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DOE OSTI2024

Down-selection of biomolecules to assemble “reverse micelle” with perovskites

Abstract Biological molecule-semiconductor interfacing has triggered numerous opportunities in applied physics such as bio-assisted data storage and computation, brain-computer interface, and advanced distributed bio-sensing. The introduction of electronics into biological embodiment is being quickly developed as it has great potential in providing adaptivity and improving functionality. Reciprocally, introducing biomaterials into semiconductors to manifest bio-mimetic functionality is impactful in triggering new enhanced mechanisms. In this study, we utilize the vulnerable perovskite semiconductors as a platform to understand if certain types of biomolecules can regulate the lattice and endow a unique mechanism for stabilizing the metastable perovskite lattice. Three tiers of biomolecules have been systematically tested and the results reveal a fundamental mechanism for the formation of a “reverse-micelle” structure. Systematic exploration of a large set of biomolecules led to the discovery of guiding principle for down-selection of biomolecules which extends the classic emulsion theory to this hybrid systems. Results demonstrate that by introducing biomaterials into semiconductors, natural phenomena typically observed in biological systems can also be incorporated into semiconducting crystals, providing a new perspective to engineer existing synthetic materials.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Minimum stabilizing energy release for mixing processes

Diffusive operations, which mix the populations of different elements of phase space, can irreversibly transform a given initial state into any of a spectrum of different states from which no further energy can be extracted through diffusive operations. We call these ground states. Here, the lower bound of accessible ground-state energies represents the maximal possible release of energy. This lower bound, sometimes called the diffusively accessible free energy, is of interest in theories of instabilities and wave-particle interactions. On the other hand, the upper bound of accessible ground-state energies has escaped identification as a problem of interest. Yet, as demonstrated here, in the case of a continuous system, it is precisely this upper bound that corresponds to the paradigmatic “quasilinear plateau” ground state of the bump-on-tail distribution. Although for general discrete systems the complexity of calculating the upper bound grows rapidly with the number of states, using techniques adapted from treatments of the lower bound, the upper bound can in fact be computed directly for the three-state discrete system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

FitCache: A Transparent Drop-In Framework for Multi-Tier Caching to Accelerate Distributed Deep Learning Workloads

Training in Deep learning (DL) remains highly compute- and data-intensive, with I/O becoming a critical bottleneck as models and datasets scale. Recent studies report that data loading can dominate training time, especially on large-scale HPC systems with shared parallel file systems (PFS). Existing caching approaches either rely on single-tier designs or require intrusive modifications to training pipelines, limiting their portability and effectiveness. In this work, we present FitCache, a transparent drop-in framework for multi-tier caching to accelerate distributed DL training by coordinating fast local memory (e.g., DRAM, Persistent Memory (PMem)) and NVMe as hierarchical caches atop PFS. Our design adapts to hardware diversity, i.e., if NVMe is missing, memory transparently acts as a caching tier, ensuring stable performance. FitCache transparently intercepts I/O requests and issues concurrent fetches across all tiers, returning data from the fastest responder without centralized metadata or static redirection paths. FitCache adapts to dynamic workloads and heterogeneous clusters while maintaining POSIX compatibility. Experiments on Frontier (2048 GPUs) and smaller research clusters show that FitCache reduces training time by up to 40% and per-batch I/O latency by up to 71.6% compared to Lustre Orion PFS, offering a drop-in solution for scalable DL training.

