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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers

With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for improved energy efficiency, equipment reliability, quality, safety, and productivity. This challenges capital cost and complexity for many small and medium-sized manufacturers (SMMs) who heavily rely on people to supervise manufacturing processes and facilities. This research aims to create an affordable, scalable, accessible, and portable (ASAP) solution to automate the supervision of manufacturing processes. The proposed approach seeks to reduce the cost and complexity of smart manufacturing deployment for SMMs through the deployment of consumer-grade electronics and a novel AI development methodology. The proposed system, AI-assisted Machine Supervision (AIMS), provides SMMs with two major subsystems: direct machine monitoring (DMM) and human-machine interaction monitoring (HIM). The AIMS system was evaluated and validated with a case study in 3D printing through the affordable AI accelerator solution of the vision processing unit (VPU).

3D printing↗
NASA NTRS1992

Study of shock-induced combustion using an implicit TVD scheme

The supersonic combustion flowfields associated with various hypersonic propulsion systems, such as the ram accelerator, the oblique detonation wave engine, and the scramjet, are being investigated using a new computational fluid dynamics (CFD) code. The code solves the fully coupled Reynolds-averaged Navier-Stokes equations and species continuity equations in an efficient manner. It employs an iterative method and a second order differencing scheme to improve computational efficiency. The code is currently being applied to study shock wave/boundary layer interactions in premixed combustible gases, and to investigate the ram accelerator concept. Results obtained for a ram accelerator configuration indicate a new combustion mechanism in which a shock wave induces combustion in the boundary layer, which then propagates outward and downstream. The combustion process creates a high pressure region over the back of the projectile resulting in a net positive thrust forward.

Yungster, Shayne↗
DOE OSTI2025

Engineering PHL7 for Improved Poly(Ethylene Terephthalate) Depolymerization via Rational Design and Directed Evolution

Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Tailoring MoS 2 for Small-Molecule Electroreduction: The Role of Metal Doping and Heterostructures

The electrification of chemical transformations central to sustainable fuel production and waste valorization, such as overall water splitting (OWS), hydrogen evolution reaction (HER), and electrochemical reduction of CO 2 (CO 2 R), presents a powerful opportunity to advance carbon-neutral energy technologies. Transition metal dichalcogenides (TMDs), particularly MoS 2 , have emerged as promising electrocatalyst candidates, owing to their abundance, tunable active sites, and defect-rich structures. This review highlights recent progress in leveraging metal doping and heterostructure engineering of MoS 2 to enhance the electrocatalytic activity and selectivity. By compiling insights from experimental studies and density functional theory (DFT) predictions, we examine how defect creation, electronic structure modification, and interface design contribute to improved charge transport and catalytic efficiency. Particular emphasis is placed on rational design principles, synthetic strategies, and operando characterization methods that provide a pathway to understanding and optimizing MoS 2 -based materials. We also discuss the challenges of stability, mechanistic ambiguity, and scaling while outlining opportunities to bridge theory and experiment. Collectively, this review underscores how defect and heterostructure engineering of MoS 2 can accelerate the development of efficient, sustainable electrocatalysts for both fuel generation and waste-to-value generation.

CO2 reduction↗
DOE OSTI2025

Artificial intelligence–powered biofoundries for protein engineering and metabolic engineering

Synthetic biology is rapidly evolving through the integration of artificial intelligence (AI) and automated biofoundries. This convergence accelerates the design–build–test–learn cycle, shifting protein engineering and metabolic engineering from labor-intensive manual experimentation to autonomous experimentation. This review summarizes recent advances in workflow development, AI models, and their integration with biofoundries for automated or autonomous protein engineering and metabolic engineering. Particularly, we highlight the potential of AI-powered biofoundries for accelerated scientific discovery and innovation in synthetic biology.

