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At least 613 records · Page 34

All sources NASA NTRS DOE OSTI

NASA NTRS2009

Proceedings of the First NASA Formal Methods Symposium

Topics covered include: Model Checking - My 27-Year Quest to Overcome the State Explosion Problem; Applying Formal Methods to NASA Projects: Transition from Research to Practice; TLA+: Whence, Wherefore, and Whither; Formal Methods Applications in Air Transportation; Theorem Proving in Intel Hardware Design; Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering; Model Checking for Autonomic Systems Specified with ASSL; A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process; Software Model Checking Without Source Code; Generalized Abstract Symbolic Summaries; A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing; Component-Oriented Behavior Extraction for Autonomic System Design; Automated Verification of Design Patterns with LePUS3; A Module Language for Typing by Contracts; From Goal-Oriented Requirements to Event-B Specifications; Introduction of Virtualization Technology to Multi-Process Model Checking; Comparing Techniques for Certified Static Analysis; Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder; jFuzz: A Concolic Whitebox Fuzzer for Java; Machine-Checkable Timed CSP; Stochastic Formal Correctness of Numerical Algorithms; Deductive Verification of Cryptographic Software; Coloured Petri Net Refinement Specification and Correctness Proof with Coq; Modeling Guidelines for Code Generation in the Railway Signaling Context; Tactical Synthesis Of Efficient Global Search Algorithms; Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems; and Formal Methods for Automated Diagnosis of Autosub 6000.

Denney, Ewen↗

NASA NTRS2001

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

Blonksi, Slawomir↗

DOE OSTI2025

CRISPR/Cas9 editing of p-COUMAROYL-CoA:MONOLIGNOL TRANSFERASE 1 in maize alters phenolic metabolism, lignin structure, and lignin-first biomass processing

Valorization of lignocellulosic biomass for sustainable production of high-value chemicals is challenged by the complexity of lignin, a phenolic biopolymer. Beyond the classical lignin monomers derived from p-coumaryl, coniferyl, and sinapyl alcohol, grass lignins incorporate substantial amounts of monolignol p-coumarates that are produced by p-COUMAROYL-CoA:MONOLIGNOL TRANSFERASE (PMT). Here, the CRISPR/Cas9-mediated mutation of ZmPMT1 in maize enabled the design of biomass depleted in p-coumaroylated lignin and enriched in guaiacyl lignin. Lignin-first biorefining of stem biomass from zmpmt1 mutants by reductive catalytic fractionation (RCF) generated a lignin oil depleted in carboxylates and enriched in guaiacyl-derived alcohols, which are desirable substrates for bio-based polyurethane synthesis. Furthermore, the reported lignin engineering in maize is a promising strategy for designing a dual-purpose crop, providing both food and feed, along with a renewable feedstock for the production of plant-based chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

In-situ synchrotron X-ray investigation of phase evolution in gas atomized powder enabling manufacturing of nanoscale oxide-dispersion strengthened ferritic steels

Here, we present an investigation of Fe-14Cr-3W-0.4Y-0.4Zr-0.18Ti (wt.%) as a reduced-activation oxide-dispersion strengthened (ODS) ferritic steel, an alternative to the “14YWT” structural alloys designed for nuclear energy applications. Gas atomization reaction synthesis (GARS) was used to produce these Zr-modified powders with a non-equilibrium (metastable) phase that enable a heat treatment (delayed) route for producing nanoscale oxide-dispersion strengthening. In situ synchrotron X-ray diffraction and transmission electron microscopy were used to analyze phase evolution as a function of temperature and time, revealing formation of highly dispersed oxide nanoprecipitate phases at temperatures above those needed for powder consolidation and shaping of components. This would allow fabrication of net-shape parts using conventional powder-processing methods prior to thermal activation of a reaction producing nanocrystalline Y-(Ti, Zr)-O particles, with a size of 20 ± 7 nm. These results can inform processing of tubes, cladding, sheets, and plates for use in advanced fission and fusion reactors.

