Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “accelerated discovery”

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 865 records · Page 48

Flying Through the Ages: Rodent Research for Human Health

As humans, we evolved, developed, grew, and now function in a continuous 1-gravity environment. Habitation in space poses unique challenges to human cells and organ systems. Biomedical research with rodents (primarily mice and rats) can help to both unravel molecular, cellular and physiologic mechanisms relevant to humans and test candidate interventions that mitigate adverse effects of space on humans, such as muscle atrophy, bone loss and cardiovascular deconditioning. One favored hypothesis that may explain the detrimental effects of spaceflight on humans is that reduced mechanical loading in microgravity accelerates aging. Rodents provide a relevant model system to study this problem as they age 40 times faster than humans. Now scientists from both public and commercial sectors conduct rodent experiments on the ISS using a new capability developed primarily at ARC. Results from the maiden voyage of the Rodent Research Project on the ISS reveal that long duration effects of spaceflight appear far different than short duration effects. Thus, Rodent Research missions on the ISS usher in a new era for exploration and biological discovery in space.

Globus, Ruth↗

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

36 MATERIALS SCIENCE↗

The Saturn System Through the Eyes of Cassini

More than 400 years ago, Galileo Galilei trained his homemade telescope on the night sky and observed that Saturn had two objects closely related to the planet extending on either side. At the time, in 1610, Galileo declared them to be moons. A few decades later, Saturn moon science accelerated at a dizzying pace. Christiaan Huygens first observed Saturn's largest moon Titan in 1655 and was the first to describe the extended moon-like features at Saturn as a disk of material sounding the planet. From 1671 to 1674, Giovanni Cassini discovered the moons lapetus, Rhea, Dione and Tethys. In 1675, Cassini discovered the gap in Saturn's rings that we now know as the Cassini Division. In the space age, before the Cassini-Huygens mission, we had only hints of the discoveries awaiting us at Saturn. Pioneer 11 and Voyagers 1 and 2 conducted flybys decades ago. But these quick encounters didn't allow time for more extensive research. NASA and the European Space Agency created a partnership to orbit a Saturn orbiter (Cassini) and a lander (Huygens) on Titan. Like its namesakes, the Cassini-Huygens mission not only discovered previously unknown moons, but it also helped us understand the science behind their formation, their interactions with the rings, and how truly diverse they are. The Cassini-Huygens mission revolutionized what we know about the Saturn system. The rings of Saturn, the moons, and the planet itself offer irresistible and inexhaustible subjects for intense study, and Cassini-Huygens did not disappoint. The Saturnian system proved to be a rich ground for science exploration and discoveries, and Cassini has been nothing short of a discovery machine. At the time Cassini plunged into Saturn at the end of its mission, it had observed the planet for a little less than half of a Saturn year. But it also orbited the gas giant 293 times, forever changing our understanding of the Saturn system and yielding tremendous insight for understanding the entire Solar System.

Green, James↗

LLNL FESP Theory Highlights: August 2024

The 2024 ABOUND SciDAC and BOUT++ combined workshop was held August 5-9 th 2024 at the University of California Livermore Collaboration Center (UCLC) in Livermore. Bringing together leading scientists and researchers from across the globe, this pivotal event focused on advancing plasma physics and boundary plasma dynamics within the context of fusion energy research. Key discussions throughout the meeting highlighted significant advancements in the BOUT++ framework, including enhanced simulations of small Edge Localized Modes (ELMs) and the initiation of integrating the integration of the 5D GEM gyrokinetic turbulence core code with the 2D SOLPS-ITER boundary transport code. These developments are crucial for managing heat loads in fusion reactors and supporting the longevity of plasma-facing components. The event also featured a session on Inter-SciDAC Collaborations, where principal investigators from multiple U.S. FES SciDAC tokamak projects explored opportunities for cross-collaboration. Additionally, the meeting showcased cutting-edge advancements in GPU acceleration and AI/ML technologies, poised to drive the next generation of fusion research. In his closing remarks, Dr. Xueqiao Xu emphasized the importance of the collaborative efforts and discussions that took place, noting their potential to shape future breakthroughs in fusion energy. The event underscored the global nature of the BOUT++ collaboration, with contributions from over 57 institutions worldwide. The 2024 BOUT++ and ABOUND Joint Hybrid Meeting continues to drive forward the research and innovations needed to achieve fusion energy, setting the stage for future collaboration and discovery.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A convergence metric for counting statistics in time-resolved small angle neutron scattering