Chen, Junyu [Univ. of Illinois at Urbana-Champaign↗
NASA NTRS1983

Control techniques to improve Space Shuttle solid rocket booster separation

The present Space Shuttle's control system does not prevent the Orbiter's main engines from being in gimbal positions that are adverse to solid rocket booster separation. By eliminating the attitude error and attitude rate feedback just prior to solid rocket booster separation, the detrimental effects of the Orbiter's main engines can be reduced. In addition, if angular acceleration feedback is applied, the gimbal torques produced by the Orbiter's engines can reduce the detrimental effects of the aerodynamic torques. This paper develops these control techniques and compares the separation capability of the developed control systems. Currently with the worst case initial conditions and each Shuttle system dispersion aligned in the worst direction (which is more conservative than will be experienced in flight), the solid rocket booster has an interference with the Shuttle's external tank of 30 in. Elimination of the attitude error and attitude rate feedback reduces that interference to 19 in. Substitution of angular acceleration feedback reduces the interference to 6 in. The two latter interferences can be eliminated by atess conservative analysis techniques, that is, by using a root sum square of the system dispersions.

Tomlin, D. D.↗
NASA NTRS2001

Scramjet Tests in a Shock Tunnel at Flight Mach 7, 10, and 15 Conditions

Tests of the Hyper-X scramjet engine flowpath have been conducted in the HYPULSE shock tunnel at conditions duplicating the stagnation enthalpy at flight Mach 7, 10, and 15. For the tests at Mach 7 and 10 HYPULSE was operated as a reflected-shock tunnel; at the Mach 15 condition, HYPULSE was operated as a shock-expansion tunnel. The test conditions matched the stagnation enthalpy of a scramjet engine on an aerospace vehicle accelerating through the atmosphere along a 1000 psf dynamic pressure trajectory. Test parameter variation included fuel equivalence ratios from lean (0.8) to rich (1.5+); fuel composition from pure hydrogen to mixtures of 2% and 5% silane in hydrogen by volume; and inflow pressure and Mach number made by changing the scramjet model mounting angle in the HYPULSE test chamber. Data sources were wall pressures and heat flux distributions and schlieren and fuel plume imaging in the combustor/nozzle sections. Data are presented for calibration of the facility nozzles and the scramjet engine model. Comparisons of pressure distributions and flowpath streamtube performance estimates are made for the three Mach numbers tested.

Rogers, R. C.↗
DOE OSTI2025

Coupled order parameters and photoinduced domain walls in the charge density wave of (TaSe 4 ) 2 I

The charge density wave in (TaSe 4 ) 2 I has drawn much attention recently as a controversial candidate for an axion insulator where the CDW breaks the chiral symmetry of the Weyl semimetal. Here we use ultrafast x-ray scattering to study the collective modes of this CDW. By measuring several diffraction peaks we find that the order parameter involves coupled optical and acoustic modes. For strong near-infrared excitation, the dynamics of the x-ray diffraction show evidence of photoinduced inversion of both components of the CDW order parameter, and associated domain walls. These results demonstrate the potential of ultrafast methods to induce topological defects through highly nonequilibrium dynamics. In (TaSe 4 ) 2 I these defects should lead to exotic electronic states due to the nontrivial topology of the band structure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Design update on the transition beamline for the CEBAF Energy Upgrade

For Jefferson Lab’s 22GeV upgrade, two new permanent-magnet Fixed-Field Alternating Gradient (FFA) arcs will be integrated to serve the accelerator’s six highest-energy recirculation passes. Connecting these FFA arcs to the existing linear accelerator (linac) requires a carefully engineered transition section. The current design has two parts where the first part adiabatically matches the beam dispersion and orbit trajectories, while the second part aligns the Twiss parameters (alpha and beta functions) with those at the linac entrance. Given the tight spatial constraints and multiple matching requirements, a genetic algorithm is being explored to optimize the beam optics matching. This paper presents the current progress in developing and optimizing this transition.

