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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Proceedings of the 2024 Advancing Chemical Safety and Security Education Symposium at the 27th IUPAC International Conference on Chemistry Education

The inaugural Advancing Chemical Safety and Security Education symposium was held at the 27th IUPAC International Conference on Chemistry Education (ICCE2024). Speakers showcased innovative strategies for seamlessly integrating security concepts into established safety programs, addressing specific needs of diverse academic institutions, and evaluating the effectiveness of different pedagogical approaches. Here, this proceedings publication encapsulates insights from 11 oral presentations, 12 poster presentations, and panel discussions including key recommendations for future advancements in educating chemical safety and security education for academic and industry audiences.

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

Structural and Optical Response of Polymer-Stabilized Blue Phase Liquid Crystal Films to Volatile Organic Compounds

Engineering useful mechanical properties into stimuli-responsive soft materials without compromising their responsiveness is, in many cases, an unresolved challenge. For example, polymer networks formed within blue-phase liquid crystals (BPs) have been shown to form mechanically robust films, but the impact of polymer networks on the response of these soft materials to chemical stimuli has not been explored. In this work, we report on the response of polymer-stabilized BPs (PSBPs) to volatile organic compounds (VOCs, using toluene as a model compound) and compare the response to BPs without polymer stabilization and to polymerized nematic and cholesteric phases. We find that PSBPs generate an optical response to toluene vapor (change in reflection intensity under crossed polars) that is sixfold greater in sensitivity than the polymerized nematic or cholesteric phases and with a limit of detection (140 ± 10 ppm at 25 °C) that is relevant to the measurement of permissible exposure limits for humans. Additionally, when compared to BPs that have not been polymerized, PSBPs respond to a broader range of toluene vapor concentrations (5000 vs <1000 ppm) over a wider temperature interval (25–45 vs 45–53 °C). We place these experimental observations into the context of a simple thermodynamic model to explore how the PSBP response reflects the effect of toluene on competing contributions of double-twisted LC cylinders, disclinations, and polymer network to the free energy that controls the PSBP lattice spacing. Overall, we conclude that the mechanical and thermal stability of PSBPs, when combined with their optical responsiveness to toluene, make this class of self-supporting LCs a promising one as the basis of passive and compact (e.g., wearable) sensors for VOCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Polyacrylonitrile Composites of Ag–Al–Si–O Aerogels and Xerogels as Iodine and Iodide Sorbents

Mechanically robust engineered sorbents were constructed by embedding Ag-loaded aerogels or xerogels in a polyacrylonitrile (PAN) matrix at 30 or 50 mass% loadings of gel in PAN. Here, the process for making the base gels as well as the composite materials is described herein, a technology that is very flexible for making hybrid sorbents using various inorganic or organic active sorbents. The PAN-gel composite materials were evaluated for iodine uptake in the form of gaseous iodine [I 2(g) ] at room temperature and at 150°C as well as iodide (I – ) at room temperature from simulated liquid nuclear wastes. The composites show high I 2(g) uptake and high I – uptake (= 93 mass%) in simulated liquid secondary waste spiked with 5 mg L -1 I – . These results demonstrate the utility of such a composite form for iodine removal from contaminated gas and liquid streams.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Intercalation-Engineered Out-of-Plane Polarized van der Waals Ferromagnetic Superlattice with Room-Temperature Néel-Type Skyrmions

Superlattices (SLs) based on two-dimensional (2D) van der Waals (vdW) materials, abbreviated as 2D-SLs, have garnered significant attention due to their customizable properties. 2D-SLs can be engineered by mechanical stacking or chemical intercalation to achieve diverse forms of symmetry breaking, resulting in exotic phenomena like the quantum anomalous Hall effect and topological magnetism. Hitherto, broken symmetries in 2D-SLs have been widely produced within lateral planes or three dimensions. However, symmetry breaking along the vertical direction, specifically as an out-of-plane one-dimensional (1D) polarized superlattice, has not yet been achieved. Here, in this paper, we report a so far unseen out-of-plane 1D polarized vdW ferromagnetic superlattice achieved through an approach of two-step intercalation and de-embedding of chromium (Cr)-based 2D vdW magnets. The off-centering polarization of both intrinsic and intercalated Cr atoms in this (1 × 1 × 2) superstructure breaks the mirror symmetry vertically, yielding a Dzyaloshinskii–Moriya interaction (DMI). This results in high-density Néel-type magnetic skyrmions over a broad temperature range. Notably, sub-100 nm Néel-type skyrmions at room temperature (RT) can be achieved by tuning the Cr intercalation ratio, marking the first binary compound RT Néel-type skyrmionic vdW magnet. Our work expands the 2D-SL family with a class of out-of-plane 1D polarized ferromagnetic superlattice with tunable topological magnetism.

