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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

Applications of emulation and Bayesian methods in heavy-ion physics

Abstract Heavy-ion collisions provide a window into the properties of many-body systems of deconfined quarks and gluons. Understanding the collective properties of quarks and gluons is possible by comparing models of heavy-ion collisions to measurements of the distribution of particles produced at the end of the collisions. These model-to-data comparisons are extremely challenging, however, because of the complexity of the models, the large amount of experimental data, and their uncertainties. Bayesian inference provides a rigorous statistical framework to constrain the properties of nuclear matter by systematically comparing models and measurements. This review covers model emulation and Bayesian methods as applied to model-to-data comparisons in heavy-ion collisions. Replacing the model outputs (observables) with Gaussian process emulators is key to the Bayesian approach currently used in the field, and both current uses of emulators and related recent developments are reviewed. The general principles of Bayesian inference are then discussed along with other Bayesian methods, followed by a systematic comparison of seven recent Bayesian analyses that studied quark-gluon plasma properties, such as the shear and bulk viscosities. The latter comparison is used to illustrate sources of differences in analyses, and what it can teach us for future studies.

Paquet, Jean-François (ORCID:0000000187368171)↗

Plant Metabolic Network 16: expansion of underrepresented plant groups and experimentally supported enzyme data

Abstract The Plant Metabolic Network (PMN) is a free online database of plant metabolism available at https://plantcyc.org. The latest release, PMN 16, provides metabolic databases representing >1200 metabolic pathways, 1.3 million enzymes, >8000 metabolites, >10 000 reactions and >15 000 citations for 155 plant and green algal genomes, as well as a pan-plant reference database called PlantCyc. This release contains 29 additional genomes compared with PMN 15, including species listed by the African Orphan Crop Consortium and nonflowering plant species. Furthermore, 52 new enzymes with experimentally supported function information have been included in this release. The single-species databases contain a combination of experimental information from the literature and computationally predicted information obtained through PMN’s database generation pipeline for a single species, while PlantCyc contains only experimental information but for any species within Viridiplantae. PMN is a comprehensive resource for querying, visualizing, analyzing and interpreting omics data with metabolic knowledge. It also serves as a useful and interactive tool for teaching plant metabolism.

Hawkins, Charles (ORCID:0000000312849047)↗

DXRD : a user-friendly suite of two- and multiple-beam dynamical X-ray diffraction programs

The DXRD program suite consisting of a series of dynamical theory programs is introduced for computing dynamical X-ray diffraction from single crystals. Its interactive graphical user interfaces (GUIs) allow general users to make complicated calculations with minimal effort. It can calculate plane-wave Darwin curves of single crystals (or multiple crystals) for both the Bragg and Laue cases, including grazing-incidence diffraction and backward diffraction (with Bragg angles approaching 90°). It is also capable of simulating rocking curves for divergent incident X-ray beams with finite bandwidths. A unique feature of DXRD is that it provides a convenient GUI-based multiple-beam diffraction program that can accurately compute arbitrary N-beam diffraction of any geometry using a universal 4N × 4N matrix method. DXRD also provides a mapping program for plotting all the multiple-beam diffraction lines (monochromator glitches) in the azimuth–energy coordinate system. All these functions make DXRD a convenient and powerful software tool for designing crystal-based synchrotron/X-ray optics (monochromators, analyzers, polarizers, phase plates etc.) and for crystal characterization, X-ray spectroscopy and X-ray diffraction teaching.

Bragg reflection↗

Coherent diffraction imaging in the undergraduate laboratory

We present an undergraduate optics instructional laboratory designed to teach skills relevant to a broad range of modern scientific and technical careers. In this laboratory project, students image a custom aperture using coherent diffraction imaging, while learning principles and skills related to digital image processing and computational imaging, including multidimensional Fourier analysis, iterative phase retrieval, noise reduction, finite dynamic range, and sampling considerations. After briefly reviewing these imaging principles, we describe the required experimental materials and setup for this project. Our experimental apparatus is both inexpensive and portable, and a software application we developed for interactive data analysis is freely available.