Accelerator Physics↗
NASA NTRS1986

The central engine of quasars and active galactic nuclei Hadronic interactions of shock-accelerated relativistic protons

The detailed dynamics are presented of a model for AGNs and QSOs based on spherically symmetric accretion onto a black hole and dissipation of the accretion energy in a collisionless shock. The basic assumptions and equations relevant for the model are presented, and the relations between the physical parameters are given in terms of the shock parameters. The latter are calculated for varying Mach numbers, and the resulting scaling laws are discussed and compared to the data, in particular the recently discovered correlations between luminosity and mass. The model can naturally produce ultrarelativistic electrons with flat spectra, a feature which, when coupled with e(+)-e(-) pair production, can account for the observed continuum radiation from these objects over essentially the whole electromagnetic spectrum. The model also predicts the emission of high-energy neutrinos with a luminosity roughly equal to that of the photons.

Kazanas, D.↗
NASA NTRS1991

Engineering derivatives from biological systems for advanced aerospace applications

The present study consisted of a literature survey, a survey of researchers, and a workshop on bionics. These tasks produced an extensive annotated bibliography of bionics research (282 citations), a directory of bionics researchers, and a workshop report on specific bionics research topics applicable to space technology. These deliverables are included as Appendix A, Appendix B, and Section 5.0, respectively. To provide organization to this highly interdisciplinary field and to serve as a guide for interested researchers, we have also prepared a taxonomy or classification of the various subelements of natural engineering systems. Finally, we have synthesized the results of the various components of this study into a discussion of the most promising opportunities for accelerated research, seeking solutions which apply engineering principles from natural systems to advanced aerospace problems. A discussion of opportunities within the areas of materials, structures, sensors, information processing, robotics, autonomous systems, life support systems, and aeronautics is given. Following the conclusions are six discipline summaries that highlight the potential benefits of research in these areas for NASA's space technology programs.

Winfield, Daniel L.↗
NASA NTRS2003

Magnetic Field Would Reduce Electron Backstreaming in Ion Thrusters

The imposition of a magnetic field has been proposed as a means of reducing the electron backstreaming problem in ion thrusters. Electron backstreaming refers to the backflow of electrons into the ion thruster. Backstreaming electrons are accelerated by the large potential difference that exists between the ion-thruster acceleration electrodes, which otherwise accelerates positive ions out of the engine to develop thrust. The energetic beam formed by the backstreaming electrons can damage the discharge cathode, as well as other discharge surfaces upstream of the acceleration electrodes. The electron-backstreaming condition occurs when the center potential of the ion accelerator grid is no longer sufficiently negative to prevent electron diffusion back into the ion thruster. This typically occurs over extended periods of operation as accelerator-grid apertures enlarge due to erosion. As a result, ion thrusters are required to operate at increasingly negative accelerator-grid voltages in order to prevent electron backstreaming. These larger negative voltages give rise to higher accelerator grid erosion rates, which in turn accelerates aperture enlargement. Electron backstreaming due to accelerator-gridhole enlargement has been identified as a failure mechanism that will limit ionthruster service lifetime. The proposed method would make it possible to not only reduce the electron backstreaming current at and below the backstreaming voltage limit, but also reduce the backstreaming voltage limit itself. This reduction in the voltage at which electron backstreaming occurs provides operating margin and thereby reduces the magnitude of negative voltage that must be placed on the accelerator grid. Such a reduction reduces accelerator- grid erosion rates. The basic idea behind the proposed method is to impose a spatially uniform magnetic field downstream of the accelerator electrode that is oriented transverse to the thruster axis. The magnetic field must be sufficiently strong to impede backstreaming electrons, but not so strong as to significantly perturb ion trajectories. An electromagnet or permanent magnetic circuit can be used to impose the transverse magnetic field downstream of the accelerator-grid electrode. For example, in the case of an accelerator grid containing straight, parallel rows of apertures, one can apply nearly uniform magnetic fields across all the apertures by the use of permanent magnets of alternating polarity connected to pole pieces laid out parallel to the rows, as shown in the left part of the figure. For low-temperature operation, the pole pieces can be replaced with bar magnets of alternating polarity. Alternatively, for the same accelerator grid, one could use an electromagnet in the form of current-carrying rods laid out parallel to the rows.