1D polarized superlattice↗
DOE OSTI2021

Soft elasticity optimises dissipation in 3D-printed liquid crystal elastomers

Soft-elasticity in monodomain liquid crystal elastomers (LCEs) is promising for impact-absorbing applications where strain energy is ideally absorbed at constant stress. Conventionally, compressive and impact studies on LCEs have not been performed given the notorious difficulty synthesizing sufficiently large monodomain devices. Here, we use direct-ink writing 3D printing to fabricate bulk (>cm 3 ) monodomain LCE devices and study their compressive soft-elasticity over 8 decades of strain rate. At quasi-static rates, the monodomain soft-elastic LCE dissipated 45% of strain energy while comparator materials dissipated less than 20%. At strain rates up to 3000 s –1 , our soft-elastic monodomain LCE consistently performed closest to an ideal-impact absorber. Drop testing reveals soft-elasticity as a likely mechanism for effectively reducing the severity of impacts – with soft elastic LCEs offering a Gadd Severity Index 40% lower than a comparable isotropic elastomer. Lastly, we demonstrate tailoring deformation and buckling behavior in monodomain LCEs via the printed director orientation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Controlling process instability for defect lean metal additive manufacturing

The process instabilities intrinsic to the localized laser-powder bed interaction cause the formation of various defects in laser powder bed fusion (LPBF) additive manufacturing process. Particularly, the stochastic formation of large spatters leads to unpredictable defects in the as-printed parts. Here we report the elimination of large spatters through controlling laser-powder bed interaction instabilities by using nanoparticles. The elimination of large spatters results in 3D printing of defect lean sample with good consistency and enhanced properties. We reveal that two mechanisms work synergistically to eliminate all types of large spatters: (1) nanoparticle-enabled control of molten pool fluctuation eliminates the liquid breakup induced large spatters; (2) nanoparticle-enabled control of the liquid droplet coalescence eliminates liquid droplet colliding induced large spatters. The nanoparticle-enabled simultaneous stabilization of molten pool fluctuation and prevention of liquid droplet coalescence discovered here provide a potential way to achieve defect lean metal additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The interplay between vapour, liquid, and solid phases in laser powder bed fusion

The capability of producing complex, high performance metal parts on demand has established laser powder bed fusion (LPBF) as a promising additive manufacturing technology, yet deeper understanding of the laser-material interaction is crucial to exploit the potential of the process. By simultaneous in-situ synchrotron x-ray and schlieren imaging, we probe directly the interconnected fluid dynamics of the vapour jet formed by the laser and the depression it produces in the melt pool. The combined imaging shows the formation of a stable plume over stable surface depressions, which becomes chaotic following transition to a full keyhole. We quantify process instability across several parameter sets by analysing keyhole and plume morphologies, and identify a previously unreported threshold of the energy input required for stable line scans. The effect of the powder layer and its impact on process stability is explored. These high-speed visualisations of the fluid mechanics governing LPBF enable us to identify unfavourable process dynamics associated with unwanted porosity, aiding the design of process windows at higher power and speed, and providing the potential for in-process monitoring of process stability.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ultra-strong tungsten refractory high-entropy alloy via stepwise controllable coherent nanoprecipitations

High-performance refractory alloys with ultrahigh strength and ductility are in demand for a wide range of critical applications, such as plasma-facing components. However, it remains challenging to increase the strength of these alloys without seriously compromising their tensile ductility. Here, we put forward a strategy to “defeat” this trade-off in tungsten refractory high-entropy alloys by stepwise controllable coherent nanoprecipitations (SCCPs). The coherent interfaces of SCCPs facilitate the dislocation transmission and relieve the stress concentrations that can lead to premature crack initiation. As a consequence, our alloy displays an ultrahigh strength of 2.15 GPa with a tensile ductility of 15% at ambient temperature, with a high yield strength of 1.05 GPa at 800 °C. The SCCPs design concept may afford a means to develop a wide range of ultrahigh-strength metallic materials by providing a pathway for alloy design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Anomalous temperature dependence of elastic limit in metallic glasses

