportive policy framework for the deployment of DPV. Nonetheless, many questions remain as to how DPV impacts customers, the utility, and the economy as a whole. This report presents a holistic view of DPV economic impacts in the Java-Bali region of Indonesia by assessing customer economic impacts, utility revenue impacts, and jobs and economic development impacts.

14 SOLAR ENERGY↗
DOE OSTI2020

An Overview of Behind-the-Meter Solar-Plus-Storage Regulatory Design: Approaches and Case Studies to Inform International Applications

Behind-the-meter energy storage systems paired with distributed photovoltaic (DPV) - with the capability to act as both generation and load - represent a unique and disruptive power sector technology capable of providing a range of important services to customers, utilities, and the broader power system. How should regulators, utilities, and policymakers manage the range of challenges and opportunities that increased behind-the-meter energy storage deployment will bring to the power system, in particular when these systems are paired with DPV? This report is intended to offer key regulatory considerations for facilitating DPV-plus-storage programs for retail customers; relevant cases from U.S. states are provided as examples of how novel regulatory issues related to behind-the-meter energy storage systems paired with DPV are being addressed in practice. At a high level, designing a regulatory framework that aligns DPV-plus-storage deployment with larger policy objectives requires thoughtful deliberation across a range of technical and economic issues. While this report attempts to segment many of these issues into distinct topics to enhance reader understanding, in reality, DPV-plus-storage regulatory issues are all closely integrated, and design decisions on a single aspect often have broader implications. With that in mind, this report outlines a series of steps that can be employed by regulators to approach DPV-plus-storage regulatory design.

14 SOLAR ENERGY↗
DOE OSTI2020

sCO 2 Brayton System Market Analysis

Supercritical CO 2 Brayton cycle systems (sCO 2 ) offer potential benefits over traditional steam plants. The changing economics of the electricity sector favors solar photovoltaic (PV), wind, and natural gas combined cycle (NGCC). Ultimately, the ability of sCO 2 systems to compete depends on the economics and ability to offer additional benefits to the market, such as the ability for dry cooling and their compact size. Updated results show that the projected LCOE for Brayton systems in the 100 to 300 MWe size range are between ${$}$44.8 and ${$}$56.1/MWh (4.48 and 5.61 cents/kWh). This report presents screening tools for assessing the potential market size and concludes that while at these LCOE estimates sCO 2 systems can compete directly against NGCC, there are many hurdles to commercialization, including the need to demonstrate long-term operations at low-cost and ability to quickly ramp for integration with intermittent resources. Additional customer discovery is necessary to fully understand the ability of this technology to solve customer problems that other technologies cannot.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Bat Impact Minimization Technology: An Improved Bat Deterrent for the Full Swept Rotor Area of Any Wind Turbine

The growth in the number of wind turbine generators has led to a significant number of fatal interactions with bat species. The need to reduce the number of bat fatalities while minimizing power losses is the greatest conservation challenge for wind energy development in parts of the country, according to the American Wind Wildlife Institute. Technological solutions that can also allow turbines to operate normally would generate the maximum electricity and avoid financial losses. Bats use echolocation to perceive their surroundings by listening to features of echoes from their high frequency vocal signals reflecting from targets. In this project, Frontier Wind built on previous research demonstrating that ultrasonic noise can mask echolocation and act as a repellent or deterrent to bat flight activity. Whereas the initial study only broadcast ultrasonic transmissions from the center of the turbine, the Strike Free™ system developed for this project extended the ultrasonic coverage to the entire area swept by the turbine blades. Frontier Wind designed the system components and their integration and then tested them in the lab and in the field at Pattern Energy’s Hatchet Ridge Wind Facility near Redding, California. The researchers used an acoustic model to determine the optimal configuration of transmitters along the blades to provide sound transmission coverage across the turbine rotor swept area volume. The custom ultrasonic transmitters were designed specifically for the echolocation frequencies of the four main bat species that have been shown to have died at Hatchet Ridge, although the transmitters can be customized for different frequencies as needed in other geographic locations. The Strike Free™ system shows promise for reducing bat fatalities, and the path to commercialization requires further testing to validate and optimize performance in the field.

