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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Van der Waals heterostructures

The integration of dissimilar materials into heterostructures has become a powerful tool for engineering interfaces and electronic structure. The advent of two-dimensional (2D) materials brought unprecedented opportunities for novel heterostructures in the form of van der Waals stacks, laterally stitched 2D layers, and more complex layered and 3D architectures. This Primer provides an overview of state-of-the-art methodologies for producing such van der Waals heterostructures, focusing on the two fundamentally different strategies, top-down deterministic assembly and bottom-up synthesis. For both approaches, successful techniques, advantages, and limitations are discussed. As important as the fabrication itself is the characterization of the resulting engineered materials, for which a range of analysis techniques covering structure, composition, and emerging functionality are highlighted. Examples of the properties of artificial van der Waals structures include optoelectronics and plasmonics, twistronics, and unique functionality arising from the generalization of van der Waals assembly from 2D- to 3D-crystalline components. Lastly, current issues of reproducibility, limitations, and opportunities for future breakthroughs in terms of enhanced homogeneity, interfacial purity, feature control, and ultimately orders of magnitude increased complexity of van der Waals heterostructures are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solving disorder in (3D) real space: a comparative study of the three-dimensional difference pair distribution function and atomic resolution holography reconstructions

The quantitative analysis of local ordering principles in disordered crystalline systems has gained much attention over the past few years, as it is often considered crucial for optimizing material functionality. This development has been driven by significant advancements in computational and experimental methods, which have led to the establishment and widespread use of various analytical techniques. In this study, we perform model calculations to compare the effectiveness of atomic resolution holography and three-dimensional difference pair distribution function analysis (3D-ΔPDF). Using Cu 3 Au as a model system, we demonstrate an approach to derive local order parameters quantitatively and show that both techniques are well suited to quantifying chemical short-range order correlations and local bond-distance variations. By evaluating the strengths and limitations of both techniques, we advocate for their combined use to solve complex short-range order problems accurately.

3D-ΔPDF↗
DOE OSTI2021

Calculation of the Thermodynamic Voltage Limit of CdSeTe Solar Cells

The first step to understand the origin of losses in any photovoltaic solar cell is to determine the fundamental thermodynamic efficiency and voltage limits of such a device. In this contribution, we detail techniques to calculate the voltage limit in the case of cadmium selenium telluride (CdSeTe) solar cells, and how approaches based on bandgap alone—i.e., the Shockley-Queisser approach with step-function absorptance—can overestimate the thermodynamic open-circuit voltage limit Voc,ideal . This is particularly true for arsenic-doped samples, which tend to exhibit below-bandgap absorptance.

absorptance↗
DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Relaxing Direct Ptychography Sampling Requirements via Parallax Imaging Insights

Direct ptychography enables the retrieval of information encoded in the phase of an electron wave passing through a thin sample by deconvolving the interference effects of a converged probe with known aberrations. Under the weak phase object approximation, this permits the optimal transfer of information using noniterative techniques. However, the achievable resolution of the technique is traditionally limited by the probe step size—setting stringent Nyquist sampling requirements. At the same time, parallax imaging has emerged as a dose-efficient phase technique which relaxes sampling requirements and enables scan-upsampling. Here, we formulate parallax imaging as a quadratic approximation to part of the direct ptychography kernel and use this insight to enable upsampling in direct ptychography. We validate our analytical results numerically using simulated and experimental reconstructions.

direct ptychography, parallax imaging, scan Nyquis↗
DOE OSTI2024

Cryo-EM sample preparation for high-resolution structure studies

High-resolution structures of biomolecules can be obtained using single-particle cryo-electron microscopy (SPA cryo-EM), and the rapidly growing number of structures solved by this method is encouraging more researchers to utilize this technique. As with other structural biology methods, sample preparation for an SPA cryo-EM data collection requires some expertise and an understanding of the strengths and limitations of the technique in order to make sensible decisions in the sample-preparation process. Here, in this article, common strategies and pitfalls are described and practical advice is given to increase the chances of success when starting an SPA cryo-EM project.