Foster, John E.↗
NASA NTRS1990

A hypersonic research vehicle to develop scramjet engines

Four student design teams produced conceptual designs for a research vehicle to develop the supersonic combustion ramjet (scramjet) engines necessary for efficient hypersonic flight. This research aircraft would provide flight test data for prototype scramjets that is not available in groundbased test facilities. The design specifications call for a research aircraft to be launched from a carrier aircraft at 40,000 feet and a Mach number of 0.8. The aircraft must accelerate to Mach 6 while climbing to a 100,000 foot altitude and then ignite the experimental scramjet engines for acceleration to Mach 10. The research vehicle must then be recovered for another flight. The students responded with four different designs, two piloted waverider configurations, and two unmanned vehicles, one with a blended body-wing configuration, the other with a delta wing shape. All aircraft made use of an engine database provided by the General Electric Aircraft Engine Group; both turbofan ramjet and scramjet engine performance using liquid hydrogen fuel was available. Explained here are the students' conceptual designs and the aerodynamic and propulsion concepts that made their designs feasible.

Gregorek, G. M.↗
DOE OSTI2018

Experience and Practice of Batch Scheduling on Leadership Supercomputers at Argonne

The mission of the DOE Argonne Leadership Computing Facility (ALCF) is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community. The ALCF operates supercomputers that are generally amongst the Top 5 fastest machines in the world. Specifically, ALCF is looking for the science that is either too big to run anywhere else, or it would take so long as to be impractical (i.e., “capability jobs”). At ALCF, batch scheduling plays a critical role for achieving a set of site goals within a set of constraints. While system utilization is an important goal at ALCF, its largest mission constraint is to enable extreme scale parallel jobs to take precedence. In this paper, we will describe the specific scheduling goals and constraints, analyze the workload traces collected in 2013–2017 from the 48-rack petascale supercomputer Mira, and discuss the upcoming scheduling challenges at ALCF.

Allcock, William↗
DOE OSTI2016

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this article, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Passive SCR for lean gasoline NO X control: Engine-based strategies to minimize fuel penalty associated with catalytic NH 3 generation

Lean gasoline engines offer greater fuel economy than common stoichiometric gasoline engines. However, excess oxygen prevents the use of the current three-way catalyst (TWC) to control nitrogen oxide (NO X ) emissions in lean exhaust. A passive SCR concept, introduced by General Motors Global R&D, makes use of a TWC that is already onboard to generate NH 3 under slightly rich conditions, which is stored on the downstream SCR. The stored NH 3 is then used to reduce NO X emissions when the engine switches to lean operation. In this work, the effect of engine parameters, such as air-fuel equivalence ratio and spark timing, on NH 3 generation over a commercial Pd-only TWC with no dedicated oxygen storage component was evaluated on a 2.0-liter BMW lean burn gasoline direct injection engine. NO X reduction, NH 3 formation, and reductant utilization processes were evaluated, and fuel efficiency was assessed and compared to the stoichiometric engine operation case. We found air-fuel equivalence ratio to be one of the most important parameters in controlling the NH 3 production; however, the rich operation necessary for NH 3 production results in a fuel consumption penalty. The fuel penalty can be minimized by adjusting spark timing to increase rich-phase engine out NO X emissions and, thereby, NH 3 levels. Additionally, higher engine out NO X during engine load increase to simulate acceleration resulted in additional fuel savings. Ultimately, a 10% fuel consumption benefit was achieved with the passive SCR approach by optimizing rich air-fuel equivalence ratio and spark timing while also utilizing acceleration load conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM↗