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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A miniature multi-anvil apparatus using diamond as anvils—MDAC: Multi-axis diamond anvil cell

The diamond anvil cell (DAC) has been widely used in high-pressure research. Despite significant progress over the past five decades, the opposed anvil geometry in the DAC inevitably leads to a disk-shaped sample configuration at high pressure. This intrinsic limitation is largely responsible for the large pressure and temperature gradients in the DAC, which often compromise precise experiments and their characterizations. Here, we designed and fabricated a multi-axis diamond anvil cell (MDAC) by adopting the concept of a multi-anvil apparatus but using single crystal diamonds as the anvil material. Preliminary data show that the MDAC can generate extreme pressure conditions above 100 GPa. The advantages of the MDAC over a traditional opposed anvil DAC include thicker, voluminous samples, quasi-hydrostatic, or designed deviatoric stress conditions, and multidirectional access windows for optical applications and x-ray probes. In this article, we present the design and performance of a prototype MDAC, as well as the application prospects in high-pressure research.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗
DOE OSTI2025

Electrostatically Enhanced Buried Interface Binding of Self‐Assembled Monolayers for Efficient And Stable Inverted Perovskite Solar Cells

Inverted p‐i‐n structure perovskite solar cells (PSCs) have outperformed traditional n‐i‐p PSCs in recent years. A key advancement is the use of self‐assembled monolayers (SAMs) as hole transport layers. One class of widely used SAMs is carbazole‐based phosphonic acids. However, it is found that these SAMs lack strong binding with transparent conducting oxides (TCO) and perovskite. The weak binding strength results in suboptimal interfacial adhesion of the buried interface, which limits the device's stability. Here, interfacial binding is enhanced by increasing the dipole moment that creates a strong interfacial electric field that enhances electrostatic interactions at the TCO/perovskite interface, while incorporating tailored functional groups in SAMs to improve chemical anchoring to TCO and binding to perovskite. Specifically, the donor‐acceptor SAM molecule 4‐(7‐(4‐(bis(4‐methoxyphenyl)amino)‐2,5‐difluorophenyl)benzo[c][1,2,5]thiadiazol‐4‐yl)benzoic acid (PAFTB) is employed, which features an enhanced dipole moment along with electron‐donating and electron‐withdrawing functional groups to optimize interfacial interactions. Compared to extensively used [2‐(9H‐carbazol‐9‐yl)ethyl]phosphonic acid (2PACz), PAFTB enhances total interfacial adhesion by 2.8 times, thereby improving the thermal stability of the layer. Using this approach, PSCs are demonstrated with a certified quasi‐steady‐state power conversion efficiency of 24.9% and maintain 80% of the initial efficiency after 900 h of maximum power point tracking at 85 °C.

Interfacial adhesion↗
DOE OSTI2021

Direct comparison of gamma, electron beam and X-ray irradiation doses on characteristics of low-density polyethylene, polypropylene homopolymer, polyolefin elastomer and chlorobutyl rubber medical device polymers

There is a growing need for increased efficiency in the sterilization of single use medical devices and other products that contain polymer components. Gamma radiation is widely used for devices suited for radiation sterilization; however, safety, throughput and cobalt-60 source availability are challenging the prospect of relying on gamma radiation to meet the anticipated needs of the industry. Use of electron beam (e-beam) and X-rays as alternatives to gamma for radiation sterilization have been hampered in part by a concern that these modalities may adversely affect polymer integrity and performance relative to the gamma method, for which the industry has had much more experience. To address this concern, the effects of sterilization-relevant doses of ebeam, X-ray and gamma radiation were directly compared using common medical device polymers found in two prototypical commercial devices currently sterilized using cobalt-60 gamma irradiation. The Becton, Dickinson and Company (BD) Vacutainer™ Plus tube contains low-density polyethylene and chlorobutyl rubber components, while the BD Vacutainer™ Push Button Blood Collection Set contains polypropylene homopolymer and polyolefin elastomer components. Injection-molded samples prepared from the polymers used in these products were exposed to target doses of 15, 35, 50 and 80 kGy using gamma, e-beam and X-ray radiation. Changes in coloration, tensile properties and hardness were measured for each condition, and the effects of e-beam and X-ray irradiation compared with the effects of gamma irradiation on these properties. Both e-beam and X-ray appear as viable alternatives to gamma irradiation for sterilization of the polymers tested.

sterilization, gamma, X-ray, electron beam, radiat↗
DOE OSTI2022

Stable and unstable supersonic stagnation of an axisymmetric rotating magnetized plasma