36 MATERIALS SCIENCE↗
DOE OSTI2022

When not to use machine learning: A perspective on potential and limitations

Abstract The unparalleled success of artificial intelligence (AI) in the technology sector has catalyzed an enormous amount of research in the scientific community. It has proven to be a powerful tool, but as with any rapidly developing field, the deluge of information can be overwhelming, confusing, and sometimes misleading. This can make it easy to become lost in the same hype cycles that have historically ended in the periods of scarce funding and depleted expectations known as AI winters. Furthermore, although the importance of innovative, high-risk research cannot be overstated, it is also imperative to understand the fundamental limits of available techniques, especially in young fields where the rules appear to be constantly rewritten and as the likelihood of application to high-stakes scenarios increases. In this article, we highlight the guiding principles of data-driven modeling, how these principles imbue models with almost magical predictive power, and how they also impose limitations on the scope of problems they can address. Particularly, understanding when not to use data-driven techniques, such as machine learning, is not something commonly explored, but is just as important as knowing how to apply the techniques properly. We hope that the discussion to follow provides researchers throughout the sciences with a better understanding of when said techniques are appropriate, the pitfalls to watch for, and most importantly, the confidence to leverage the power they can provide. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. However, the current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques, which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. In this work, an in situ NDE (INDE) system was engineered to detect subsurface flaws detected in X-Ray Computed Tomography (XCT) directly from process monitoring data. A multilayer, multimodal data input allowed the INDE system to detect numerous subsurface flaws in the size range of 200–1000µm using a novel human-in-the-loop annotation procedure. Furthermore, a framework was established for generating probability-of-detection (POD) and probability-of-false-alarm (PFA) curves compliant with NDE standards by systematically comparing instances of detected subsurface flaws to post-build XCT data. Here, we also introduce for the first time in the AM in situ sensing literature the a 90/95 – the flaw size corresponding to a 90% detection rate on the lower 95% confidence interval of the POD curve. The INDE system successfully demonstrated POD capabilities commensurate with traditional NDE methods. Traditional ML performance metrics were also shown to be inadequate for assessing the ability of the INDE system’s flaw detection performance. It is the hope of the authors that future studies will adopt the POD and PFA approach outlined here to provide better insight into the utility of process monitoring for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Seeing in with X-rays: 4D Strain and Thermometry Measurements for Thermal-Mechanical Testing

Understanding temperature-dependent material decomposition and structural deformation induced by combined thermal-mechanical environments is critical for safety qualification of hardware under accident scenarios. Seeing in with X-rays elucidated the physics necessary to develop X-ray strain and thermometry diagnostics for use in optically opaque environments. Two parallel thermometry schemes were explored: X-ray fluorescence and X-ray diffraction of inorganic doped ceramics– colloquially known as thermographic phosphors. Two parallel surface strain techniques–Path-Integrated Digital Image Correlation and Frequency Multiplexed Digital Image Correlation–were demonstrated. Finally, preliminary demonstration of time-resolved digital volume correlation was performed by taking advantage of limited view reconstruction techniques. Additionally, research into blended ceramic-metal coatings was critical to generating intrinsic thermographic patterns for the future combination of X-ray strain and thermometry measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-throughput synthesis of high-entropy alloys via parallelized electric field assisted sintering

Materials discovery and design is an expensive and time-consuming process, though necessary to advance many engineering fields. In this work, a novel tooling design is utilized in conjunction with electric field assisted sintering (EFAS) to effectively create a new high-throughput synthesis technique: parallelized EFAS. Through this technique, a wide range of material compositions and geometries can be synthesized in parallel as isolated samples or as part of contiguous arrays. Multiple tooling designs are explored to examine both the flexibility and limitations of the technique. A series of increasing complex alloys is produced simultaneously using in situ alloying, beginning with pure Ni and adding equimolar constituents up to the septenary high-entropy alloy AlCoCrCuFeMnNi. Microstructural characterization reveals each sample is effectively fully dense and chemically homogenous while exhibiting phases in agreement with CALPHAD predictions. Scalability of parallelized EFAS is then experimentally demonstrated and the implications for materials discovery and automation are discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Quantum-amplified global-phase spectroscopy on an optical clock transition

