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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Classical analog of quantum models in synthetic dimensions

We introduce a classical analog of quantum matter in ultracold molecule-synthetic or Rydberg atom-synthetic dimensions, by extending the Potts model to include interactions J 1 between atoms adjacent in both real and synthetic space and studying its finite-temperature properties. For intermediate values of J 1 , the resulting phases and phase diagrams are similar to those of the clock and Villain models, in which three phases emerge. There exists a sheet phase analogous to that found in quantum synthetic dimension models between the high-temperature disordered phase and the low-temperature ferromagnetic phase. Furthermore, we also employ machine learning to uncover nontrivial features of the phase diagram using the learning by confusion approach, which is able to discern several successive phase transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Magnetic bulk photovoltaic effect: Strong and weak field

Shift current and ballistic current have been proposed to explain the bulk photovoltaic effect (BPVE), and there have been experiments designed to separate the two mechanisms. These experiments are based on the assumption that under magnetic field, ballistic current can have a Hall effect while the shift current cannot, which is from some energy-scale arguments and has never been proven. A recent work [D. Hornung and R. von Baltz, Phys. Rev. B 103, 195203 (2021)] using quantum transport formalism achieves a conclusion that shift current indeed has a Hall current, seemingly contradicting the previous assumption and making the situation more confusing. Moreover, the behavior of BPVE under strong magnetic field is still unexplored. In this Letter, using a minimal two-dimensional tight-binding model, we carry out a systematic numerical study of the BPVE under weak and strong magnetic field by treating the field in a nonperturbative way. Further, our model clearly shows the appearance of the magnetically induced ballistic current along the transverse direction, which agrees with the previous predictions, and interestingly a sizable longitudinal response of the shift current is also observed, a phenomenon that is not captured by any existing theories where the magnetic field is treated perturbatively. More surprisingly, drastically different shift current is found in the strong-field regime, and the evolution from weak to strong field resembles a phase transition. We hope that our work could resolve the debate over the behavior of BPVE under magnetic field, and the strong-field behavior of shift current is expected to inspire more studies on the relation between nonlinear optics and quantum geometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Supervised and unsupervised machine learning of structural phases of polymers adsorbed to nanowires

Here, we identify configurational phases and structural transitions in a polymer nanotube composite by means of machine learning. We employ various unsupervised dimensionality reduction methods, conventional neural networks, as well as the confusion method, an unsupervised neural-network-based approach. We find neural networks are able to reliably recognize all configurational phases that have been found previously in experiment and simulation. Furthermore, we locate the boundaries between configurational phases in a way that removes human intuition or bias. This could be done before only by relying on preconceived, ad hoc order parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quasiprobabilistic Readout Correction of Midcircuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Quantum measurements are a fundamental component of quantum computing. However, on present-day quantum computers, measurements can be more error prone than quantum gates and are susceptible to nonunital errors as well as nonlocal correlations due to measurement crosstalk. While readout errors can be mitigated in postprocessing, this is inefficient in the number of qubits due to a combinatorially large number of possible states that need to be characterized. In this work, we show that measurement errors can be tailored into a simple stochastic error model using randomized compiling, enabling the efficient mitigation of readout errors via quasiprobability distributions reconstructed from the measurement of a single preparation state in an exponentially large confusion matrix. We demonstrate the scalability and power of this approach by correcting readout errors without matrix inversion on a large number of different preparation states applied to a register of eight superconducting transmon qubits. Moreover, we show that this method can be extended to midcircuit measurements used for active feedback via quasiprobabilistic error cancellation, and we demonstrate the correction of measurement errors on an ancilla qubit used to detect and actively correct bit-flip errors on an entangled memory qubit. Our approach enables the correction of readout errors on large numbers of qubits and offers a strategy for correcting readout errors in adaptive circuits in which the results of midcircuit measurements are used to perform conditional operations on nonlocal qubits in real time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Thermally induced structural competitiveness and metastability of body-centered-cubic iron under nonequilibrium conditions