The Naval Research Laboratory ‘Mag Noh problem’, described in this paper, is a self-similar magnetized implosion flow, which contains a fast magnetohydrodynamic (MHD) outward propagating shock of constant velocity. We generalize the classic Noh ( OSTI Tech. Rep. 577058, 1983) problem to include azimuthal and axial magnetic fields as well as rotation. Our family of ideal MHD solutions is five parametric, each solution having its own self-similarity index, gas gamma, magnetization, the ratio of axial to the azimuthal field and rotation. While the classic Noh problem must have a supersonic implosion velocity to create a shock, our solutions have an interesting three-parametric special case with zero initial velocity in which magnetic tension, instead of implosion flow, creates the shock at $t=0+$ . Our self-similar solutions are indeed realized when we solve the initial value MHD problem with the finite volume MHD code Athena. We numerically investigated the stability of these solutions and found both stable and unstable regions in parameter space. Stable solutions can be used to test the accuracy of numerical codes. Unstable solutions have also been widely used to test how codes reproduce linear growth, transition to turbulence and the practically important effects of mixing. Now we offer a family of unstable solutions featuring all three elements relevant to magnetically driven implosions: convergent flow, magnetic field and a shock wave.

Mechanics↗
DOE OSTI2022

Impacts of Suppressing Excessive Light Rain on Aerosol Radiative Effects and Health Risks

Global climate models (GCMs) have been used widely to study radiative forcing and health risks of aerosols. A recent study using two GCMs found that light rain plays a dominant role in controlling aerosol loading. However, “too much light rain and too little heavy rain” is a longstanding bias in GCMs. It is unclear how much light rain affects aerosol-cloud-radiation interactions and health risks from air pollution. Here, in this work, we show that, with the correction of the rainfall intensity spectrum in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 by introducing a stochastic deep convection scheme, the reduced frequency of light rain (1–20 mm d -1 ) results in changes of aerosol direct radiative effects (DRE) of up to -0.5 ± 0.03 W/m 2 and aerosol cloud radiative effects (CRE) of up to -0.9 ± 0.03 W/m 2 . The total (CRE + DRE) radiative effects of light rain-mediated aerosol changes exceed the present-day anthropogenic forcing of aerosols relative to preindustrial levels from the Coupled Model Intercomparison Project (CMIP5&6) models. However, the correction of the rainfall intensity spectrum has little effect on anthropogenic aerosol forcing (defined as the radiative perturbation due to changes in aerosol concentrations between the industrial era and preindustrial levels). Due to increased exposure to fine particulates (PM 2.5 ), the estimated global total premature mortality is much higher than previously estimated, by 300,000 ± 60,000 deaths per year, and is more severe in populous regions such as India and China. The findings in this study highlight the need to understand uncertainties in radiative effects and health risks of aerosols due to simulation biases of precipitation in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

BLINK enables ultrafast tandem mass spectrometry cosine similarity scoring

Metabolomics has a long history of using cosine similarity to match experimental tandem mass spectra to databases for compound identification. Here we introduce the Blur-and-Link (BLINK) approach for scoring cosine similarity. By bypassing fragment alignment and simultaneously scoring all pairs of spectra using sparse matrix operations, BLINK is over 3000 times faster than MatchMS, a widely used loop-based alignment and scoring implementation. Using a similarity cutoff of 0.7, BLINK and MatchMS had practically equivalent identification agreement, and greater than 99% of their scores and matching ion counts were identical. This performance improvement can enable calculations to be performed that would typically be limited by time and available computational resources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Tetraphenylpentalenide organolanthanide complexes

Lanthanide sandwiches of the D 2h 1,3,4,6-tetraphenylpentalenide are reported. The Ph 4 Pn dianion shows promise for new electron-rich f-block organometallics using the metal's d z 2 orbital, in contrast to the more widely used cyclooctatetraenyl dianion.

