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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗
DOE OSTI2026

A simple wire-coil resistive heater for high temperature radial x-ray diffraction in a diamond anvil cell

Diamond anvil cells are commonly used at synchrotron x-ray diffraction beamlines to study structural and thermoelastic properties of materials at high pressures. In a radial geometry, where the x-ray probe is oriented perpendicular to the axis of force, the deformation and strength of materials can be measured in situ. Because the anelastic and failure properties of materials depend strongly on temperature, many applications would benefit from the ability to measure high pressure radial diffraction in elevated and accurately controlled thermal environments. Previous work to introduce high temperature to radial diamond anvil cells has been largely limited to laser heating, with relatively scant efforts to resistively heat the sample. Here, we report a relatively straightforward adaptation of a simple wire coil heater, with in situ high-temperature radial diffraction performed on tungsten carbide up to 573 K at beamline 12.2.2 of the Advanced Light Source. In conclusion, the results demonstrate that the differential stress supported by WC decreases with increasing temperature: the differential stress on the basal (001) and pyramidal (101) planes decreased 6.6% and 5.5%, respectively, while the (100) plane only saw a 2.7% decrease, in agreement with previous studies.

Diamond anvil cells↗
DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗
DOE OSTI2025

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

Safta, Cosmin [Sandia National Laboratories (SNL-C↗
NASA NTRS1971

New techniques for the analysis of manual control systems

Studies are summarized on the application of advanced analytical and computational methods to the development of mathematical models of human controllers in multiaxis manual control systems. Specific accomplishments include the following: (1) The development of analytical and computer methods for the measurement of random parameters in linear models of human operators. (2) Discrete models of human operator behavior in a multiple display situation were developed. (3) Sensitivity techniques were developed which make possible the identification of unknown sampling intervals in linear systems. (4) The adaptive behavior of human operators following particular classes of vehicle failures was studied and a model structure proposed.

Bekey, G. A.↗
NASA NTRS1986

A system for conducting igneous petrology experiments under controlled redox conditions in reduced gravity

The Space Shuttle and the planned Space Station will permit experimentation under conditions of reduced gravitational acceleration offering experimental petrologists the opportunity to study crystal growth, element distribution, and phase chemistry. In particular the confounding effects of macro and micro scale buoyancy-induced convection and crystal settling or floatation can be greatly reduced over those observed in experiments in the terrestrial laboratory. Also, for experiments in which detailed replication of the environment is important, the access to reduced gravity will permit a more complete simulation of processes that may have occurred on asteroids or in free space. A technique that was developed to control, measure, and manipulate oxygen fugacites with small quantities of gas which are recirculated over the sample is described. This system should be adaptable to reduced gravity space experiments requiring redox control. Experiments done conventionally and those done using this technique yield identical results done in a 1-g field.

Williams, R. J.↗
NASA NTRS1955

High-Resolution Autoradiography

This investigation was made to adapt wet-process autoradiography to metallurgical samples to obtain high resolution of segregated radioactive elements in microstructures. Results are confined to development of the technique, which was perfected to a resolution of less than 10 microns. The radioactive samples included carbon-14 carburized iron and steel, nickel-63 electroplated samples, a powder product containing nickel-63, and tungsten-185 in N-155 alloy.

Towe, George C↗
NASA NTRS1995

Performance of a focused cavity aerosol spectrometer for measurements in the stratosphere of particle size in the 0.06-2.0-micrometer-diameter range

A focused cavity aerosol spectrometer aboard a NASA ER-2 high-altitude aircraft provided high-resolution measurements of the size of the stratospheric particles in the 0.06-2.0-micrometer-diameter range in flights following the eruption of Mount Pinatubo in 1991. Effects of anisokinetic sampling and evaporation in the sampling system were accounted for by means adapted and specifically developed for this instrument. Calibrations with monodisperse aerosol particles provided the instrument's response matrix, which upon inversion during data reduction yielded the particle size distributions. The resultant dataset is internally consistent and generally shows agreement to within a factor of 2 with comparable measurements simultaneously obtained by a condensation nuclei counter, a forward-scattering spectrometer probe, and aerosol particle impactors, as well as with nearby extinction profiles obtained by satellite measurements and with lidar measurements of backscatter.

Jonsson, H. H.↗
NASA NTRS2001

Electronic Thermometer Readings

NASA Stennis' adaptive predictive algorithm for electronic thermometers uses sample readings during the initial rise in temperature and applies an algorithm that accurately and rapidly predicts the steady state temperature. The final steady state temperature of an object can be calculated based on the second-order logarithm of the temperature signals acquired by the sensor and predetermined variables from the sensor characteristics. These variables are calculated during tests of the sensor. Once the variables are determined, relatively little data acquisition and data processing time by the algorithm is required to provide a near-accurate approximation of the final temperature. This reduces the delay in the steady state response time of a temperature sensor. This advanced algorithm can be implemented in existing software or hardware with an erasable programmable read-only memory (EPROM). The capability for easy integration eliminates the expense of developing a whole new system that offers the benefits provided by NASA Stennis' technology.