Abstract Understanding the atomistic mechanisms of inelastic deformation in metallic glasses (MGs) remains challenging due to their amorphous structure, where local carriers of plasticity cannot be easily defined. Using molecular dynamics (MD) simulations, we analyzed the onset of inelastic deformation in CuZr MGs, specifically the temperature dependence of the elastic limit, in terms of localized shear transformation (ST) events. We find that although the ST events initiate at lower strain with increasing temperature, the elastic limit increases with temperature in certain temperature ranges. We explain this anomalous behavior through the framework of an energy-strain landscape (ESL) constructed from high-throughput strain-dependent energy barrier calculations for the ST events identified in the MD simulations. The ESL reveals that the anomalous behavior is caused by the transition of ST events from irreversible to reversible with increasing temperature. An analytical formulation is developed to predict this transition and the temperature dependence of the elastic limit.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A strong fracture-resistant high-entropy alloy with nano-bridged honeycomb microstructure intrinsically toughened by 3D-printing

Strengthening materials via conventional “top-down” processes generally involves restricting dislocation movement by precipitation or grain refinement, which invariably restricts the movement of dislocations away from, or towards, a crack tip, thereby severely compromising their fracture resistance. In the present study, a high-entropy alloy Al0.5CrCoFeNi is produced by the laser powder-bed fusion process, a “bottom-up” additive manufacturing process similar to how nature builds structures, with the microstructure resembling a nano-bridged honeycomb structure consisting of a face-centered cubic (fcc) matrix and an interwoven hexagonal net of an ordered body-centered cubic B2 phase. While the B2 phase, combined with high-dislocation density and solid-solution strengthening, provides strength to the material, the nano-bridges of dislocations connecting the fcc cells, i.e., the channels between the B2 phase on the cell boundaries, provide highways for dislocation movement away from the crack tip. Consequently, the nature-inspired microstructure imparts the material with an excellent combination of strength and toughness.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tetris-inspired detector with neural network for radiation mapping

Abstract Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Learning turbulent flows with generative models for super resolution and sparse flow reconstruction

Neural operators are promising surrogates for dynamical systems but when trained with standard L 2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that combining operator learning with generative modeling overcomes this limitation. We consider three practical turbulent-flow challenges where conventional neural operators fail: spatio-temporal super-resolution, forecasting, and sparse flow reconstruction. For Schlieren jet super-resolution, an adversarially trained neural operator (adv-NO) reduces the energy-spectrum error by 15 × while preserving sharp gradients at neural operator-like inference cost. For 3D homogeneous isotropic turbulence, adv-NO trained on only 160 timesteps from a single trajectory forecasts accurately for five eddy-turnover times and offers 114 × wall-clock speed-up at inference than the baseline diffusion-based forecasters, enabling near-real-time rollouts. For reconstructing cylinder wake flows from highly sparse Particle Tracking Velocimetry-like inputs, a conditional generative model infers full 3D velocity and pressure fields with correct phase alignment and statistics. These advances enable accurate reconstruction and forecasting at low compute cost, bringing near-real-time analysis and control within reach in experimental and computational fluid mechanics.

Fluid dynamics↗
DOE OSTI2023

Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI)

Abstract Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset. However, current state-of-the-art optimization algorithms are not designed with the capabilities to find solutions to these challenging multidimensional Needle-in-a-Haystack problems, resulting in slow convergence or pigeonholing into a local minimum. In this paper, we present a Zooming Memory-Based Initialization algorithm, entitled ZoMBI, that builds on conventional Bayesian optimization principles to quickly and efficiently optimize Needle-in-a-Haystack problems in both less time and fewer experiments. The ZoMBI algorithm demonstrates compute time speed-ups of 400× compared to traditional Bayesian optimization as well as efficiently discovering optima in under 100 experiments that are up to 3× more highly optimized than those discovered by similar methods.