Here, this work introduces a model-independent, dimensionless metric for predicting optimal measurement duration in time-resolved small-angle neutron scattering using early-time data. Built on a Gaussian process regression framework, the method reconstructs scattering profiles with quantified uncertainty, even from sparse or noisy measurements. Demonstrated on the EQ-SANS instrument at the Spallation Neutron Source, the approach generalizes to general SANS instruments with a two-dimensional detector. A key result is the discovery of a dimensionless convergence metric revealing a universal power-law scaling in profile evolution across soft matter systems. When time is normalized by a system-specific characteristic time t*, the variation in inferred profiles collapses onto a single curve with an exponent between −2 and −1. This trend emerges within the first ten time steps, enabling early prediction of measurement sufficiency. The method supports real-time experimental optimization and is especially valuable for maximizing efficiency in low-flux environments such as compact accelerator-based neutron sources.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗

The origin of broad emission lines in the extragalactic giant H II region NGC 2363

High signal-to-noise long-slit spectra have been obtained of the giant H II region NGC 2363 located in the dwarf SBm galaxy NGC 2366. A discovery of low-intensity broad spectral components (FWHM is approximately equal to 40 A or 2400 km/s) in the bright nebular lines H-alpha, H-beta, and forbidden O III is reported. The broad spectral components are detected over a large spatial extent (not less than 500 pc) centered on the nebula. Several mechanisms for broadening nebular lines are explored: stellar winds, Thomson scattering by hot gas, supernova remnants, and superbubble blowout. All mechanisms have problems. Superbubble blowout, which is the only known mechanism capable of accelerating interstellar gas over such a volume of space, does not appear consistent with the physical properties of the H II region NGC 2363 or with the nature of the host galaxy. It is concluded that the broad nebular lines are probably due to very high velocity gas whose origin is, at present, unknown.

Roy, Jean-Rene↗

The First United States Microgravity Laboratory

The United States Microgravity Laboratory (USML-1) is one part of a science and technology program that will open NASA's next great era of discovery and establish the United States' leadership in space. A key component in the preparation for this new age of exploration, the USML-1 will fly in orbit for extended periods, providing greater opportunities for research in materials science, fluid dynamics, biotechnology, and combustion science. The major components of the USML-1 are the Crystal Growth Furnace, the Surface Tension Driven Convection Experiment (STDCE) Apparatus, and the Drop Physics Module. Other components of USML-1 include Astroculture, Generic Bioprocessing Apparatus, Extended Duration Orbiter Medical Project, Protein Crystal Growth, Space Acceleration Measurement System, Solid Surface Combustion Experiment, Zeolite Crystal Growth and Spacelab Glovebox provided by the European Space Agency.

Powers, C. Blake↗

Discovery of a Magnetar Associated with the Soft Gamma Repeater SGR 1900 + 14

The soft-gamma repeater (SGR) 1900 + 14 became active again on June 1998 after a long period of quiescence; it remained at a low state of activity until August 1998, when it emitted a series of extraordinarily intense outbursts. We have observed the source with RXTE twice, during the onset of each active episode. We confirm the pulsations at the 5.16 s period reported earlier from SCR 1900 + 14 . Here we report the detection of a secular spindown of the pulse period at an average rate of 1.1 x 10(exp -10) s/s. In view of the strong similarities between SGRs, we attribute the spindown of SGR 1900 + 14 to magnetic dipole radiation, possibly accelerated by a quiescent flux, as in the case of SGR 1806 - 20. This allows an estimate of the pulsar dipolar magnetic field, which is 2 - 8 x 10(exp 14) G. Our results confirm that SGRs are magnetars.

Kouveliotou, Chryssa↗

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Roadmap for transforming heterogeneous catalysis with artificial intelligence

Artificial intelligence (AI) is poised to transform heterogeneous catalysis, opening avenues for catalytic materials discovery. By uncovering intricate patterns in high-dimensional data, AI has been reshaping our pursuit of sustainable catalytic processes across the energy, environmental and chemical sectors. This promise, however, hinges on overcoming fundamental barriers, including limitations in data availability and quality, challenges in the generalizability and interpretability of data-augmented decisions, and the persistent gap between in silico predictions and experiments. Furthermore, we outline a forward-looking roadmap for deeply integrating AI into heterogeneous catalysis with an AI-ready data ecosystem, multimodal foundation models, and ultimately autonomous laboratories to accelerate the development of next-generation catalytic technologies via AI-empowered human–machine collaboration.