Source record↗
NASA NTRS2016

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The Glenn Research Center (GRC) team made a software-defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development on an STRS compliant platform to support future space communication systems for advanced exploration missions. Validated STRS compliant applications provided tested code with extensive documentation to potentially reduce risk, cost and efforts in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, the sample waveform, and wrapper development efforts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation SDRs for advance exploration missions.

space communications↗
DOE OSTI2026

Beyond Point Estimates: Benchmarking Uncertainty Quantification Methods on the AION-1 Astronomical Foundation Model

Foundation models for astronomical surveys offer powerful learned representations that can be transferred to downstream regression tasks such as galaxy property estimation. However, point predictions alone are insufficient for scientific inference; reliable uncertainty quantification (UQ) is essential. We compare seven UQ methods on galaxy property regression using frozen AION-1 foundation-model embeddings, predicting redshift, stellar mass, stellar-population age, gas-phase metallicity, and specific star-formation rate, from Legacy Survey photometry/imaging and DESI spectra, with PROVABGS-derived labels. Distribution-free conformal methods achieve marginal coverage within $\sim$1 pp of the nominal 90% across all properties, while non-conformal baselines (Deep Ensembles, MC~Dropout) fail to calibrate reliably. Among conformal approaches, Conformalized Quantile Regression (CQR) delivers the best coverage in the bin with the poorest model predictions. More importantly, only the Locally Valid and Discriminative (LVD) framework -- particularly when operating on AION-1 embeddings -- also provides finite-sample \emph{local validity}, producing intervals that adapt to each galaxy's local prediction difficulty rather than relying on marginal guarantees alone. These results establish conformal prediction, and LVD in particular, as the preferred UQ framework for uncertainty-aware inference on foundation-model embeddings in astrophysics.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗
NASA NTRS2002

Probabilistic #D data fusion for multiresolution surface generation

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

3D data fusion multiresolution surface generation ↗
NASA NTRS2019

Thermal design of the sample handling assembly in the sampling and caching subsystem on the Mars 2020 rover

The Mars 2020 Rover is scheduled to land on Mars on February 18, 2021. One of the primary mission objectives for the Mars 2020 Rover is to collect a set of Martian regolith samples for potential future return to Earth. Regolith and rock samples will be collected and placed into sample tubes using a coring drill, located at the end of a large Robotic Arm, on the outside of the rover. Filled sample tubes will be transferred from the outside of the Rover into the Adaptive Caching Assembly (ACA), located inside the Rover chassis, via the Bit Carousel. Once the filled sample tube is brought into the ACA, the Sample Handling Assembly (SHA) will transfer it to all of the internal processing stations of the ACA for volume assessment, sealing and finally drop-off on the Martian surface. The ACA is a volume within the rover chassis that is not temperature-controlled. Actuators inside the SHA and its End Effector (EE) must be warmed to above -55°C and -25°C, respectively, prior to use. This paper discusses the thermal design of the SHA that uses heaters and temperature sensors to warm up and maintain the temperature-sensitive arm components within temperature limits during operation. Thermal performance predictions for Mars surface operations are also presented.

Lee, Chern-Jiin↗
DOE OSTI2026

Predicting Adaptively Chosen Observables in Quantum Systems

Recent advances have demonstrated that 𝒪⁡(log 𝑀) measurements suffice to predict 𝑀 properties of arbitrarily large quantum many-body systems. However, these remarkable findings assume that the properties to be predicted are chosen independently of the data. This assumption can be violated in practice, where scientists adaptively select properties after looking at previous predictions. This work investigates the adaptive setting for three classes of observables: local, Pauli, and bounded-Frobenius-norm observables. We prove that Ω⁡(√𝑀) samples of an arbitrarily large unknown quantum state are necessary to predict expectation values of 𝑀 adaptively chosen local and Pauli observables, where the system size scales exponentially and polynomially in 𝑀, respectively. We also present computationally efficient algorithms that achieve this information-theoretic lower bound. In contrast, for bounded-Frobenius-norm observables, we devise an algorithm requiring only 𝒪⁡(log 𝑀) samples, independent of system size. These results highlight the potential pitfalls of adaptivity in analyzing data from quantum experiments and provide algorithmic tools to safeguard against erroneous predictions in quantum experiments.