In-situ synchrotron X-ray diffraction↗

DOE OSTI2022

Probing growth of metal–organic frameworks with X-ray scattering and vibrational spectroscopy

Nucleation and crystallization arising from liquid to solid phase are involved in a multitude of processes in fields ranging from materials science to biology. Controlling the thermodynamics and kinetics of growth is advantageous to help tune the formation of complex morphologies. In this report, we harness wide-angle X-ray scattering and vibrational spectroscopy to elucidate the mechanism for crystallization and growth of the metal–organic framework Co-MOF-74 within microscopic volumes enclosed in a capillary and an attenuated total reflection microchip reactor. The experiments reveal molecular and structural details of the growth processes, while the results of plane wave density functional calculations allow identification of lattice and linker modes in the formed crystals. Synthesis of the metal–organic framework with microscopic volumes leads to monodisperse and micron-sized crystals, in contrast to those typically observed under bulk reaction conditions. Reduction in the volume of reagents within the microchip reactor was found to accelerate the reaction rate. The coupling of spectroscopy with scattering to probe reactions in microscopic volumes promises to be a useful tool in the synthetic chemist's kit to understand chemical bonding and has potential in designing complex materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Nanoporous Materials Genome Center Final Technical Report

Nanoporous materials (NPMs), including zeolites/zeotypes, metal-organic frameworks (MOFs), covalent organic frameworks, polymers with intrinsic microporosity, and molecular cages, possess enormous potential in diverse areas relevant to the DOE Office of Science Basic Energy Sciences (BES) mission and objectives. The Nanoporous Materials Genome Center (NMGC) has developed exascale-ready software, computational/theoretical chemistry methods, and data-driven science approaches that enable (i) the de-novo design of functional NPMs for chemical separation and catalysis tasks of increasing complexity, (ii) the discovery of the most promising functional NPMs from databases of synthesized and hypothetical adsorbent structures and the optimization of process conditions for specific applications, and (iii) the microscopic-level understanding of the fundamental interactions underlying the function of NPMs including hierarchical architectures, composite materials, responsive frameworks that may undergo phase transitions or post-synthetic modifications, and materials containing defects, partial disorder, or interfaces. A pivotal part of the NMGC project has been a tight collaboration between leading experimental groups for synthesis and characterization of NPMs and of computational groups that allowed for iterative feedback. The NMGC project has resulted in the publication of more than 290 research and review articles including more than 60 publications in high-impact journals and more than 15 journal covers. NMGC publications have already received more than 20,000 citations (with more than 3,000 citations per year in 2021, 2022, and 2023) and contribute to an h-index of more than 72. The NMGC award has supported collaborative research involving 28 research groups and contributed to the training of more than 40 postdocs, more than 60 graduate students, and more than 20 undergraduate students with broad expertise in data-driven science approaches, computational chemistry methods, and high-performance computing, in addition to the skills to thrive in an integrated experimental and computational research environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Graphene nanopattern as a universal epitaxy platform for single-crystal membrane production and defect reduction

Heterogeneous integration of single-crystal materials offers great opportunities for advanced device platforms and functional systems. Although substantial efforts have been made to co-integrate active device layers by heteroepitaxy, the mismatch in lattice polarity and lattice constants has been limiting the quality of the grown materials. Layer transfer methods as an alternative approach, on the other hand, suffer from the limited availability of transferrable materials and transfer-process-related obstacles. Here, we introduce graphene nanopatterns as an advanced heterointegration platform that allows the creation of a broad spectrum of freestanding single-crystalline membranes with substantially reduced defects, ranging from non-polar materials to polar materials and from low-bandgap to high-bandgap semiconductors. Additionally, we unveil unique mechanisms to substantially reduce crystallographic defects such as misfit dislocations, threading dislocations and antiphase boundaries in lattice- and polarity-mismatched heteroepitaxial systems, owing to the flexibility and chemical inertness of graphene nanopatterns. More importantly, we develop a comprehensive mechanics theory to precisely guide cracks through the graphene layer, and demonstrate the successful exfoliation of any epitaxial overlayers grown on the graphene nanopatterns. Furthermore, this approach has the potential to revolutionize the heterogeneous integration of dissimilar materials by widening the choice of materials and offering flexibility in designing heterointegrated systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Construction of Lattice Strain in Bimetallic Nanostructures and Its Effectiveness in Electrochemical Applications