Optical lattice clocks are at the forefront of precision metrology, operating near a standard quantum limit set by quantum noise. Harnessing quantum entanglement offers a promising route to surpass this limit; however, there are practical difficulties in terms of scalability and measurement resolution requirements. Here we adapt the holonomic quantum gate concept to develop a new Rabi-type ‘global-phase spectroscopy’ that uses the detuning-sensitive global Aharonov–Anandan phase19. With this approach, we can demonstrate quantum-amplified time-reversal spectroscopy on an optical clock transition that achieves directly measured 2.4(7) dB metrological gain and 4.0(8) dB improvement in laser noise sensitivity beyond the standard quantum limit. To this end, we introduce rotary echo to protect the dynamics from inhomogeneities in light–atom coupling and implement a laser-noise-cancelling differential measurement through symmetric phase encoding in two nuclear spin states. Our technique is not limited by measurement resolution, scales easily because of the global nature of entangling interaction and exhibits high resilience to typical experimental imperfections. As a result, we expect it to be broadly applicable to next-generation atomic clocks and other quantum sensors approaching the fundamental quantum precision limits.

Zaporski, Leon [Massachusetts Institute of Technol↗
DOE OSTI2025

Final Results of the M AJORANA D EMONSTRATOR ’s Search for Double-Beta Decay of 76 Ge to Excited States of 76 Se

76 Ge can 𝛽⁢𝛽 decay into three possible excited states of 76 Se , with the emission of two or, if the neutrino is Majorana, zero neutrinos. None of these six transitions have yet been observed. The M AJORANA D EMONSTRATOR was designed to study 𝛽⁢𝛽 decay of 76 Ge using a low background array of high purity germanium detectors. With 98.2 kg-y of isotopic exposure, the demonstrator sets the strongest half-life limits to date for all six transition modes. For 2⁢𝜈⁢𝛽⁢𝛽 to the 0$^+_1$ state of 76 Se , this search has begun to probe for the first time half-life values predicted using modern many-body nuclear theory techniques, setting a limit of 𝑇 1/2 > 1.5 × 10 24 y (90% CL).

Majorana neutrinos↗
DOE OSTI2021

The Digital Mirror Langmuir Probe: Field Programmable Gate Array Implementation of Real-Time Langmuir Probe Biasing

High bandwidth, high spatial resolution measurements of electron temperature, density and plasma potential are valuable for resolving turbulence in the boundary plasma of tokamaks. While conventional Langmuir probes can provide such measurements either their temporal or spatial resolution is limited: the former by the sweep rate necessary for obtaining I-V characteristics and the latter by the need to use multiple electrodes, as is the case in triple and double probe configurations. The Mirror Langmuir Probe (MLP) bias technique overcomes these limitations by rapidly switching the voltage on a single electrode cycling between three bias states, each dynamically optimised for the local plasma conditions. The MLP system on Alcator C-Mod used analog circuitry to perform this function, measuring Te, VF, and Isat at 1.1 MSPS. Recently, a new prototype digital MLP controller has been implemented on a Red Pitaya Field Programmable Gate Array (FPGA) board which reproduces the functionality of the original controller and performs all data acquisition. There is also the potential to provide the plasma parameters externally for use with feedback control systems. The use of FPGA technology means the system is readily customisable at a fraction of the development time and implementation cost. A second Red Pitaya was used to test the MLP by simulating the current response of a physical probe using C-Mod experimental measurements. This project is available as a git repository to facilitate extensibility (e.g. real-time control outputs, more voltage states) and scalability through collaboration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor’s scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhancing Time Synchronization in Smart Grid With White Rabbit: Theory, Architecture, and Challenges

The smart grid aims to provide economically efficient and sustainable power to consumers with high quality and security. However, the increasing integration of distributed renewable energy sources presents challenges for smart grid protection and control systems. Here, to enhance smart grid operations, this article introduces White Rabbit (WR) as a more precise and accurate time synchronization technique. To explore White Rabbit’s potential applications in the smart grid, this study first explains existing time synchronization techniques and their limitations, followed by an analysis of the role and importance of time synchronization in smart grids. A comprehensive survey is then conducted, covering the theories, principles, implementations, performances, and existing application cases of White Rabbit. The findings suggest that White Rabbit is a promising technique for smart grid deployment. However, several challenges remain on the path to large-scale implementation. These challenges are analyzed in detail, highlighting key areas for future research.