Machine learning↗
NASA NTRS2009

Spatial Cognitive Performance During Adaptation to Conflicting Tilt-Translation Stimuli as a Sensorimotor Spaceflight Analog

The need to resolve new patterns of sensory feedback in altered gravitoinertial environments requires cognitive processes to develop appropriate reference frames for spatial orientation awareness. The purpose of this study was to examine deficits in spatial cognitive performance during adaptation to conflicting tilt-translation stimuli. Fourteen subjects were tilted within a lighted enclosure that simultaneously translated at one of 3 frequencies. Tilt and translation motion was synchronized to maintain the resultant gravitoinertial force aligned with the longitudinal body axis, resulting in a mismatch analogous to spaceflight in which the canals and vision signal tilt while the otoliths do not. Changes in performance on different spatial cognitive tasks were compared 1) without motion, 2) with tilt motion alone (pitch at 0.15, 0.3 and 0.6 Hz or roll at 0.3 Hz), and 3) with conflicting tilt-translation motion. The adaptation paradigm was continued for up to 30 min or until the onset of nausea. The order of the adaptation conditions were counter-balanced across 4 different test sessions. There was a significant effect of stimulus frequency on both motion sickness and spatial cognitive performance. Only 3 of 14 were able to complete the full 30 min protocol at 0.15 Hz, while 7 of 14 completed 0.3 Hz and 13 of 14 completed 0.6 Hz. There were no changes in simple visual-spatial cognitive tests, e.g., mental rotation or match-to-sample. There were significant deficits during 0.15 Hz adaptation in both accuracy and reaction time during a spatial reference task in which subjects are asked to identify a match of a 3D reoriented cube assemblage. Our results are consistent with antidotal reports of cognitive impairment that are common during sensorimotor adaptation with G-transitions. We conclude that these cognitive deficits stem from the ambiguity of spatial reference frames for central processing of inertial motion cues.

Kayanickupuram, A. J.↗
NASA NTRS1988

Design of a sample acquistion system for the Mars exobiological penetrator

The Mars Exobiological Penetrator will be imbedded into several locations on the Martian surface. It contains various scientific instruments, such as an Alpha-Particle Instrument (API), Differential Scanning Calorimeter (DSC), Evolved Gas Analyzer (EGA) and accelerometers. A sample is required for analysis in the API and DSC. To avoid impact contaminated material, this sample must be taken from soil greater than 2 cm away from the penetrator shell. This study examines the design of a dedicated sampling system including deployment, suspension, fore/after body coupling, sample gathering and placement. To prevent subsurface material from entering the penetrator sampling compartment during impact, a plug is placed in the exit hole of the wall. A U-lever device is used to hold this plug in the penetrator wall. The U-lever rotates upon initial motion of the core-grinder mechanism (CGM), releasing the plug. Research points to a combination of coring and grinding as a plausible solution to the problem of dry drilling. The CGM, driven by two compressed springs, will be deployed along a tracking system. A slowly varying load i.e., springs, is favored over a fixed displacement motion because of its adaptability to different material hardness. However, to accommodate sampling in a low density soil, two dash pots set a maximum transverse velocity. In addition, minimal power use is achieved by unidirectional motion of the CGM. The sample will be transported to the scientific instruments by means of a sample placement tray that is driven by a compressed spring to avoid unnecessary power usage. This paper also explores possible modifications for size, weight, and time as well as possible future studies.

Thomson, Ron↗
NASA NTRS1973

Vacuum probe surface sampler

A vacuum probe surface sampler is described for rapidly sampling relatively large surface areas which possess relatively light loading densities of micro-organism, drug particles or the like. A vacuum head with a hollow handle connected to a suitable vacuum source is frictionally attached to a cone assembly terminating in a flared tip adapted to be passed over the surface to be sampled. A fine mesh screen carried by the vacuum head provides support for a membrane filter which collects the microorganisms or other particles. The head assembly is easily removed from the cone assembly without contacting the cone assembly with human hands.

Zahlava, B. A.↗
NASA NTRS1994

Stable Direct Adaptive Periodic Control Using Only Plant Order Knowledge

The main contribution of this paper is to put stability requirements for convergence of direct adaptive periodic controllers on equal footing with requirements for indirect adaptive periodic control, as set forth by Lozano. The resulting stability condition is simply that the plant order is known a priori. No other prior plant knowledge is used (e.g., relative degree, high-frequency gain, etc.), and persistent excitation is not required. More importantly, no assumption or knowledge is required as to whether the plant is minimum or nonminimum phase. A numerical example is given to demonstrate the method, and some guidelines are given for improving the adaptive transient response.

sampling↗