The structure and stability of iron near melting at multi-megabar pressures are of significant interest in high pressure physics and earth and planetary sciences. While the body-centered cubic (BCC) phase is generally recognized as unstable at lower temperatures, its stability relative to the hexagonal close-packed (HCP) phase at high temperatures (approximately 0.5 eV) in the Earth’s inner core (IC) remains a topic of ongoing theoretical and experimental debate. Motivated by a series of studies attempting to understand the state of the IC and resulting in contradictory findings, we aim to explore the physical factors that may contribute to this confusion in a broader context. Our ab initio calculations show a significant drop in energy, the emergence of a plateau and a local minimum in the potential energy surface, and stabilization of all phonon modes of BCC iron at elevated electron temperatures (>1–1.5 eV). These effects increase the competition among the BCC, HCP, and the face-centered cubic (FCC) phases and lead to the metastability of the BCC structure. Furthermore, at pressure-temperature conditions relevant to the IC, we can expect substantial coexistence of FCC and HCP iron due to their similar free energies and low transition barrier (∼0.2 eV/atom), and the thermodynamic stability of BCC iron is enhanced by its substantial lattice vibration entropy. In conclusion, these findings provide a clear theoretical framework for understanding iron phase relations and solidification processes, both experimentally and in the IC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Illustrated formalisms for total scattering data: a guide for new practitioners

The total scattering method is the simultaneous study of both the real- and reciprocal-space representations of diffraction data. While conventional Bragg-scattering analysis (employing methods such as Rietveld refinement) provides insight into the average structure of the material, pair distribution function (PDF) analysis allows for a more focused study of the local atomic arrangement of a material. Generically speaking, a PDF is generated by Fourier transforming the total measured reciprocal-space diffraction data (Bragg and diffuse) into a real-space representation. However, the details of the transformation employed and, by consequence, the resultant appearance and weighting of the real-space representation of the system can vary between different research communities. As the worldwide total scattering community continues to grow, these subtle differences in nomenclature and data representation have led to conflicting and confusing descriptions of how the PDF is defined and calculated. This paper provides a consistent derivation of many of these different forms of the PDF and the transformations required to bridge between them. Some general considerations and advice for total scattering practitioners in selecting and defining the appropriate choice of PDF in their own research are presented. This contribution aims to benefit people starting in the field or trying to compare their results with those of other researchers.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Adversarial Sampling-Based Motion Planning

In this report there are many scenarios in which a mobile agent may not want its path to be predictable. Examples include preserving privacy or confusing an adversary. However, this desire for deception can conflict with the need for a low path cost. Optimal plans such as those produced by RRT* may have low path cost, but their optimality makes them predictable. Similarly, a deceptive path that features numerous zig-zags may take too long to reach the goal. We address this trade-off by drawing inspiration from adversarial machine learning. We propose a new planning algorithm, which we title Adversarial RRT*. Adversarial RRT* attempts to deceive machine learning classifiers by incorporating a predicted measure of deception into the planner cost function. Adversarial RRT* considers both path cost and a measure of predicted deceptiveness in order to produce a trajectory with low path cost that still has deceptive properties. We demonstrate the performance of Adversarial RRT*, with two measures of deception, using a simulated Dubins vehicle. We show how Adversarial RRT* can decrease cumulative RNN accuracy across paths to 10%, compared to 46% cumulative accuracy on near-optimal RRT* paths, while keeping path length within 16% of optimal. We also present an example demonstration where the Adversarial RRT* planner attempts to safely deliver a high value package while an adversary observes the path and tries to intercept the package.

42 ENGINEERING↗
DOE OSTI2023

1-D Convolutional Graph Convolutional Networks for Fault Detection in Distributed Energy Systems

This paper presents a 1-D convolutional and graph convolutional networks for fault detection in microgrids. The combination of 1-D convolutional neural networks (1D-CNN) and graph convolutional networks (GCN) helps extract both spatial-temporal correlations from the voltage measurements in microgrids. The fault detection scheme includes fault event detection, fault type and phase classification, and fault location. There are five neural network model training to handle these tasks. Transfer learning and fine-tuning are applied to reduce training efforts. The combined 1-D convolutional and graph convolutional networks (1D-CGCN) is compared with the traditional ANN structure on the Potsdam 13-bus microgrid dataset. The accuracy of 99.5%, 98.4%, 99.2%, and 95.5% are achieved in fault event detection, fault type classification, fault phase identification, and fault location respectively. The detailed confusion matrices of fault type and fault phase classification are provided for validation.

deep neural network↗
DOE OSTI2025

Clarifying Terminology in Microbial Ecology: A Call for Precision in Scientific Communication