17 WIND ENERGY↗
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2020

TA-55 Forensic Support Operations Cross-Training Exercise

As part of the annual FBI/LANL training schedule, a joint training exercise was conducted during the week of 10FEB2020 with FBI HEAT members and LANL Fissile Material Handlers (FMHs). The joint training exercise was conducted in a non-radiological area to reduce cost and ensure the test object would not be contaminated. The exercise test object was fabricated by LANL using surrogate materials to represent an object containing Special Nuclear Material (SNM). Working with Jim Blankenship and Kevin Swearingen, functional requirements of the test object included the following: unclassified, disassembly (to include screws), and moderately heavy. To meet the objectives, the test object was fabricated by welding a custom aluminum box (8” x 8” x 12”) with a lid which was secured by four (4) screws. The custom box housed a track and field shot put (16 lbs.) that was anchored by a hose clamp. The intent of the training was to disassemble the test object and conduct traditional forensic determinations on the parts. This lessons learned report documents all of the associated aspects related to the joint training effort.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Coupled Hydrothermal Extraction and Ligand-Associated Swellable Glass Media Recovery of Rare Earth Elements from Coal Fly Ash (Final Report)

Wayne State University (WSU) researchers, in collaboration with the University of California-Los Angeles (UCLA) and Los Alamos National Laboratory (LANL), have successfully developed a new sorbent media used in a process that concentrated the rare earth content in a coal fly ash sample from southeast MI by >350×, resulting in >13 wt% REO powder. The project developed a new DTPA-associated media that was used to concentrate total REEs. This project demonstrated a coupled hydrothermal extraction and solid-liquid recovery process that produced REO powder from raw fly ash while nearly eliminating the use of organic solvents. The project successfully: 1) identified a commercially viable ash supply with >$2.5 M in REO value being deposited monthly, 2) hydrothermally extracted >77% of REEs in coal fly ash (20% more than acid alone), 3) developed a new sorbent media that was used to concentrate REEs, 4) and engineered a process that resulted in a >13 wt% REO powder. The media also demonstrates a selectivity for mid and heavy REEs over Ce and La and the potential for use in separating individual rare earth elements. An invention disclosure for the sorbent media has been filed with WSU and a patent application will be submitted in the near future. The project examined the potential to couple hydrothermal leaching of coal fly ash with the engineering of a custom ligand-associated media to provide an organic solvent-free method of extracting and recovering REEs. Fly ash feedstock was collected from Detroit area coal-fired power plants, characterized for REE content, and subjected to a bench-top batch hydrothermal leaching/dissolution process inside custom-build pressure reactors at Los Alamos National Laboratory (LANL). This process applied a dissolution technique previously developed to process spent nuclear fuel and other nuclear materials. The modified ash was acidified and the resulting leachate was enriched with REEs along with Ca, Al, and Si. Ligands known to be effective in lanthanide/actinide separation were evaluated based on a series of criteria such as selectivity and association to organosilica through hydrophobicity. Batch experiments were conducted to establish the best conditions (e.g., pH, eluent, etc.) and best ligand systems for the effective extraction of REEs from the alkaline feed solution obtained from the hydrothermal leaching process. Once the organosilica-ligand extraction media was developed for REE concentration, an acidic solution was used to back extract and concentrate the REEs into a heavily REE-laden strip solution. The REEs in the strip solution were precipitated with oxalate to produce rare earth oxides.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Smart Microbial Cell Technology: A high-throughput platform to optimize biocatalysts

Los Alamos National Laboratory developed an ultra-high-throughput screening platform to engineer custom biocatalysts that enhance the rate of chemical reactions critical in pharmaceuticals, renewable energy, and environmental cleanup. Current methods to find biocatalysts are slow. This platform scans genetic variations to optimize a single enzyme or microbial cell to generate a product efficiently. It selects rare mutations needed for biocatalyst optimization orders of magnitude faster than current screening methods. A custom sensor reporter gene circuit causes cells to fluoresce when they are making the target product. When coupled to flow cytometry, a million biocatalyst variants can be screened in hours.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Adapting DESGW Single Epoch Image Differencing to the LSST Software Stack