Porter, J. Nicholas↗

A self-supervised robotic system for autonomous contact-based spatial mapping of semiconductor properties

Integrating robotically driven contact-based material characterization techniques into self-driving laboratories can enhance measurement quality, reliability, and throughput. While deep learning models support robust autonomy, current methods lack reliable pixel-precision positioning and require extensive labeled data. To overcome these challenges, we propose an approach for building self-supervised autonomy into contact-based robotic systems that teach the robot to follow domain expert measurement principles at high throughputs. We demonstrate the performance of this approach by autonomously driving a 4-DOF robotic probe for 24 hours to characterize semiconductor photoconductivity at 3025 uniquely predicted poses across a gradient of drop-casted perovskite film compositions, achieving throughputs of more than 125 measurements per hour. Spatially mapping photoconductivity onto each drop-casted film reveals compositional trends and regions of inhomogeneity, valuable for identifying manufacturing defects. With this self-supervised neural network–driven robotic system, we enable high-precision and reliable automation of contact-based characterization techniques at high throughputs, thereby allowing measurement of previously inaccessible yet important semiconductor properties for self-driving laboratories.

Science & Technology - Other Topics↗

Siting Lab [SWR-24-95]

Siting Lab contains a collection of user-friendly tutorials and guides for working with the Siting Lab (https://data.openei.org/siting_lab) data within the context of the reV model. The python code examples demonstrate the creation and transformation of Siting Lab data into reV compliant format as well as working with the reV model inputs and outputs. Specifically, Siting Lab provides a collection of Jupyter Notebooks that serve as guides for working with data from NREL's spatial analysis portfolio. These notebooks teach users how to create and interact with reV data in order to facilitate external use of the model. The guides in this repository reference NREL's Supply Curve data as well as Siting Lab spatial data available on OEDI.

Lopez, Anthony↗

Hydropower Market Game

SF-25-121 The Hydropower Market Game is an interactive educational software developed to teach fundamental concepts of hydropower generation, operations, and its role within electricity markets. Developed in Python and powered by Pygame, the game combines narrative-driven learning with progressive, hands-on levels where players explore topics such as the relationship between water flow and power generation, dam operations, pumped-storage systems, market interactions, and environmental constraints.Designed to support outreach and workforce development initiatives, the game provides an intuitive and engaging way to build energy literacy and raise awareness of hydropower’s contribution to the nation’s energy system.

Ploussard, Quentin [Argonne National Laboratory (A↗

ICAT: The Interactive Corpus Analysis Tool

The Interactive Corpus Analysis Tool (ICAT) is a Python library for creating dashboards to explore textual datasets and build simple binary classification models to help filter through them and focus on entries of interest. This tool uses a form of interactive machine learning (IML), a paradigm of “machine teaching” (Simard et al., 2017) that sits at the intersection of the fields of human computer interaction (HCI), visual analytics, and machine learning. The intent of ICAT is to allow subject matter experts (SME) with limited to no experience in machine learning to benefit from an iterative human-in-the-loop (HITL) approach to building their own model without needing to understand the details of the underlying algorithm. This interactivity is achieved by allowing the user to create features, label data points, and visually manipulate a representation of the features to manually cluster and investigate data, while a model is trained on the fly based on these actions. ICAT is built on top of the Panel (Holoviz, 2018) library, using a combination of Vega, a custom IPyWidget using D3, and ipyvuetify, and is intended to be used inside of a Jupyter environment.

Martindale, Nathan [Oak Ridge National Laboratory ↗

2023 High Energy Density Science Summer School

The University of California San Diego (UCSD) hosted the High Energy-Density Science (HEDS) Summer School from July 17 – 28, 2023 on the UCSD campus. The goal of the Summer School was to introduce new talent to the breadth of the U.S. HEDS community through lectures, engaging workshops, and discussion sessions with leaders in academia and the national laboratories. The objectives were to inspire young scientists to pursue graduate and professional careers in the fields of HEDS, teach them fundamental HEDS and critical skills, and grant them the opportunity to network with leading academic and national laboratory researchers. Our focus was to attract promising early-career students from across the country.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reimagining DOE Lab-University Partnership for the AI Era

This report describes observations and suggestions from a workshop on needs for partnerships between national laboratories and universities in the AI era. The workshop took place over two days in March of 2024 at Texas A&M University’s Bush School of Government and Public Service Washington, D.C., teaching site. Through good fortune this happened to be at the peak of cherry blossom season and the weather was beautiful. In attendance were professors and leadership from universities across the nation, members of four national laboratories, and a representative of the Office of Critical and Emerging Technologies in Department of Energy (DOE). This group spanned a broad range of disciplines—applied mathematics, materials science, nuclear security, intelligence, and more. The workshop also had the benefit of insights from Charlie McMillan, former director of Los Alamos National Laboratory, and retired Air Force Lieutenant General Jack Shanahan, who led AI efforts at the Pentagon.