The rapid evolution of microbiology as a field of research has led to the introduction of new terminology and the adaptation of existing terms. However, inconsistencies in the use of these terms, including variations across different scientific disciplines, can lead to confusion and miscommunication within the scientific community. This article discusses the importance of precise terminology in microbiome research, highlighting examples where terms have been misused or redefined without clear justification. We also present a list of frequently used terms in microbial ecology along with their specific definitions. We argue that the misuse of terminology can hinder scientific progress by creating ambiguity and misunderstanding. To address this, we propose a set of guidelines for the consistent use of key terms and provide clear definitions for some of the most commonly misused or newly introduced terms in the field. The definitions provided herein will also function as a guide for young researchers new to the field of microbial ecology. Accurate and consistent use of terminology is crucial for effective communication and collaboration in microbiology research. By adhering to standardised definitions, researchers can ensure that their work is clearly communicated and contributes meaningfully to the progress of science.

definitions↗
DOE OSTI2021

Beyond denitrification: The role of microbial diversity in controlling nitrous oxide reduction and soil nitrous oxide emissions

Many biotic and abiotic processes contribute to nitrous oxide (N 2 O) production in the biosphere, but N 2 O consumption in the environment has heretofore been attributed primarily to canonical denitrifying microorganisms. The nosZ genes encoding the N 2 O reductase enzyme, NosZ, responsible for N 2 O reduction to dinitrogen are now known to include two distinct groups: the well-studied Clade I which denitrifiers typically possess, and the novel Clade II possessed by diverse groups of microorganisms, most of which are non-denitrifiers. Clade II N 2 O reducers could play an important, previously unrecognized role in controlling N 2 O emissions for several reasons, including: (1) the consumption of N 2 O produced by processes other than denitrification, (2) hypothesized non-respiratory functions of NosZ as an electron sink or for N 2 O detoxification, (3) possible differing enzyme kinetics of Clade II NosZ compared to Clade I NosZ, and (4) greater nosZ gene abundance for Clade II compared to Clade I in soils of many ecosystems. Despite the potential ecological significance of Clade II NosZ, a census of 800 peer-reviewed original research articles discussing nosZ and published from 2013 to 2019 showed that the percentage of articles evaluating or mentioning Clade II nosZ increased from 5% in 2013 to only 22% in 2019. The census revealed that the slowly spreading awareness of Clade II nosZ may result in part from disciplinary silos, with the percentage of nosZ articles mentioning Clade II nosZ ranging from 0% in Agriculture and Agronomy journals to 32% in Multidisciplinary Sciences journals. In addition, inconsistent nomenclature for Clade I nosZ and Clade II nosZ, with 17 different terminologies used in the literature, may have created confusion about the two distinct groups of N 2 O reducers. Furthermore, we provide recommendations to accelerate advances in understanding the role of the diversity of N 2 O reducers in regulating soil N 2 O emissions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Chaos, percolation and the coronavirus spread: a two-step model

We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected, d 0 , grows exponentially to a saturation value, d ∞ . The typical growth time (aggressive spreading of the virus) is given by τ = 1/λ where λ is the Lyapunov exponent. After a time t crit determined by social distancing and/or other measures, the spread decreases exponentially analogous to nuclear decays and non-chaotic maps. Some countries, like China, S. Korea and Italy, are in this second stage while others including the USA are near the end of the growth stage. The model predicted 15,000 (±2250) casualties for the Lombardy region (Italy) at the end of the spreading around May 10, 2020. Without the quarantine, the casualties would have been more than 50,000, one hundred days after the start of the pandemic. Here, the data from the 50 US states are of very poor quality because of an extremely late and confused response to the pandemic, resulting unfortunately in a large number of casualties, more than 70,000 on May 6, 2020, and more than 170,000 on August 21, 2020. S. Korea, notwithstanding the high population density (511/km 2 ) and the closeness to China, responded best to the pandemic with 255 deceased as of May 6, 2020, and 301 on August 21, 2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Luke↗
DOE OSTI2022

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Lucas↗
DOE OSTI2021

An In-Depth Analysis of the Transformation of Tin Foil Anodes during Electrochemical Cycling in Lithium-Ion Batteries

Tin foils have an impressive lithium-storage capacity more than triple that of graphite anodes, and their adoption could facilitate a drastic improvement in battery energy density. However, implementation of a dense foil electrode architecture represents a significant departure from the standard blade-cast geometry with a distinct electrochemical environment, and this has led to confusion with regards to the first cycle efficiency of the system. In this work, we investigate the unique behavior of a tin active material in a foil architecture to understand its performance as an anode. We find shallow cycling of the foil results in an irreversible formation (< 40%) due to diffusional trapping, but intermediate and complete utilization allows for a remarkably reversible formation reaction (> 90%). This striking nonlinearity stems from an in situ transformation from bulk metal to porous electrode that occurs during formation cycles and defines electrode-level lithium-transport on subsequent cycles. As a result, an alternative cycling procedure for assessing the stability of foils is proposed to account for this chemomechanical effect.