Hu, Guangxing [ORNL] (ORCID:0009000283203614)↗

DOE OSTI2023

Validation of Play Fairway Analysis of the geothermal potential of Camas Prairie, south-central Idaho, by an exploration well

Abstract Play Fairway Analysis (PFA) methodology was adapted for geothermal exploration at Camas Prairie, Idaho. Geophysical data, structural and geologic mapping, volcanic rock ages and vent locations, and the distribution of thermal springs and wells all indicated a relatively high geothermal potential along the southern margin of the Prairie. An exploration well (USU Camas-1) was drilled to a depth of 618.3 m to validate the PFA. A permeable zone was encountered at ~ 357.5 m with a maximum measured temperature of ~ 80 °C, which was suppressed following the injection of cold water. A moderate transmissivity of ~ 0.25–1 cm 2 /s estimated from an injection test as well a seasonal artesian flow at ~ 0.7 L/s corroborate the presence of a permeable zone. The existence of a lacustrine clay seal was confirmed near the bottom of the basin-fill sediment occupying the upper 314 m of the well. Geothermometers suggest the USU Camas-1 well water equilibrated at a reservoir temperature of ~ 120 °C. Based on the locations of both thermal and cold wells, geothermal fluids appear to be flowing upward along one or both of two fault systems. The presence of young basalts and elevated helium isotope ratios suggest that the heat source of Camas Prairie is magmatic. However, the faults may be acting as a conduit for geothermal fluids to rise from great depth without a shallow magmatic source being present. Camas Prairie is a promising area for geothermal development, but the relatively low reservoir temperatures indicate this resource may not be suitable for electric generation. Perhaps the best use would be for heating.

Lachmar, Thomas E. (ORCID:0000000249640119)↗

DOE OSTI2025

Establishing Pb-203 production from electrodeposited Tl targets at Brookhaven National Laboratory

Background: Promising developments in Pb-212 radiopharmaceutical therapies have increased demand for Pb-203 diagnostic agents. Building on previous work from various isotope production facilities, this study optimized Pb-203 production from electrodeposited Tl targets at Brookhaven National Laboratory (BNL). The additional supply of Pb-203 may help meet growing preclinical and clinical demands. Results: Two Tl targets were irradiated at the Brookhaven Linac Isotope Producer facility with 30 ± 1 MeV protons, measured using previously published cross section data. Distribution coefficients for Pb Resin in acetate media were investigated for both Na + and K + cations, where potassium acetate was ~ 4 times more effective at stripping Pb from the Pb Resin. The Tl electrodeposition was optimized to deposit 350 mg of Tl (~ 60 mg/cm 2 ) on Au backing in under 6 h. The proposed separation process was completed in < 1.5 h and achieved > 98% and 92 ± 3% recovery of Tl and Pb, respectively, with an overall Tl-Pb separation factor of 6 × 10 5 . The experimentally measured half-life of Pb-203 was 52.4 ± 0.7 h, agreeing with 51.93 ± 0.02 h reported by the National Nuclear Data Center. The radioisotopic purity of the Pb fraction at 24 h post end of bombardment (EOB) from a 24 h irradiation was 66% Pb-203, 28% Pb-201, and 6% Pb-200. Following chemical separation, the Pb-203 produced in this work (21 MBq Pb-203 EOB) achieved apparent molar activities of 10 ± 5 and 0.9 ± 0.5 GBq/µmol for [ 203 Pb]Pb-DOTAM and [ 203 Pb]Pb-DO3A, respectively, decay corrected to EOB. Data derived from this work suggests BNL can produce > 10’s GBq Pb-203 with > 99% radiochemical and radioisotopic purity from Tl-205 for worldwide distribution. Conclusions: The production and separation of Pb-203 from natural Tl target material was successfully demonstrated at BNL. Existing methods were adapted and optimized for the facilities at BNL. Results from this work will guide future large-scale Pb-203 production opportunities at BNL for clinical applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2021

Data-Driven Exploration of Climate Attractor Manifolds For Long-Term Predictability