42 ENGINEERING↗

In Vitro Evolution and Computational Approaches to Predict, Prevent and Control Future Pandemics

The natural tendency of virus to mutate and the under-sampling of the environment makes it difficult to become aware of the emergence of new viral strains with pandemic potential. Being able to predict what mutations make a virus more infective might allow to spot such strains with minimal sampling and potentially allow to predict/prevent the next pandemic. The team attempted to mimic natural viral mutations and recombination through computational and experimental methods producing a variety of mutants of a SARS-COV-2 protein (receptor binding domain, RBD, of spike protein) responsible for viral entry in mammalian cells. The library of mutants was then interrogated for ability and lack-there-of to interact with the host cell receptor ushering viral entry, Angiotensin-converting enzyme 2 (ACE2). The negative and positive data set is intended to “teach the rules” of virus-host receptor interaction. Additionally, the positive clones were used to screen a set of antibody mutants designed to widen the breadth of viral mutants recognition, to demonstrate that this kind of libraries could also be a tool to produce antibody therapeutics impervious to viral mutation, even before a pandemic strain is discovered.

59 BASIC BIOLOGICAL SCIENCES↗

Development and Validation of Smart Building Technology Modules for Academic and Professional Education (Final Technical Report)

Smart building technologies can improve building energy efficiency and resilience, reduce carbon emissions, and provide load flexibility to the grid. However, in both college curricula and building professionals’ continuing education, there is a lack of systematic instruction on smart building technologies. Slipstream, partnering with Texas A&M University (TAMU), the Society of Building Science Educators (SBSE), and the National Institute of Building Sciences (NIBS), developed a semester-long smart building curriculum for college students and 16 training videos for building professionals and the general public. The education and training cover the drivers and benefits of smart building technologies, key building energy systems, the latest sensor technologies and IoT devices, and focus on topics related to smart building controls (i.e., energy management information systems, smart building control platforms, cybersecurity, grid-interactive-efficient buildings [GEBs], smart building control methods, and occupant-centric control). The smart building curriculum for college students was taught at TAMU in the Spring semester of 2024 as part of the validation process. Student feedback was collected and summarized in a validation report by TAMU. The curriculum material was also reviewed by SBSE faculty who are interested in teaching smart building technology-related courses. Suggestions on revisions and better adoption of the materials by other faculty across the architectural, engineering, and construction (AEC) domains were compiled in a distinct validation report by SBSE. The SBSE validation report was used to create structured subsets of the curriculum material for adoption at different levels in different sub-disciplines. These subsets are categorized and offered on the SBSE website (https://www.sbse.org/courses/Smart-Building-Technologies). The 16 training videos for building professionals and the general public were previewed by 17 industry experts, and feedback and suggested changes were incorporated into the final version of these videos. The videos are organized into a smart building technology training course and published on the Whole Building Design Guide website (https://www.wbdg.org/ce/doe/bto/sbtt), which is hosted by the National Institute of Building Sciences (NIBS). Project team members created marketing materials to promote the awareness of these free, publicly available education and training resources. Outreach and marketing activities included creating short promotional videos, building project webpages, making project announcements on social media, conducting an email campaign, and directly reaching out to faculties and building professionals. This report describes the project approach, provides outlines of the training materials, along with links to resources, and identifies lessons learned in creating the content. We also suggest ways to scale the instruction of smart building concepts to empower the workforce to accelerate the adoption of smart building technologies in the real world.

99 GENERAL AND MISCELLANEOUS↗

Market Driven Residential Energy Codes: Comparing Performance in a Changing Technological Environment

The research project is undertaken to better understand the changing relationship between the two basic methods of building energy code compliance – prescriptive and performance – and how those methods relate to each other with respect to advancements in building energy computer simulation standards and capabilities. The International Energy Efficiency Code (IECC) is a model code adopted by many jurisdictions across the United States. Historically, the prescriptive compliance methodology has been preferred in most jurisdictions. The prescriptive methodology requires meeting or exceeding specific efficiency minimums for each envelope component. This tends to be a simple method to teach and verify. A more involved prescriptive alternative called the Total UA alternative is sometimes used. This method requires some multiplication, summing, and comparison to compute, so it is done with a fairly simple computer program. However, advances in computer and building energy simulation technology have resulted in increased use of more detailed performance compliance methods. The performance compliance method establishes the annual energy cost threshold via hourly simulation models. The compliance threshold is determined with a comparison building model simulation with geometry similar to the proposed home and with energy feature parameters and efficiencies as specified in the IECC. This project examines relationships between the two methods of building energy code compliance, including: • Overall annual energy use based on utility bill analysis by compliance method • Code official work processes with respect to compliance methods • Gaps and issues associated with building code compliance methods • Simulated energy use difference between compliance methods • Code compliance cost as a function of compliance method • Code compliance labeling effectiveness for high performance residences • Getting to net zero energy use and net zero greenhouse gas emissions through high performance code alternatives • Electronic code permitting and compliance alternatives