Bimetallic nanocrystals (NCs), associated with various surface functions such as ligand effect, ensemble effect, and strain effect, exhibit superior electrocatalytic properties. The stress-induced surface strain effect can alter binding strength between the surface active sites and reactants as well as their intermediates, and the electrochemical performance of bimetallic NCs can be significantly facilitated by the lattice-strain modification via their morphologies, sizes, shell-thickness, surface defectiveness as well as compositions. Here in this review, an overview of fundamental principles, characterization techniques, and quantitative determination of the surface lattice strain is provided. Various strategies and synthesis efforts on creating lattice-strain-engineered bimetallic NCs, including the de-alloying process, atomic layer-by-layer deposition, thermal treatment evolution, one-pot synthesis, and other efforts are also discussed. It is further outlined how the lattice strain effect promotes electrochemical catalysis through the selected case studies. The reactions on oxygen reduction reaction, small molecular oxidation, water splitting reaction, and electrochemical carbon dioxide reduction reactions are focused. In particular, studies of lattice strain arisen from core–shell nanostructure and defectiveness are highlighted. Lastly, the potential challenges are summarized and the prospects of lattice-strain-based engineering on bimetallic nanocatalysts with suggestion and guidance of the future electrocatalyst design are envisioned.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo- and Copolymers

The purpose of this study was to develop a data-driven machine learning model to predict the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced polyesters featuring excellent performance, to guide future design and synthesis experiments. A deep neural network (DNN) machine learning model was built for predicting the glass transition temperature, Tg, of PHA homo- and copolymers. Molecular fingerprints were used to capture the structural and atomic information of PHA monomers. The other input variables included the molecular weight, the polydispersity index, and the percentage of each monomer in the homo- and copolymers. The results indicate that the DNN model achieves high accuracy in estimation of the glass transition temperature of PHAs. In addition, the symmetry of the DNN model is ensured by incorporating symmetry data in the training process. The DNN model achieved better performance than the support vector machine (SVD), a nonlinear ML model and least absolute shrinkage and selection operator (LASSO), a sparse linear regression model. The relative importance of factors affecting the DNN model prediction were analyzed. Sensitivity of the DNN model, including strategies to deal with missing data, were also investigated. Compared with commonly used machine learning models incorporating quantitative structure–property (QSPR) relationships, it does not require an explicit descriptor selection step but shows a comparable performance. The machine learning model framework can be readily extended to predict other properties.

quantitative structure–property relationship (QSPR↗

DOE OSTI2025

Uncovering the True Active Sites in Ni–N–C Catalysts for CO 2 Electroreduction

Understanding and designing active sites in single-atom catalysts (SACs) requires going beyond static models to capture their dynamic evolution under realistic electrochemical conditions. Here, in this work, we develop an integrated theoretical framework that accounts for operational conditions, by combining grand canonical density functional theory (GC-DFT) with machine-learning-accelerated sampling, to uncover structure–activity–stability relationships in Ni–N–C SACs for the CO 2 reduction reaction (CO 2 RR). A library of NiN x C 4–x (x = 0–4) motifs─representing coordination defects likely formed during high-temperature synthesis─was systematically evaluated. Under working conditions, these sites were found to undergo hydrogenation, and NiN 3 C 1_ H 1 was identified as the most probable active site. At reducing potentials, hydrogen adsorbs spontaneously at C–Ni bridge sites rather than Ni top sites, while subsurface hydrogen facilitates bent CO 2 adsorption crucial for activation. High CO 2 RR selectivity toward CO arises from site separation: Ni centers drive CO2RR, while the hydrogen evolution reaction (HER) occurs at the C–Ni bridge or N sites and from thermodynamic suppression of HER at moderate hydrogen coverage. At more negative potentials, a shift in the CO 2 RR rate-determining process (RDP) and Ni out-of-surface displacement induced by coadsorption of H and H 2 O jointly reduce activity and selectivity. Thus, both the high CO2RR selectivity of Ni–N–C catalysts and its reversal with more negative potentials can be rationalized by accounting for hydrogenated surfaces. This highlights the necessity of modeling realistic; in situ conditions. This framework provides generalizable insights into the dynamic behavior of active sites in SACs, offering guidance for the rational design of active and robust catalysts for a wide range of electrochemical reactions.

