Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Active target”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The cytochrome bc 1 complex as an antipathogenic target

The cytochrome bc 1 complex is a key component of the mitochondrial respiratory chains of many eukaryotic microorganisms that are pathogenic for plants or humans, such as fungi responsible for crop diseases and Plasmodium falciparum, which causes human malaria. Cytochrome bc 1 is an enzyme that contains two (ubi)quinone/quinol-binding sites, which can be exploited for the development of fungicidal and chemotherapeutic agents. In this article, we review recent progress in determination of the structure and mechanism of action of cytochrome bc 1 , and the associated development of antimicrobial agents (and associated resistance mechanisms) targeting its activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequenc- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. Finally, this approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Rational inhibitor design for Pseudomonas aeruginosa salicylate adenylation enzyme PchD

Pseudomonas aeruginosa is an increasingly antibiotic-resistant pathogen that causes severe lung infections, burn wound infections, and diabetic foot infections. P. aeruginosaproduces the siderophore pyochelin through the use of a non-ribosomal peptide synthetase (NRPS) biosynthetic pathway. Targeting members of siderophore NRPS proteins is one avenue currently under investigation for the development of new antibiotics against antibiotic-resistant organisms. Here, the crystal structure of the pyochelin adenylation domain PchD is reported. The structure was solved to 2.11 Å when co-crystallized with the adenylation inhibitor 5'-O-(N-salicylsulfamoyl)adenosine (salicyl-AMS) and to 1.69 Å with a modified version of salicyl-AMS designed to target an active site cysteine (4-cyano-salicyl-AMS). In the structures, PchD adopts the adenylation conformation, similar to that reported for AB3403 from Acinetobacter baumannii.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Optimizing mixed cool thermal storage systems across a connected community

A high level of electric demand flexibility must be integrated into our building infrastructure to enable greater renewable energy penetration in the grid. In the U.S., 9% of electricity generated is used to cool buildings in a periodic manner, making this end-use an ideal target for active management through cool thermal energy storage (CTES) technologies. Historic uses for CTES are designed around central chilled water plants, but these systems cool less than 25% of U.S. commercial floorspace. Emerging technologies are under development to serve the many smaller distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to an additional 66% of cooled commercial floorspace. However, these unitary thermal storage systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive grid context. Here, this study develops the modeling and optimization tools necessary to simultaneously examine central and distributed ice storage systems within the multi-building, connected community context. An integrated simulation-optimization workflow is created to allow for rapid customized analysis. Results demonstrate the energy and flexibility tradeoffs of various implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗
DOE OSTI2021

MuSIC@Indiana: An effective tool for accurate measurement of fusion with low-intensity radioactive beams

The design, construction, and characterization of the Multi-Sampling Ionization Chamber, MuSIC@Indiana, are described. This detector provides efficient and accurate measurement of the fusion cross-section at near-barrier energies. The response of the detector to low-intensity beams of 17,18 O, 19 F, 23 Na, 24,26 Mg, 27 Al, and 28 Si at E lab 50–60MeV was examined. MuSIC@Indiana was commissioned by measuring the 18 O+ 12 C fusion excitation function for 11 < E cm < 20 MeV using CH 4 gas. Here, a simple, effective analysis cleanly distinguishes proton capture and two-body scattering events from fusion on carbon. With MuSIC@Indiana, measurement of 15 points on the excitation function for a single incident beam energy is achieved. The resulting excitation function is shown to be in good agreement with literature data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Classification of events from α -induced reactions in the MUSIC detector via statistical and ML methods

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other applications. From the MUSIC data produced in one experiment scientists carefully extract an order of 10 3 events of interest from about 10 9 total events, where each event can be represented by an 18-dimensional vector. However, the standard data classification process is based on expert driven, manually intensive data analysis techniques that require several months to identify patterns and classify the relevant events from the collected data. Here, to address this issue, we present a method for the classification of events originating from specific α-induced reactions by combining statistical and machine learning methods that require significantly less input from the domain scientist, relative to the standard technique. Here, we applied the new method to two experimental data sets and compared our results with those obtained using traditional methods. With few exceptions, the number of events classified by our method agrees within ±20% with the results obtained using traditional methods. With the present method, which is the first of its kind for the MUSIC data, we have established the foundation for the automated extraction of physical events of interest from experiments using the MUSIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Ad-apoptin inhibits glycolysis, migration and invasion in lung cancer cells targeting AMPK/mTOR signaling pathway