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CIE Curriculum Guide (V.2.0)

The Cyber-Informed Engineering (CIE) Curriculum Guide offers a comprehensive framework, guidance, and resources for integrating CIE into university-level engineering programs and related educational activities. The primary goal is to help educators adopt CIE principles into their teaching to produce future engineers and technicians who understand digital risks in modern engineered systems, thereby addressing the nation’s infrastructure resilience needs. This guide outlines practical integration examples, links to resources to accelerate CIE adoption, and shares insights from partner academic institutions on various implementation strategies. CIE is a framework for embedding engineered controls that mitigate the impact of cyber-attacks in any cyber-physical system used in critical energy infrastructure and other sectors. Developed by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), the National Cyber-Informed Engineering Strategy emphasizes embedding CIE into formal education, training, and credentialing. This guide supports this strategic objective by providing examples of integrating CIE concepts into engineering curricula, from class activities to new courses and certificate programs. The importance of educating cyber-informed engineers is underscored by the evolving cybersecurity threats facing engineered systems. As industrial control systems (ICS) increasingly incorporate digital technologies, the responsibility for security extends to both cyber professionals and engineers. CIE addresses critical gaps in designing and protecting physical systems with digital components against cyber risks, ensuring engineers consider digital risk throughout the engineering design lifecycle. Currently, engineering education does not routinely include cyber-informed principles, highlighting a gap in addressing modern engineering system risks. This guide advocates for updating engineering curricula to include digital risk management as a fundamental element. By doing so, future engineers will be equipped to design resilient systems that mitigate digital risks from the outset. Through this guide, engineering faculty can integrate CIE into their curricula, bridging the gap between digital risk and engineering. This approach prepares a cyber-informed workforce capable of safeguarding the cyber-physical systems crucial to national security and public welfare. By embedding CIE into education and training, institutions can produce engineers and technicians who can effectively mitigate cyber impacts throughout the engineering design lifecycle, resulting in more secure critical infrastructures.

42 - ENGINEERING↗

Driving Affordable Energy Through Utility Program Design

The presentation is aimed to teach participants about achieving affordable energy through utility program design. Learning objectives include: identify key utility program characteristics that support affordability and consumer choice; apply best practices in outreach, eligibility, and evaluation to improve program design; and evaluate strategies for aligning program design with customer needs and regulatory goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Transitions, Dynamics, and Driven States in Quantum Magnets (Final Report Revised)

Transitions into unusual electronic, optical, and magnetic states at the absolute zero of temperature display special properties that teach us about fundamental quantum mechanics and also underlie important technologies. These so-called quantum phase transitions intertwine the static and dynamical responses of the materials changing state. They are extremely sensitive to the effects of disorder and etch in high relief the role of quantum fluctuations. There are ample questions remaining about the character of such transitions and the nature of the competing quantum states. There are also opportunities to drive quantum materials out of equilibrium, with the possibility of new types of correlated and coherent order, and new ways to access the dynamical evolution of ground and excited states. We have investigated how the order develops in time and space, and the nature of the final configurations. We are able to compare and contrast classical and quantum excitations in our experimental system of choice, and thereby can trace the relative speed by which the system settles into its lowest-energy ground state. This comparison of quantum and classical annealing protocols lies at the heart of strategies for harnessing the power of quantum computers dedicated to optimization problems. A combination of magnetic susceptibility measurements at finite frequency where the magnetic spins are queried by an external ac field, dc magnetometry measurements that characterize the macroscopic strength of magnetic order and its resistance to change, noise measurements that reveal the microscopic fluctuations of the spins as they prepare to change state, and microwave spectroscopy to look at the response of both the electronic and nuclear degrees of freedom, have been performed as functions of temperature, magnetic field, frequency, excitation amplitude, magnetic spin concentration, and disorder. This combination of probes addresses issues of stability over time, overlap between spin states, the ability of the spins to respond independently or coherently, and the promise of control on the nanometer length scale. The research reported here provides insights into fundamental quantum physics. It also addresses the question of how best to use complex systems, such as magnetic solids, to stably process quantum information.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