25 ENERGY STORAGE↗

NASA NTRS1978

Trajectory module of the NASA Ames Research Center aircraft synthesis program ACSYNT

A program was developed to calculate trajectories for both military and commercial aircraft for use in the aircraft synthesis program, ACSYNT. The function of the trajectory module was to calculate the changes in the vehicle's flight conditions and weight, as fuel is consumed, during the flying of one or more missions. The trajectory calculations started with a takeoff, followed by up to 12 phases chosen from among the following: climb, cruise, acceleration, combat, loiter, descent, and paths. In addition, a balanced field length was computed. The emphasis was on relatively simple formulations and analytic expressions suitable for rapid computation since a prescribed trajectory had to be calculated many times in the process of converging an aircraft design, or finding an optimum configuration. The trajectory module consists of about 2500 cards and operational on a CDC 7600 computer.

Tauber, M. E.↗

DOE OSTI2021

High-Performance Piezo-Electrocatalytic Sensing of Ascorbic Acid with Nanostructured Wurtzite Zinc Oxide

We report nanostructured piezoelectric semiconductors offer unprecedented opportunities for high-performance sensing in numerous catalytic processes of biomedical, pharmaceutical, and agricultural interests, leveraging piezocatalysis that enhances the catalytic efficiency with the strain-induced piezoelectric field. Here, we design and demonstrate for the first time a cost-efficient, high-performance piezo-electrocatalytic sensor for detecting L-ascorbic acid (AA), a critical chemical for many organisms, metabolic processes, and medical treatments. We prepared ZnO nanorods and nanosheets to characterize and compare their efficacy for the piezo-electrocatalysis of AA. The electrocatalytic efficacy of AA was significantly boosted by the piezoelectric polarization induced in the nanostructured semiconducting ZnO catalysts. We elucidated the charge transfer between the strained ZnO nanostructures and AA to reveal the mechanism for the related piezo-electrocatalytic process. The low-temperature synthesis of high-quality ZnO nanostructures allows the low-cost, scalable production and integration directly into wearable electrocatalytic sensors whose performance could be boosted by otherwise wasted mechanical energy from the working environment, e.g., the human-generated mechanical signals.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Manufacturing the Harmonic Kicker Cavity Prototype for the Electron-Ion Collider

High-bunch-frequency beam-separation schemes, such as the injection scheme proposed for the Rapid Cycling Synchrotron at the Electron-Ion Collider, demand rise and fall times an order of magnitude below what can realistically be accomplished with a stripline kicker. Nanosecond-time-scale kick waveforms can instead be obtained by Fourier synthesis in a harmonically resonant quarter-wave radio-frequency cavity which is optimized for high shunt impedance. Originally developed for the Jefferson Lab Electron-Ion Collider (JLEIC) Circulator Cooler Ring, a hypothetical 11-pass ring driven by an energy-recovery linac at Jefferson Lab, our high-power prototype of such a harmonic kicker cavity, which operates at five modes at the same time, will demonstrate the viability of this concept with a beam test at Jefferson Lab. As the geometry of the cavity, tight mechanical tolerances, and number of ports complicate the design and manufacturing process, special care must be given to the order of the manufacturing steps. We present our experiences with the manufacturability of the present design, lessons learned, and first RF test results from the prototype.