25 ENERGY STORAGE↗
DOE OSTI2022

Assessment of the Phase-to-Ground Fault Apparent Admittance Method with Phase/Ground Boundaries to Detect Types of Electrical Faults for Protective Relays Using Signature Library and Simulated Events

Protective relays in electric power grids recognize the types of electrical faults in a few seconds. The most common detection method to detect the types of electrical faults is based on measuring the angle between the zero and negative sequence currents. However, it is not completely accurate because the phase-to-phase-ground and phase-to-ground electrical faults could have the same detection conditions. Therefore, engineers need to plot the events after an electrical fault to observe the nature of the incidents in detail. In this study, the phase-to-ground fault apparent (PGFA) admittance method with phase/ground boundaries identified the types of electrical faults located in distribution power lines and feeders. This method was based on measuring the PGFA admittance magnitudes for the faulted and nonfaulted phases, resulting in greater than zero and near zero, respectively. The PGFA admittance algorithm was built with MATLAB/Simulink software and tested with signature library and grid simulation events. The PGFA method with phase/ground boundaries was evaluated with the confusion matrix. The measured and predicted values matched in more than 90% of the tests, and the PGFA admittance method with phase/ground boundaries presented an accuracy of 94.3% and a precision of 100%.

42 ENGINEERING↗
DOE OSTI2020

A new genus and species of mud crab (Crustacea, Brachyura, Panopeidae) from shoreline waters of the western Gulf of Mexico

Several specimens of a small panopeid crab from coastal waters of the western Gulf of Mexico were long suspected to represent an undescribed species and are herein designated as representatives of a new genus. While the originally collected specimens from over four decades ago were not of gene-sequence quality, later collections from the same locality produced materials that yielded sequence data for inclusion in molecular phylogenetic studies. Building on results of those analyses, the present taxonomic description draws upon morphology to support the description of a unique species in which especially the male first gonopods differ from those of all other described panopeid genera. To date, the species remains known from only two western Gulf of Mexico sites, both of which are wave-washed intertidal rocky habitats where substrates are heavily burrowed by boring bivalves and sipunculans. While we cannot exclude the possibility that the species was introduced, recurrent collections show its populations to be at very least persistent, the species most likely being a long-overlooked among a confusing hard-substrate assemblage of small panopeid crabs.

Zoology↗
DOE OSTI2021

Description of Paraxiopsis kensleyi n. sp., a new axiid lobster from the Gulf of Mexico (Crustacea: Decapoda: Axiidea)

A new species of axiid was discovered during sampling offshore deep banks on the middle continental shelf off Louisiana. Paraxiopsis kensleyi n. sp. appears to inhabit interstices and cavities of coralline algal rubble, rhodoliths, coral rubble, and other eroded calcareous substrates. Weakly separated from Eutrichocheles Wood-Mason, 1876 on the basis of morphology, present assignments of western Atlantic species to Paraxiopsis de Man, 1905 are regarded as provisional. The new species is described morphologically, and the coloration of freshly captured specimens is documented and compared to related species where possible. Coloration readily distinguishes mature specimens of the new species from Paraxiopsis spinipleura Kensley, 1996, with which it was initially confused. The diagnosis includes GenBank accession numbers for COI sequences to allow future molecular phylogenetic comparisons. Compared to regional species that share a similar dentation or spination on the submedian carina, the pleon of the new species is distinctive in the truncate ventral margin on pleura 2–4, as opposed to being broadly rounded or directed ventrally in an acutely triangular tip. The new species is the eighteenth species of Paraxiopsis worldwide and the ninth from western Atlantic waters, seven of which are now known to range into the Gulf of Mexico. An updated key to western Atlantic members of the genus is provided.

59 BASIC BIOLOGICAL SCIENCES↗