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

Reactor System Facility Modification to Detect Compromised Human Machine Interfaces

This study focuses on a multi-layered Industrial Control System (ICS)/Operational Technology (OT) security architecture to aid in the discovery and mitigation of compromised Human Machine Interface (HMI)/Instrumentation & Control (I&C) based systems for modifying a prototypical reactor condition test facility called the Flowing Autoclave System (FAS) at Idaho National Laboratory (INL). This is achieved through a three-layered combination of network security solutions, hash-based algorithms, and blockchain technologies. Hash algorithms are mathematical functions used to generate a predetermined set of fixed-length values. They are widely used in computer security to verify the integrity of system information and data, both on a local network and the wider internet. Even small amounts of unauthorized system modification will cause the hash algorithm to output a set of characters that deviate significantly from its original value. Assisting secure hash functions, blockchain technology is a secure and distributed technology used to provide an immutable set of records replicated on all devices within a decentralized network. Blockchain offers a cost-effective solution to detect system compromise by providing a traceable breadcrumb trail of all network activity and data modification happening on a system. If both are used in conjunction with network monitoring tools, the integration of this three-pronged approach can become an asset in detecting suspected system compromises before any real damage can occur.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Analytical and numerical modeling of optical second harmonic generation in anisotropic crystals using #SHAARP package

Electric-dipole optical second harmonic generation (SHG) is a second-order nonlinear process that is widely used as a sensitive probe to detect broken inversion symmetry and local polar order. Analytical modeling of the SHG polarimetry of a nonlinear optical material is essential to extract its point group symmetry and the absolute nonlinear susceptibilities. Current literature on SHG analysis involves numerous approximations and a wide range of (in)accuracies. We have developed an open-source package called the Second Harmonic Analysis of Anisotropic Rotational Polarimetry (#SHAARP.si) which derives analytical and numerical solutions of reflection SHG polarimetry from a single interface (.si) for bulk homogeneous crystals with arbitrary symmetry group, arbitrary crystal orientation, complex and anisotropic linear dielectric tensor with frequency dispersion, a general SHG tensor and arbitrary light polarization. #SHAARP.si enables accurate modeling of polarimetry measurements in reflection geometry from highly absorbing crystals or wedge-shaped transparent crystals. The package is extendable to multiple interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of Molecular Diffusion at Block Copolymer Thin Films Using Maximum Entropy Method-Based Fluorescence Correlation Spectroscopy and Single Molecule Tracking

Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated nitrogen atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. Furthermore, these results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Materials for the biorefinery: high bio-content, shape memory Kraft lignin-derived non-isocyanate polyurethane foams using a non-toxic protocol

Polyurethanes are among the top six polymers produced in the world and are widely used in the automotive, furniture, construction and appliance industry for their light weight, impact resistance, and insulating properties. However, the use of hazardous diisocyanates used in polyurethane formulations has led many to search for more sustainable alternatives. The lignin component of biomass has been targeted to replace the often toxic and petroleum-derived precursors to polymer synthesis in support of the biorefinery concept where natural materials are used as the feedstock for commodity plastics. The use of lignin is often hampered due to its low reactivity, heterogeneity and the necessity of employing extensive purification and/or functionalization measures to ensure materials are of comparable quality. In this report, a unique method is presented for the synthesis and processing of a non-toxic, non-isocyanate polyurethane foam utilizing unmodified Kraft lignin and a biobased curing agent. Here, raw Kraft lignin is functionalized with green organic carbonates and a non-toxic approach is taken to solubilize the precursors with a curing agent from renewable fatty acids enabling rapid gel-times. For the first time, a NIPU foam from lignin is synthesized while the structure–property relationship of different reaction mixtures is studied demonstrating shape memory capacity and 100% biobased carbon content.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗
DOE OSTI2021

Thermodynamically consistent semi-compressible fluids: a variational perspective

This paper presents (Lagrangian) variational formulations for single and multicomponent semi-compressible fluids with both reversible (entropy-conserving) and irreversible (entropy-generating) processes. Semi-compressible fluids are useful in describing low-Mach dynamics, since they are soundproof. These models find wide use in many areas of fluid dynamics, including both geophysical and astrophysical fluid dynamics. Specifically, the Boussinesq, anelastic and pseudoincompressible equations are developed through a unified treatment valid for arbitrary Riemannian manifolds, thermodynamic potentials and geopotentials. By design, these formulations obey the 1st and 2nd laws of thermodynamics, ensuring their thermodynamic consistency. This general approach extends and unifies existing work, and helps clarify the thermodynamics of semi-compressible fluids. To further this goal, evolution equations are presented for a wide range of thermodynamic variables: entropy density s, specific entropy η, buoyancy b, temperature T, potential temperature θ and a generic entropic variable χ; along with a general definition of buoyancy valid for all three semicompressible models and arbitrary geopotentials. Finally, the elliptic equation for the pressure perturbation (the Lagrange multiplier that enforces semi-compressibility) is developed for all three equation sets in the case of reversible dynamics, and for the Boussinesq/anelastic equations in the case of irreversible dynamics; and some discussion is given of the difficulty in formulating it for the pseudoincompressible equations with irreversible dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Hydration‐Induced β‐Sheet Crosslinking of α‐Helical‐Rich Spider Prey‐Wrapping Silk