Focal Area: This white paper responds to Focal Area 3. We seek to gain insight into decadal-scale climate predictability by applying novel manifold-finding probabilistic AI techniques to the complex data produced by Earth System models (ESMs) such as E3SM. The associated portfolio of research activities leverages DOE’s asset mix of HPC platforms, climate expertise, climate simulation codes, and AI expertise. Science Challenge: Climate and climate models are dynamical systems exhibiting properties that are interpretable through chaos theory. The theory contains an important concept that is relevant to multi-decade-scale climate prediction: a chaotic attractor. While the space containing all the possible states of the Earth’s atmosphere and ocean, the possible weather, is large, the realized states tend to stay near the smaller-dimensioned attractor. This behavior is responsible for the “order behind the irregularity” [1] of climate phenomena. Climate change can be thought of as a change in the properties of the attractor, and predicting the climate over years to decades is equivalent to predicting how those properties will change. To date, the attractor has been a useful conceptual tool, but has not been amenable to direct characterization. A new development is the advent of efficient high-dimensional manifold-finding probabilistic AI techniques, which permit a data-driven characterization of the ESM attractor and its probability distribution over weather states. Such a characterization would result in a natural dimensional reduction — a “non-linear Principal Components Analysis (PCA) adapted to climate simulation data” — leading to important advances in scenario-based long-term climate prediction, long-term prediction of water cycle extremes, ESM verification, inter-model comparison, and process model development.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Aerodynamic influence coefficient method using singularity splines

A numerical lifting surface formulation, including computed results for planar wing cases is presented. This formulation, referred to as the vortex spline scheme, combines the adaptability to complex shapes offered by paneling schemes with the smoothness and accuracy of loading function methods. The formulation employes a continuous distribution of singularity strength over a set of panels on a paneled wing. The basic distributions are independent, and each satisfied all the continuity conditions required of the final solution. These distributions are overlapped both spanwise and chordwise. Boundary conditions are satisfied in a least square error sense over the surface using a finite summing technique to approximate the integral. The current formulation uses the elementary horseshoe vortex as the basic singularity and is therefore restricted to linearized potential flow. As part of the study, a non planar development was considered, but the numerical evaluation of the lifting surface concept was restricted to planar configurations. Also, a second order sideslip analysis based on an asymptotic expansion was investigated using the singularity spline formulation.

Mercer, J. E.↗

NASA NTRS1989

Robotic sampling system for an unmanned Mars mission

A major robotics opportunity for NASA will be the Mars Rover/Sample Return Mission which could be launched as early as the 1990s. The exploratory portion of this mission will include two autonomous subsystems: the rover vehicle and a sample handling system. The sample handling system is the key to the process of collecting Martian soils. This system could include a core drill, a general-purpose manipulator, tools, containers, a return canister, certification hardware and a labeling system. Integrated into a functional package, the sample handling system is analogous to a complex robotic workcell. Discussed here are the different components of the system, their interfaces, forseeable problem areas and many options based on the scientific goals of the mission. The various interfaces in the sample handling process (component to component and handling system to rover) will be a major engineering effort. Two critical evaluation criteria that will be imposed on the system are flexibility and reliability. It needs to be flexible enough to adapt to different scenarios and environments and acquire the most desirable specimens for return to Earth. Scientists may decide to change the distribution and ratio of core samples to rock samples in the canister. The long distance and duration of this planetary mission places a reliability burden on the hardware. The communication time delay between Earth and Mars minimizes operator interaction (teleoperation, supervisory modes) with the sample handler. An intelligent system will be required to plan the actions, make sample choices, interpret sensor inputs, and query unknown surroundings. A combination of autonomous functions and supervised movements will be integrated into the sample handling system.

Chun, Wendell↗

NASA NTRS2004

Distribution of Near-Surface Ground Ice on Mars

During the course of this grant we made significant progress in our understanding of martian ground ice in areas of theoretical and laboratory research. We recently completed a manuscript comparing a new map of ground-ice stability with leakage neutron data for the southern hemisphere . In this manuscript we incorporated several improvements to a model of ground ice stability. We quantitatively compared measured epithermal-neutron flux with predicted ice-table burial depth and found that the observed distribution of ground ice is consistent with ice in diffusive equilibrium with the atmosphere. In addition to this theoretical study we have adapted an experimental apparatus, designed for measuring ice condensation in antarctic soils , to martian permafrost.