36 MATERIALS SCIENCE↗
DOE OSTI2021

StressNet - Deep learning to predict stress with fracture propagation in brittle materials

Abstract Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and improving the fracture resistance and reliability of materials. Existing high-fidelity methods, such as the Finite-Discrete Element Model (FDEM), are limited by their high computational cost. Therefore, to reduce computational cost while preserving accuracy, a deep learning model, StressNet, is proposed to predict the entire sequence of maximum internal stress based on fracture propagation and the initial stress data. More specifically, the Temporal Independent Convolutional Neural Network (TI-CNN) is designed to capture the spatial features of fractures like fracture path and spall regions, and the Bidirectional Long Short-term Memory (Bi-LSTM) Network is adapted to capture the temporal features. By fusing these features, the evolution in time of the maximum internal stress can be accurately predicted. Moreover, an adaptive loss function is designed by dynamically integrating the Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE), to reflect the fluctuations in maximum internal stress. After training, the proposed model is able to compute accurate multi-step predictions of maximum internal stress in approximately 20 seconds, as compared to the FDEM run time of 4 h, with an average MAPE of 2% relative to test data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Demonstration of Super-X divertor exhaust control for transient heat load management in compact fusion reactors

Nuclear fusion could offer clean, abundant energy. However, managing the power exhausted from the core fusion plasma towards the reactor wall remains a major challenge. This is compounded in emerging compact reactor designs promising more cost-effective pathways towards commercial fusion energy. Alternative Divertor Configurations (ADCs) are a potential solution. In this work, we demonstrate exhaust control in ADCs, employing a novel method to diagnose the neutral gas buffer, which shields the target. Our work on the Mega Ampere Spherical Tokamak Upgrade shows that ADCs tackle key risks and uncertainties for fusion energy. Their highly reduced sensitivity to perturbations enables active exhaust control in otherwise unfeasible situations and facilitates an increased passive absorption of transients, which would otherwise damage the divertor. We observe a strong decoupling of each divertor from other reactor regions, enabling near-independent control of the divertors and core plasma. Our work showcases the real-world benefits of ADCs for effective heat load management in fusion power reactors.

Imaging techniques↗
DOE OSTI2026

Revealing key structures for reversible sulfur redox in amorphous polymeric sulfur

Amorphous polymeric sulfur cathodes, such as sulfurized polyacrylonitrile (SPAN), enable high-energy lithium-sulfur batteries without cobalt or nickel, leveraging abundant sulfur. However, the limited in situ understanding of their synthesis and electrochemistry has impeded targeted optimization. Here, in this study, we integrate operando high-energy total scattering with sulfur K-edge X-ray absorption spectroscopy to monitor SPAN's formation and cycling in real time. Our results show that S-C bond formation halts further fusion of cyclized polyacrylonitrile, fostering π-π stacking and a transition from long-chain to short-chain sulfur-critical for reversible sulfur redox. These features synergistically minimize polysulfide dissolution and charge-transfer resistance, enabling optimized SPAN to achieve high capacity retention over 1,000 cycles. Operando X-ray absorption spectroscopy reveals that residual protons drive thiol-thione tautomerism, with lithium replacement during the first discharge causing ~20% irreversible capacity loss. To enhance performance, minimizing -NH groups and expanding pyridine networks are key. These findings transform SPAN optimization from empirical tuning to mechanism‑guided engineering and point the way towards sulfur loadings and energy densities competitive with state‑of‑the‑art Li‑ion cathodes.

25 ENERGY STORAGE↗
DOE OSTI2020

Demonstration of cooling by the Muon Ionization Cooling Experiment

The use of accelerated beams of electrons, protons or ions has furthered the development of nearly every scientific discipline. However, high-energy muon beams of equivalent quality have not yet been delivered. Muon beams can be created through the decay of pions produced by the interaction of a proton beam with a target. Such ‘tertiary’ beams have much lower brightness than those created by accelerating electrons, protons or ions. High-brightness muon beams comparable to those produced by state-of-the-art electron, proton and ion accelerators could facilitate the study of lepton–antilepton collisions at extremely high energies and provide well characterized neutrino beams. Such muon beams could be realized using ionization cooling, which has been proposed to increase muon-beam brightness. Here we report the realization of ionization cooling, which was confirmed by the observation of an increased number of low-amplitude muons after passage of the muon beam through an absorber, as well as an increase in the corresponding phase-space density. The simulated performance of the ionization cooling system is consistent with the measured data, validating designs of the ionization cooling channel in which the cooling process is repeated to produce a substantial cooling effect. The results presented here are an important step towards achieving the muon-beam quality required to search for phenomena at energy scales beyond the reach of the Large Hadron Collider at a facility of equivalent or reduced footprint.

43 PARTICLE ACCELERATORS↗