Liu, Yu [University of Tennessee, Knoxville, TN (U↗
DOE OSTI2025

Testing convolutional neural network based deep learning systems: a statistical metamorphic approach

Machine learning technology spans many areas and today plays a significant role in addressing a wide range of problems in critical domains,i.e., healthcare, autonomous driving, finance, manufacturing, cybersecurity,etc. Metamorphic testing (MT) is considered a simple but very powerful approach in testing such computationally complex systems for which either an oracle is not available or is available but difficult to apply. Conventional metamorphic testing techniques have certain limitations in verifying deep learning-based models (i.e., convolutional neural networks (CNNs)) that have a stochastic nature (because of randomly initializing the network weights) in their training. In this article, we attempt to address this problem by using a statistical metamorphic testing (SMT) technique that does not require software testers to worry about fixing the random seeds (to get deterministic results) to verify the metamorphic relations (MRs). We propose seven MRs combined with different statistical methods to statistically verify whether the program under test adheres to the relation(s) specified in the MR(s). We further use mutation testing techniques to show the usefulness of the proposed approach in the healthcare space and test two CNN-based deep learning models (used for pneumonia detection among patients). The empirical results show that our proposed approach uncovers 85.71% of the implementation faults in the classifiers under test (CUT). Furthermore, we also propose an MRs minimization algorithm for the CUT, thus saving computational costs and organizational testing resources.

Computer Science↗
DOE OSTI2020

Using simultaneous x-ray diffraction and velocity interferometry to determine material strength in shock-compressed diamond

We determine the strength of laser shock-compressed polycrystalline diamond at stresses above the Hugoniot elastic limit using a technique combining x-ray diffraction from the Linac Coherent Light Source with velocity interferometry. X-ray diffraction is used to measure lattice strains, and velocity interferometry is used to infer shock and particle velocities. These measurements, combined with density-dependent elastic constants calculated using density functional theory, enable determination of material strength above the Hugoniot elastic limit. Furthermore, our results indicate that diamond retains approximately 20 GPa of strength at longitudinal stresses of 150–300 GPa under shock compression.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analysis of multi-electron, multi-step homogeneous catalysis by rotating disc electrode voltammetry: theory, application, and obstacles

Rotating disc electrode (RDE) voltammetry has been widely adopted for the study of heterogenized molecular electrocatalysts for multi-step fuel-forming reactions but this tool has never been comprehensively applied to their homogeneous analogues. Here, the utility and limitations of RDE techniques for mechanistic and kinetic analysis of homogeneous molecular catalysts that mediate multi-electron, multi-substrate redox transformations are explored. Using the ECEC' reaction mechanism as a case study, two theoretical models are derived based on the Nernst diffusion layer model and the Hale transformation. Current–potential curves generated by these computational strategies are compared under a variety of limiting conditions to identify conditions under which the more minimalist Nernst Diffusion Layer approach can be applied. Based on this theoretical treatment, strategies for extracting kinetic information from the plateau current and the foot of the catalytic wave are derived. RDEV is applied to a cobaloxime hydrogen evolution reaction (HER) catalyst under non-aqueous conditions in order to experimentally validate this theoretical framework and explore the feasibility of RDE as a tool for studying homogeneous catalysts. Importantly, analysis of the foot-of-the-wave via this theoretical framework provides rate constants for elementary reaction steps that agree with those extracted from stationary voltammetric methods, supporting the application of RDE to study homogeneous fuel-forming catalysts. Lastly, obstacles encountered during the kinetic analysis of cobaloxime, along with the voltammetric signatures used to diagnose this reactivity, are discussed with the goal of guiding groups working to improve RDE set-ups and help researchers avoid misinterpretation of RDE data.

08 HYDROGEN↗