Ad-apoptin is a recombinant oncolytic adenovirus constructed by our laboratory that can express apoptin. It can selectively kill tumor cells without damaging normal cells. This study investigated the effects of Ad-apoptin on glycolysis, migration and invasion of non-small cell lung cancer. Cell viability and apoptosis were detected by CCK-8 and flow cytometry, respectively. Glycolysis was investigated by glucose consumption, lactic acid production and glycolytic key enzyme protein levels. Migration and invasion were evaluated via wound healing, transwell assays and epithelial-mesenchymal transition (EMT) protein levels. The interaction between apoptin and AMPK was detected by Co-IP. A nude mice tumor model was established to investigate the anti-cancer role of Ad-apoptin in vivo. The results showed that Ad-apoptin inhibits cell viability and induces apoptosis of A549 and NCI–H23 cells. Ad-apoptin can reduce the glucose uptake and lactic production in lung cancer cells, and reduce the expression of related glycolysis-limiting enzymes. At the same time, Ad-apoptin inhibited the migration and invasion of lung cancer. Immunoprecipitation showed that apoptin and AMPK could interact directly. Moreover, knockdown of AMPK significantly attenuated the inhibitory effect of Ad-apoptin on glycolysis, migration and invasion of A549 and NCI–H23 cells. Ad-apoptin can inhibit the growth of tumors in nude mice. Compared with the control group, Ad-apoptin had a significant inhibitory effect on AMPK knockdown tumors. The immunohistochemical results of tumor tissues were consistent with those in vitro. Collectively, Ad-apoptin targets AMPK and inhibits glycolysis, migration and invasion of lung cancer cells through the AMPK/mTOR signaling pathway. This suggests that Ad-apoptin may have therapeutic potential for lung cancer by targeting AMPK activation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Pt Atomic Single-Layer Catalyst Embedded in Defect-Enriched Ceria for Efficient CO Oxidation

The local coordination structure of metal sites essentially determines the performance of supported metal catalysts. Here, using a surface defect enrichment strategy, we successfully fabricated Pt atomic single-layer (Pt ASL ) structures with 100% metal dispersion and precisely controlled local coordination environment (embedded vs adsorbed) derived from Pt single-atoms (Pt 1 ) on ceria-alumina supports. The local coordination environment of Pt 1 not only governs its catalytic activity but also determines the Pt 1 structure evolution upon reduction activation. For CO oxidation, the highest turnover frequency can be achieved on the embedded Pt ASL in the CeO 2 lattice, which is 3.5 times of that on the adsorbed Pt ASL on the CeO 2 surface and 10–70 times of that on Pt1. The favorable CO adsorption on embedded Pt ASL and improved activation/reactivity of lattice oxygen within CeO 2 effectively facilitate the CO oxidation. This work provides new insights for the precise control of the local coordination structure of active metal sites for achieving 100% atomic utilization efficiency and optimal intrinsic catalytic activity for targeted reactions simultaneously.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Phosphatidic acid: an emerging versatile class of cellular mediators

Abstract Lipids function not only as the major structural components of cell membranes, but also as molecular messengers that transduce signals to trigger downstream signaling events in the cell. Phosphatidic acid (PA), the simplest and a minor class of glycerophospholipids, is a key intermediate for the synthesis of membrane and storage lipids, and also plays important roles in mediating diverse cellular and physiological processes in eukaryotes ranging from microbes to mammals and higher plants. PA comprises different molecular species that can act differently, and is found in virtually all organisms, tissues, and organellar membranes, with variations in total content and molecular species composition. The cellular levels of PA are highly dynamic in response to stimuli and multiple enzymatic reactions can mediate its production and degradation. Moreover, its unique physicochemical properties compared with other glycerophospholipids allow PA to influence membrane structure and dynamics, and interact with various proteins. PA has emerged as a class of new lipid mediators modulating various signaling and cellular processes via its versatile effects, such as membrane tethering, conformational changes, and enzymatic activities of target proteins, and vesicular trafficking.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Fragment binding to the Nsp3 macrodomain of SARS-CoV-2 identified through crystallographic screening and computational docking