Overstreet, S. A.↗

DOE OSTI2022

Manufacturing the Harmonic Kicker Cavity Prototype for the Electron-Ion Collider

Overstreet, S. A.↗

DOE OSTI2020

Chemically Controllable Porous Polymer–Nanocrystal Composites with Hierarchical Arrangement Show Substrate Transport Selectivity

Functional organic–inorganic hybrid materials with tunable properties are useful across many application areas, ranging from gas storage to electronics, flame retardants, separations, and catalysis. Combining polymers, with a suite of functional groups and conformational flexibility, and inorganic nanoparticles, with tunable surface chemistry and composition, yields hybrids with novel functional properties. Specifically, in catalysis, control of the electronic environment at a metal interface is paramount in determining the catalytic properties. In this contribution, we describe a modular process to prepare porous polymer–nanocrystal (NC) composites in a hierarchical, multilayered synthesis, in which multiple parameters can be accurately tuned: polymer functional groups and the corresponding pore structure, the polymer layer thickness, and the NC size, shape, and composition. This process provides for a variety of controlled materials with high surface area, tunable chemistry, and thermal and chemical stabilities. Furthermore, we demonstrate their utility for shape- and size-selective catalytic conversions both in oxidation and hydrogenation reactions, where they show increased selectivity by orders of magnitude compared to conventional polymer-supported metal catalysts. In light of the high degree of control in the composite structure, this method allows for the design and realization of catalysts for several reactions and reaction environments and for nanomaterials with other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Designing silicon carbide heterostructures for quantum information science: challenges and opportunities

Abstract Silicon carbide (SiC) can be synthesized in a number of different structural forms known as polytypes with a vast array of optically active point defects of interest for quantum information sciences. The ability to control and vary the polytypes during SiC synthesis may offer a powerful methodology for the formation of new material architectures that expand our ability to manipulate these defects, including extending coherence lifetimes and enhancing room temperature operation. Polytypic control during synthesis presents a significant challenge given the extreme conditions under which SiC is typically grown and the number of factors that can influence polytype selection. In situ monitoring of the synthesis process could significantly expand our ability to formulate novel polytype structures. In this perspective, we outline the state of the art and ongoing challenges for precision synthesis in SiC. We discuss available in situ x-ray characterization methods that will be instrumental in understanding the atomic scale growth of SiC and defect formation mechanisms. We highlight optimistic use cases for SiC heterostructures that will become possible with in situ polytypic control and end by discussing extended opportunities for integration of ultrahigh quality SiC materials with other semiconductor and quantum materials.

Harmon, K. J. (ORCID:0000000164277971)↗

DOE OSTI2026

The role of transition metal formyl intermediates in the reduction of CO and CO 2

Transition-metal formyl (metalloformyl) complexes occupy a central position in the activation of small molecules, particularly in the reduction of carbon monoxide (CO) and carbon dioxide (CO 2 ). This review examines five decades of progress in the synthesis of metalloformyl complexes and investigations into their structure and reactivity. The bonding in the M–CHO unit is best described as a resonance hybrid between a classical σ-bound formyl ligand and an oxycarbene-like electronic structure, which governs their distinctive spectroscopic signatures and versatile reactivity. Established synthetic routes are summarized, including pathways involving hydride addition and CO insertion, alongside a discussion of the thermodynamic and kinetic factors that control formyl stability. Decomposition pathways and Lewis-acid stabilization strategies are analyzed as key design principles for extending metalloformyl lifetimes under catalytic conditions. Particular attention is given to hydride transfer processes and the role of metalloformyl intermediates as both reactive substrates and hydride sources in reduction chemistry. Lastly, emerging catalytic strategies that exploit metalloformyl intermediates in CO 2 and CO reduction are evaluated, highlighting how control of hydricity, redox potential, and secondary-sphere interactions enables selective C—H bond formation under comparatively mild conditions. Collectively, these studies establish metalloformyl complexes as mechanistically informative and functionally relevant intermediates that bridge fundamental organometallic chemistry with modern approaches to small-molecule activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