Mellon, Michael T.↗

NASA NTRS2008

Intelligent Sensors for Integrated Systems Health Management (ISHM)

IEEE 1451 Smart Sensors contribute to a number of ISHM goals including cost reduction achieved through: a) Improved configuration management (TEDS); and b) Plug-and-play re-configuration. Intelligent Sensors are adaptation of Smart Sensors to include ISHM algorithms; this offers further benefits: a) Sensor validation. b) Confidence assessment of measurement, and c) Distributed ISHM processing. Space-qualified intelligent sensors are possible a) Size, mass, power constraints. b) Bus structure/protocol.

Schmalzel, John L.↗

NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗

DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1996

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz.

Burdisso, Ricardo↗

NASA NTRS1994

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

Burdisso, Ricardo↗

DOE OSTI2024

Parallel Variable Population Multi-Objective Optimizer (pvpmoo) v1.0

This is a parallel variable population multi-objective optimizer with an adaptive unified differential evolution algorithm or a genetic algorithm. It can also be used for single objective optimization. Some features of this code include: 1) The population size varies from generation to generation to save the total # of objective function evaluations. 2) The population is uniformly distributed to a number of parallel processors for simultaneous objective function evaluation. 3) The objective function evaluation can be attained from an external simulation program with control variables in its input file and objectives calculated from its output files. 4) The optimizer includes an adaptive unified differential evolution algorithm and a real value genetic algorithm. The parameters in the unified differential evolution algorithm can be chosen to attain any mutation schemes in the published literature.

Qiang, Ji↗

DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

The purpose of this technical report is to document the efforts to design and test two inlet systems for aerosol sampling suitable for deployment on a medium-sized fixed-wing Uncrewed Aerial System (UAS). This work, which was supported by the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, was conducted at the Pacific Northwest National Laboratory (PNNL) for the ARM Aircraft Facility (AAF) starting in November 2017. The current work is a part of AAF efforts to instrument the ArcticShark (a mid-sized UAS owned and operated by the AAF) for atmospheric research and develop a scientific payload for deployment on a similar-sized UAS with minimal adaptation and integration. An aerosol inlet system is necessary to sample and transport ambient air sample to the scientific instrumentation with minimal distortions to the aerosols. Two isokinetic aerosol inlets were designed: the first is a simple passive system for a single instrument suitable to be installed in a wing pylon; the second is a system with active control designed to sample and distribute air among several heterogeneous instruments and to provide basic humidity control of the air sample so that the measured aerosol parameters should correspond to “dry” conditions (a common requirement). Both systems could be easily adapted for deployment on another platform and/or with a different set of instrumentation. Several conducted flight tests showed that the inlets’ performance met our design goals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

42 ENGINEERING↗

DOE OSTI2026

Nondestructive Modular Leak Detection in 3D Printed 316L Stainless Steel Pipes via Laser Powder Bed Fusion

This research investigates the leak detection features of 316L Stainless Steel pipe structures manufactured via Laser Powder Bed Fusion (LPBF). This work involves the design of a modular sensor system integrating nondestructive evaluation (NDE) methods, including thermal imaging and ultrasonic frequency detection to detect and characterize leaks in components. This aims to improve leak detection sensitivity within medium-pressure gas systems, during continuous operation without halting flow or introducing safety risks. The system could be adaptable for use on unmanned aerial vehicles (UAVs), enabling remote leak detection in active environments. A custom pneumatic system incorporating temperature and pressure sensors was assembled to detect leaks in LPBF-printed 316L SS tee pipes. Experimental results and simulations confirm the system’s effectiveness in leak detection and material evaluation. This research program also integrated a Python-based image recognition platform based on a metallography and optical microscopy to assess the porosity and complement the leak detection data on the printed structures. This allows a detailed analysis of pore distribution and internal leak paths, which could compromise structural integrity, critical for quality control during manufacturing. Findings suggest that the investigated approach holds potential for enhancing leak detection technologies and adapt them for advanced manufactured parts.

36 MATERIALS SCIENCE↗