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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

AI-enhanced Codesign for Next-Generation Neuromorphic Circuits and Systems

This report details work that was completed to address the Fiscal Year 2022 Advanced Science and Technology (AS&T) Laboratory Directed Research and Development (LDRD) call for “AI-enhanced Co-Design of Next Generation Microelectronics.” This project required concurrent contributions from the fields of 1) materials science, 2) devices and circuits, 3) physics of computing, and 4) algorithms and system architectures. During this project, we developed AI-enhanced circuit design methods that relied on reinforcement learning and evolutionary algorithms. The AI-enhanced design methods were tested on neuromorphic circuit design problems that have real-world applications related to Sandia’s mission needs. The developed methods enable the design of circuits, including circuits that are built from emerging devices, and they were also extended to enable novel device discovery. We expect that these AI-enhanced design methods will accelerate progress towards developing next-generation, high-performance neuromorphic computing systems.

42 ENGINEERING↗
DOE OSTI2022

Machine Learning-driven Molecular Design for Therapeutic Discovery

The ongoing novel coronavirus pandemic (COVID-19) has highlighted the need for new therapeutics to counter the threat of emerging viral pathogens. The main proteases are a promising target for developing antiviral inhibitors. In this work, we utilized a novel combination of artificial intelligence-driven iterative design of covalent inhibitor candidates, physics-based computational modeling of protein-inhibitor interactions, and “All in One” Native MS biophysical assay screening and characterization of therapeutic candidates. With our existing expertise in hit generation using a particular scaffold as a starting point, we first generated tens of thousands of compounds that preserve the key scaffold. In order to optimize the candidates, we calculated about 136 descriptors consisting of 2D and 3D features for molecules targeting the SARS-CoV-2 Main protease (Mpro). These compounds were initially filtered according to properties and further sorted by predicted binding affinity using our automated docking modeling and machine learning methods. We tested a handful of candidates and identified two as inhibitors of Mpro with micromolar affinities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗
DOE OSTI2024

Science & Technology Review: October-November 2024 DarkStar

At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Implementing a Laser Stabilization System for Trapping Ca+ Ions: an Internship Reflection

At Lawrence Livermore National Laboratory, I contributed to a project developing 3D printed micro ion traps for quantum computing. I designed, implemented, and assessed a laser stabilization system that locked lasers to the frequencies required for calibrating our High Finesse WS8-10 wavelength meter and for laser cooling and trapping of Ca+ ions. I also programmed a Python interface for hardware communication, data collection, and statistical analysis. Additionally, I optimized and aligned laser beam paths, and I implemented a closed digital feedback loop using Proportional, Integral, and Derivative (PID) control parameters. I analyzed both the long-term and short-term behavior of our locked lasers and adjusted PID parameters to enhance performance. Furthermore, I used COMSOL to simulate the capacitance of a linear Paul trap design and predict our trap’s performance. The procedures I developed for the interface, analysis, and simulations will continue to support the ion trapping experiment after my appointment. I strengthened my skills in data analysis, Python coding, and optical alignment for laser systems. My confidence as a researcher grew, particularly in communicating my research. This experience taught me the importance of careful planning and consideration in research and solidified my desire to continue exploring novel quantum technology as an undergraduate

42 ENGINEERING↗
DOE OSTI2026

Assessing and Enabling Trustworthy Predictions for High-Consequence Decisions

Predictions from physics-based computational models provide critical information to inform high consequence decisions, e.g., engineering design decisions. The ability to assess the reliability of such predictions is therefore critical. However, to date, reliability assessment rely heavily on expert judgment and qualitative arguments. This report details the efforts of LDRD 233072 to develop quantitative methods to assess reliability of model predictions, especially in the context of simplifying assumptions that can impact their reliability.

42 ENGINEERING↗
DOE OSTI2021

High-precision quantum algorithms for partial differential equations

Quantum computers can produce a quantum encoding of the solution of a system of differential equations exponentially faster than a classical algorithm can produce an explicit description. However, while high-precision quantum algorithms for linear ordinary differential equations are well established, the best previous quantum algorithms for linear partial differential equations (PDEs) have complexity poly(1/ϵ), where ϵ is the error tolerance. By developing quantum algorithms based on adaptive-order finite difference methods and spectral methods, we improve the complexity of quantum algorithms for linear PDEs to be poly(d,log(1/ϵ)), where d is the spatial dimension. Our algorithms apply high-precision quantum linear system algorithms to systems whose condition numbers and approximation errors we bound. We develop a finite difference algorithm for the Poisson equation and a spectral algorithm for more general second-order elliptic equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Parallelization techniques for quantum simulation of fermionic systems

Mapping fermionic operators to qubit operators is an essential step for simulating fermionic systems on a quantum computer. We investigate how the choice of such a mapping interacts with the underlying qubit connectivity of the quantum processor to enable (or impede) parallelization of the resulting Hamiltonian-simulation algorithm. It is shown that this problem can be mapped to a path coloring problem on a graph constructed from the particular choice of encoding fermions onto qubits and the fermionic interactions onto paths. The basic version of this problem is called the weak coloring problem. Taking into account the fine-grained details of the mapping yields what is called the strong coloring problem, which leads to improved parallelization performance. A variety of illustrative analytical and numerical examples are presented to demonstrate the amount of improvement for both weak and strong coloring-based parallelizations. Our results are particularly important for implementation on near-term quantum processors where minimizing circuit depth is necessary for algorithmic feasibility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Adaptive variational simulation for open quantum systems

Emerging quantum hardware provides new possibilities for quantum simulation. While much of the research has focused on simulating closed quantum systems, the real-world quantum systems are mostly open. Therefore, it is essential to develop quantum algorithms that can effectively simulate open quantum systems. Here we present an adaptive variational quantum algorithm for simulating open quantum system dynamics described by the Lindblad equation. The algorithm is designed to build resource-efficient ansatze through the dynamical addition of operators by maintaining the simulation accuracy. We validate the effectiveness of our algorithm on both noiseless simulators and IBM quantum processors and observe good quantitative and qualitative agreement with the exact solution. We also investigate the scaling of the required resources with system size and accuracy and find polynomial behavior. Our results demonstrate that near-future quantum processors are capable of simulating open quantum systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Universal framework for simultaneous tomography of quantum states and SPAM noise

We present a general denoising algorithm for performing simultaneous tomography of quantum states and measurement noise. This algorithm allows us to fully characterize state preparation and measurement (SPAM) errors present in any quantum system. Our method is based on the analysis of the properties of the linear operator space induced by unitary operations. Given any quantum system with a noisy measurement apparatus, our method can output the quantum state and the noise matrix of the detector up to a single gauge degree of freedom. We show that this gauge freedom is unavoidable in the general case, but this degeneracy can be generally broken using prior knowledge on the state or noise properties, thus fixing the gauge for several types of state-noise combinations with no assumptions about noise strength. Such combinations include pure quantum states with arbitrarily correlated errors, and arbitrary states with block independent errors. This framework can further use available prior information about the setting to systematically reduce the number of observations and measurements required for state and noise detection. Our method effectively generalizes existing approaches to the problem, and includes as special cases common settings considered in the literature requiring an uncorrelated or invertible noise matrix, or specific probe states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