Computational methods↗

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. Refined nuclear interaction models in these energy regimes will also be valuable for other applications, such as measurements of reactor, solar, and atmospheric neutrinos. This manuscript discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. This white paper discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗

A Foreshock Model for Interstellar Shocks of Solar Origin: Voyager 1 and 2 Observations

The Voyager 1 (V1) and Voyager 2 (V2) spacecraft were launched in 1977 on a mission to explore the outer planets and reach the heliopause, the boundary between the hot solar plasma and the relatively cool interstellar plasma. V1 reached the heliopause on 2012 August 25, at 121.6 au, and V2 reached the heliopause on 2018 November 5, at 119.0 au. One of their remarkable discoveries was the detection of shocks propagating into the interstellar plasma from energetic solar events. These shocks are typically preceded by electron plasma oscillations excited by electron beams streaming along interstellar magnetic field lines ahead of the shocks. The frequencies of the plasma oscillations have now provided radial electron density profiles in the outer heliosphere and in the interstellar medium to radial distances of more than 145 au. The oscillations are typically preceded by bursts of high-energy ∼5–100 MeV electrons. These electron bursts are interpreted as being due to the reflection (and acceleration) of cosmic-ray electrons by the shock at the time the shock first contacts the magnetic field line that passes through the spacecraft. Relative timing between the cosmic rays reflected by the shock and the onset of the plasma oscillations allow us, for the first time, to estimate the energy, ∼20–100 eV, of the electron beams responsible for the plasma oscillations. These observations are combined into a self-consistent model called the foreshock model that describes the interaction of shocks of solar origin with the interstellar plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Discovery of a Magnetar Associated with the Soft Gamma Repeater SGR 1900+14

The soft gamma repeater SGR 1900+14 became active again in June 1998 after a long period of quiescence; it remained at a low state of activity until August 1998, when it emitted a series of extraordinarily intense outbursts. We have observed the source with the Rossi X-Ray Timing Explorer twice, during the onset of each active episode. We confirm the pulsations at the 5.16 s period reported earlier from SGR 1900+14. Here we report the detection of a secular spin-down of the pulse period at an average rate of 1.1 x 10(exp -10)s/s. In view of the strong similarities between SGRs, we attribute the spin-down of SGR 1900+14 to magnetic dipole radiation, possibly accelerated by a quiescent flux, as in the case of SGR 1806-20. This allows an estimate of the pulsar dipolar magnetic field, which is (2-8) x 10(exp 14) G. Our results confirm that SGRs are magnetars.

Kouveliotou, C.↗

Accelerating Space Life Sciences: Successes and Challenges of Biospecimen and Data Sharing

NASA's current human space flight research is directed towards enabling human space exploration beyond Low Earth Orbit (LEO). To that end, NASA Space Flight Payload Projects; Rodent Research, Cell Science, and Microbial Labs, flown on the International Space Station (ISS), benefit the global life sciences and commercial space communities. Verified data sets, science results, peer-reviewed publications, and returned biospecimens, collected and analyzed for flight and ground investigations, are all part of the knowledge base collected by NASA's Human Exploration and Operations Mission Directorate's Space Life and Physical Sciences Research and Applications (SLPSRA) Division, specifically the Human Research and Space Biology Programs. These data and biospecimens are made available through the public Life Sciences Data Archive (LSDA) website to promote basic discovery, pre-clinical and clinical science.The NASA Institutional Scientific Collection (ISC), stores flight and ground biospecimens from Space Shuttle and ISS programs. These specimens are curated and managed by the Ames Life Sciences Data Archive (ALSDA), an internal node of NASA's LSDA. The ISC stores over 30,000 specimens from experiments dating from 1984 to present. Currently available specimens include tissues from the circulatory, digestive, endocrine, excretory, integumentary, muscular, neurosensory, reproductive, respiratory and skeletal systems.NASA's biospecimen collection represents a unique and limited resource of unique spaceflight payload and ground control research subjects. These specimens are harvested according to well established SOPs that maintain their quality and integrity. Once the primary scientific objectives have been met, the remaining specimens are made available to provide secondary opportunities for complementary studies or new investigations to broaden research without large expenditures of time or resources. Website: https://lsda.jsc.nasa.gov/

Scott, Ryan T.↗