Abstract Due to its moderate strength (≈700 MPa) and impressive extensibility before breaking (≈60–80%), orb‐weaving spider aciniform (AC) prey‐wrapping silks are actually the toughest of the spider silks but are remarkably understudied. The previous results indicate that native AC silk fibers are an α‐helix rich coiled‐coil/β‐sheet hybrid nanofiber, and that conversion of disordered or helical domains to β‐sheet aggregates is surprisingly minimal and overall β‐sheet content is low (≈15%). In this work, it is demonstrated through scanning electron microscopy that native AC silk fibers undergo matted cross‐linking upon exposure to moisture that increases silk stiffness. The unique molecular mechanism of water‐induced cross‐linking is revealed with solid‐state NMR (SSNMR) methods; water‐induced morphological changes are correlated with an increase in AC silk protein β‐sheet content, and additionally a minor unfolding of coiled‐coil regions is observed. Continued and increased β‐sheet cross‐linking is observed upon application of mechanical shear. The size of these β‐sheet domains to be 4–6 nm using Wide‐Line Separation SSNMR is determined. The observation that merely water treatment can be used to convert a protein‐based material from a flexible/extensible α‐helix‐rich fiber to a rigid crossed‐linked β‐sheet mat is a novel observation that should provide new avenues in bioinspired materials design.

Stengel, Dillan↗
DOE OSTI2026

Imputation of urban environmental sensor data using gated attention bidirectional long short-term memory (GA-BiLSTM): methods, performance, and implications

Urban environmental monitoring networks frequently encounter significant data gaps due to sensor malfunctions, environmental disturbances, and communication failures. Reliable approaches to address these gaps are essential for ensuring the continuity and quality of environmental data streams. In this study, we developed a gated attention bidirectional long short-term memory (GA-BiLSTM) model to impute missing data in a dense urban monitoring network. Using observations from the CROCUS network in Chicago, we evaluated GA-BiLSTM against widely used approaches (XGBoost and K-nearest neighbors) under scenarios of both short-term intermittent gaps and prolonged outages. GA-BiLSTM consistently outperformed comparative methods, particularly during extended outages of up to ten days, demonstrating its ability to capture spatiotemporal dependencies across sensor nodes. Beyond performance metrics, feature importance and spatial network analyses highlighted the unexpected but critical predictive role of peripheral rural nodes, underlining their strategic value for maintaining robust urban monitoring systems. These results emphasize that advanced imputation methods can substantially improve the reliability of environmental monitoring networks and support more resilient data infrastructures for urban sustainability.

Data imputation↗
DOE OSTI2025

Multi-objective surrogate-assisted calibration of CPFEM models using macroscopic response and in situ EBSD measurements of grain reorientation trajectories

Crystal plasticity finite element method (CPFEM) models are widely used to simulate the deformation behaviour of polycrystalline materials, but their calibration is often limited by their high computational cost and the non-convexity of the optimisation landscape. Here, this study develops a multi-objective surrogate-assisted calibration workflow that couples a multi-objective genetic algorithm (MOGA) with an adaptively trained deep neural network (DNN) surrogate model to efficiently identify CPFEM parameters from experimental data. The workflow is demonstrated on three crystal plasticity (CP) formulations of increasing complexity — Voce hardening (VH), two-coefficient latent hardening (LH2), and six-coefficient latent hardening (LH6) — using in situ electron backscatter diffraction (EBSD) measurements of Alloy 617 under uniaxial tensile loading. The CPFEM models are calibrated against the experimentally observed stress–strain response and reorientation trajectories of eight grains, then validated against eight additional trajectories and overall texture evolution. Across the CP formulations, the macroscopic response was reproduced reliably, while differences emerged in the robustness and accuracy of the grain-scale predictions. Including grain reorientation trajectories in the multi-objective calibration improved texture evolution predictions and filtered out physically inconsistent parameter sets that can arise from calibrating against only the stress–strain data. The workflow also demonstrates good transferability of calibrated parameters from a low- to a high-fidelity microstructural model. These results provide practical guidance for integrating in situ microstructural data into CPFEM through efficient, repeatable, and physically meaningful multi-objective calibration.

Crystal plasticity finite element method↗