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) macrodomain within the nonstructural protein 3 counteracts host-mediated antiviral adenosine diphosphate–ribosylation signaling. This enzyme is a promising antiviral target because catalytic mutations render viruses nonpathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of 2533 diverse fragments resulted in 214 unique macrodomain-binders. An additional 60 molecules were selected from docking more than 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several fragment hits were confirmed by solution binding using three biophysical techniques (differential scanning fluorimetry, homogeneous time-resolved fluorescence, and isothermal titration calorimetry). The 234 fragment structures explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Pseudomonas effector AvrB is a glycosyltransferase that rhamnosylates plant guardee protein RIN4

The plant pathogen Pseudomonas syringae encodes a type III secretion system avirulence effector protein, AvrB, that induces a form of programmed cell death called the hypersensitive response in plants as a defense mechanism against systemic infection. Despite the well-documented catalytic activities observed in other Fido (Fic, Doc, and AvrB) proteins, the enzymatic activity and target substrates of AvrB have remained elusive. Here, we show that AvrB is an unprecedented glycosyltransferase that transfers rhamnose from UDP-rhamnose to a threonine residue of the Arabidopsis guardee protein RIN4. We report structures of various enzymatic states of the AvrB-catalyzed rhamnosylation reaction of RIN4, which reveal the structural and mechanistic basis for rhamnosylation by a Fido protein. Collectively, our results uncover an unexpected reaction performed by a prototypical member of the Fido superfamily while providing important insights into the plant hypersensitive response pathway and foreshadowing more diverse chemistry used by Fido proteins and their substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Real-Time Multi-Vehicle Multi-Camera Tracking with Graph-Based Tracklet Features

An essential application in intelligent transportation systems is multi-target multi-camera tracking (MTMCT), where the target’s activity is tracked from different cameras. Although the tracking-by-detection scheme is the primary paradigm in MTMCT, the object association information from the video frames is lost. This is mainly because the multi-camera multi-object matching uses the information from the video frames separately. To solve this problem and leverage this association information, we propose an MTMCT framework, where features are built in the form of a graph and a graph similarity algorithm is used to match multi-camera objects. In this paper, we focus on the real-time scenario, where only the past images are used to match an object. Our method achieves an IDF1 score (the ratio of the number of correctly identified objects to the number of ground truth and average objects) of 0.75 with a rate of 14 frames per second (fps).

Engineering↗
DOE OSTI2021

The novel anti-CRISPR AcrIIA22 relieves DNA torsion in target plasmids and impairs SpyCas9 activity

To overcome CRISPR-Cas defense systems, many phages and mobile genetic elements (MGEs) encode CRISPR-Cas inhibitors called anti-CRISPRs (Acrs). Nearly all characterized Acrs directly bind Cas proteins to inactivate CRISPR immunity. Here, using functional metagenomic selection, we describe AcrIIA22, an unconventional Acr found in hypervariable genomic regions of clostridial bacteria and their prophages from human gut microbiomes. AcrIIA22 does not bind strongly to SpyCas9 but nonetheless potently inhibits its activity against plasmids. To gain insight into its mechanism, we obtained an X-ray crystal structure of AcrIIA22, which revealed homology to PC4-like nucleic acid–binding proteins. Based on mutational analyses and functional assays, we deduced that acrIIA22 encodes a DNA nickase that relieves torsional stress in supercoiled plasmids. This may render them less susceptible to SpyCas9, which uses free energy from negative supercoils to form stable R-loops. Modifying DNA topology may provide an additional route to CRISPR-Cas resistance in phages and MGEs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Towards provision of regularly updated climate data from the Coupled Model Intercomparison Project

The Coupled Model Intercomparison Project (CMIP) is a flagship of the World Climate Research Programme (WCRP). CMIP has become a recognised ‘brand’ in climate circles evolving over the last thirty years from a targeted research activity by a small number of climate modelling centres intercomparing their Earth System Model (ESM) simulations to a broad international coordinated research effort (Durack et al, 2025). CMIP is organized as a research activity leveraging funded and in-kind contributions from experts within modelling centres and the broader scientific community supported more recently by a fully-funded International Project Office. Within CMIP, Model Intercomparison Projects (MIPs) are community-designed to understand past, present and future climate. CMIP data provides a valuable resource for climate research and is routinely used to assess model representation of climate processes and test scientific hypotheses in the context of model uncertainty and (forced and internal) variability as evident from its prolific use in scientific publications1 . The impact relies on enabling infrastructure (most prominently via the Earth System Grid Federation (ESGF)), which allows sharing of simulation output, provision of the boundary conditions used in each simulation, and definition of the data standards that are essential to facilitating wide use of the data. The impact is supplemented by the wide-ranging scrutiny to which model simulations are subjected. Beyond its use in research, CMIP data is a key resource for communities producing derived climate information from downscaling and impact studies, such as the Coordinated Regional Downscaling Experiment (CORDEX; Gutowski et al., 2016) and the Intersectoral Impacts MIP (ISIMIP; Frieler et al., 2024). Government, academic and commercial entities also increasingly rely on CMIP and its downstream data for climate risk assessments and climate services (for example, Copernicus Climate Change Service and World Bank portal). This means that, although CMIP is a research activity, it increasingly serves a secondary and very relevant role as a provider of climate data – a long-recognised dichotomy (Stevens, 2024). Research and applications have distinct needs, with the former requiring flexibility and generality and the latter consistency. Here we explain how the design of the research activity has been adapted to reduce the burdens imposed by applications and how the research infrastructure might evolve to further enable scientific inquiry. We propose one possible approach to consistently providing model information and projections for applications in the future.