As gravitational wave detections become an ever-increasing part of cosmological research, the Gravitational Waves Group of the Dark Energy Survey (DESGW) seeks to match and interpret optical observations for these short-lived, transient events.[1]To provide timely analysis for each follow up, DESGW has developed a custom Single Epoch Differencing Pipeline for processing optical data obtained from the Dark Energy Camera (DECam).[2]While effective, the pipeline is a custom design and thus requires extra maintenance and specialized knowledge to operate and modify at a time when new projects are taking precedence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Phase 1 NuScale SMR FOAK Nuclear Demonstration Readiness Project (Final Scientific/Technical Report)

The overarching objective of the Phase 1 NuScale SMR First-of-a-Kind (FOAK) Nuclear Demonstration Readiness Project was to enhance competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale small modular reactor (SMR). The scope of this Phase 1 project continued to advance the licensing and design maturity, particularly in those areas related to supporting customer readiness, supply chain integration, cost competitiveness, and cost confidence. This investment provided by the Government has accelerated development of these designs and technologies so that the existing domestic fleet of nuclear power plants remains viable and the most mature in the nuclear industry. The intent is to have the new, advanced U.S. designs be deployed as early 2026, and be globally competitive. As a part of the First-of-a-Kind Nuclear Demonstration Readiness Project, NuScale has been developing an advanced reactor design, leading the path for other development projects or complex technology advancements for existing plants that have significant technical and licensing risk. The NuScale Power team (NuScale) is advancing licensing, engineering, supply chain development, testing, and other required activities to enhance the innovation and competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale SMR. Specifically, NuScale is performing the following activities in Phase 1. Fully supporting the NRC review of the NuScale DCA to ensure approval of a final safety evaluation report by the end of 2020. Improving plant cost confidence and cost competitiveness through design and supply chain advancement, incorporation of constructability best practices, and margin recovery to increase plant power output. Accelerating design maturity, technology development, and operational program readiness to support a customer commitment for plant deployment. The Department of Energy (DOE) Office of Scientific and Technical Information (OSTI), a unit of the Office of Science, fulfills agency-wide responsibilities to collect, preserve, and disseminate both unclassified and classified scientific and technical information (STI) emanating from DOE-funded research and development (R&D) activities at DOE national laboratories and facilities and at universities and other institutions nationwide. This scientific and technical report provides summaries of the analyses and research that was performed by NuScale under this project that achieves the objective of disseminating information to the nuclear industry to ensure the innovations realized are shared for the benefit of the industry at large.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

National Security Research Center 2021 Strategic Plan

The National Security Research Center (NSRC) is a dynamic organization staffed with an expert, highly trained experts. The NSRC opened its doors in June 2019, making it one of the newest large organizations at Los Alamos National Laboratory (LANL). It supports a broad range of researchers within the LANL Weapons Program, customers across other National Nuclear Security Administration (NNSA) labs and sites, and partners in the Department of Defense (DoD). The maintenance and growth of the NSRC necessitate strategy and foresight. The NSRC leadership has developed a series of strategic goals through discussions with NSRC staff, customers, LANL leadership, and similar research institutions around the country to guide the NSRC leadership in moving the Center forward over the next five years.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

China’s Bid To Lead Artificial Intelligence Chip Development within the Decade

In 2017, the Chinese government announced an ambitious, broad strategy to become the global leader in artificial intelligence (AI) theories, technologies, and applications by 2030 and indicated that China’s ability to indigenously produce cutting-edge AI chips would be integral to its success. China’s goal to become a dominant producer of AI hardware within a decade is a bold undertaking because China faces domestic chip production challenges and fierce competition from US chip producers. Our review of Chinese AI chip product lines shows various levels where Chinese companies compete with global firms in the production chain. China lacks a robust indigenous AI chip production infrastructure, and the United States and its allies are tightening controls on the supply of advanced semiconductor manufacturing equipment (SME) and electronic design automation (EDA) software to China. In contrast to their Chinese counterparts, US companies operate in all areas of AI chip production and have consistently driven the development of new chip designs. AI chip production is a costly endeavor, and China’s chip producers currently lack the customer base to lead global AI chip development by the 2030 goal. An expanded customer base may help China attract the necessary expertise to bolster its AI chip production chain. This would also help Chinese producers make their investments in the requisite technology economically sustainable. Chinese researchers continue to pursue promising next-generation AI chip designs, such as neuromorphic computing-based architectures, which in the next five to ten years could position Chinese companies to make or contribute to key innovations in the field.

74 ATOMIC AND MOLECULAR PHYSICS↗