Environmental sciences↗
DOE OSTI2025

Deuteron-induced reactions on natural Zr from threshold to 50 MeV: production of 86g Y

Two stacks of thin Zr foils were irradiated with 30 and 50 MeV deuterons, respectively, using the Lawrence Berkeley National Laboratory 88-Inch Cyclotron, and 19 excitation functions for nat Zr(d,x) reactions were measured over a beam energy range of 6.3–47.64 MeV, where the independent cross sections for nat Zr(d,x) 88 Nb and nat Zr(d,x) 86m,g Y were measured for the first time. The well-characterized nat Fe(d,x) 56 Co, nat Ni(d,x) 56 Co, nat Ni(d,x) 58 Co, nat Ni(d,x) 61 Cu, nat Ti(d,x) 46 Sc and nat Ti(d,x) 48 V monitor reactions were used to determine the deuteron beam current throughout the stacks. All cross sections were determined using High Purity Germanium (HPGe) detector γ-ray spectroscopy. A variance minimization technique was employed to simultaneously constrain the deuteron beam currents with multiple monitor reactions, thus reducing systematic uncertainties. An additional 16 channels are reported for reactions on the nickel, titanium, and iron monitor foils, leading to a total of 35 excitation functions, with seven reaction channels reported for the first time in this work. The measured excitation functions are compared to calculations provided by the reaction modeling codes TALYS – 2.0, ALICE – 2020, CoH – 3.5.3 and EMPIRE – 3.2.3, as well as the TENDL – 2023 data library. The degree of agreement between theory and experiments is discussed. The possible production of the important PET radionuclide 86g Y via the nat Zr(d,x) route was critically examined. The physical yields for nat Zr(d,x) 86 Y and other yttrium isotopes produced were calculated and compared to other production pathways. Due to high-level of associated radionuclide impurities, this route cannot deliver 86g Y suitable for medical applications.

86gY↗
DOE OSTI2021

Nanostructured, Targeted Layered Metal Oxides as Active and Selective Heterogeneous Electrocatalysts for Oxygen Evolution

Oxygen evolution reaction (OER) is an important chemical transformation that governs the performance of technologically relevant energy conversion and storage processes, such as electrochemical water splitting in electrolyzers and metal-air batteries. This reaction involves the evolution of oxygen gas from (i) oxygen ions formed from water splitting at high temperatures, (ii) oxygen containing species (i.e., OH, OOH) formed from water splitting at low temperatures, and (iii) metal-oxide discharge products (M x O 2 ) in metal-air batteries. One of the main challenges with OER is that it is catalyzed at low temperatures by noble metal-based electrocatalysts, which are expensive (making this process economically unviable), or at high temperatures by metal-oxide based electrocatalysts that are inefficient and lead to high overpotential losses. Our preliminary results, as well as other results in the literature, show that non-noble metal-based oxide electrocatalysts with layered structures, known as nickelate oxides, exhibit promising OER activity. Nickelate oxides (A 2 MO 4+δ ) belong to the Ruddlesden-Popper series composed of alternating perovskite-like and rocksalt-like layers. They are promising OER electrocatalysts due to their high oxygen transport/exchange properties compared to the state-of-the-art perovskite-type oxides. Unfortunately, these materials are fairly unexplored and little is known about the properties that govern their OER activity. Our preliminary studies, where we combine density functional theory (DFT) calculations, selective synthesis and characterization, show that engineering their nanocrystalline structure can significantly impact their catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