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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The cosine-sine decomposition with different-orbitals-for-different-spins determinants

We report the spin decomposition of a spin-contaminated different-orbitals-for-different-spins (DODS) wave function is formulated in terms of the Krylov space of the $\hat{S}^2$ ||operator. The number of determinants that contribute to the various projected spin eigenfunctions vertical | $\psi ; S, M \rangle$ depends on the sparsity of the orbital overlap matrix X between the α and β spatial orbitals. The cosine-sine decomposition (CSD) procedure may be applied to this overlap matrix, and the resulting redundant orbital transformations may be applied to the α and β spatial orbitals. This produces a sparse X' matrix in the transformed basis in which each row or column has either one or two nonzero elements. This sparse X' matrix simplifies the spin-decomposition procedure in three ways:1) it reduces the number of contributing determinants within the Krylov basis functions and within the projected spin functions, 2) it reduces the effective orbital dimension through elimination of the frozen core and frozen virtual orbitals, and 3) it simplifies the spin-decomposition procedure in both the original and transformed bases by limiting the Krylov space dimension. These simplifications all reduce the computational effort for the spin-decomposition process. This procedure is implemented within a string-based DODS determinant formulation and applied to spin projection of unrestricted Hartree-Fock determinants.

unrestricted Hartree-Fock↗
DOE OSTI2024

Protocols for x-ray transient grating pump/optical probe experiments at x-ray free electron lasers

Abstract Transient grating spectroscopy is a specialized application of the four-wave-mixing methodology and constitutes a versatile technique for investigating the dynamics of vibrational, magnetic and electronic degrees of freedom of matter in a background-free fashion. Recent developments in free-electron laser sources have enabled the extension of this technique into the extreme ultraviolet range. Ongoing efforts to expand transient grating spectroscopy into the x-ray regime promise numerous advantages: (1) substantial penetration depths that allow for probing bulk material properties, (2) element specificity via specific core-excited states, and (3) short wavelengths that allow for excitation gratings with higher momentum transfer and improved spatial resolution. In this study, we comprehensively outline the procedures for conducting x-ray transient grating pump/optical probe experiment. The process encompasses the design and alignment of the experimental setup, as well as the subsequent steps involved in data acquisition and analysis. This paper is intended as a comprehensive guide for researchers interested in implementing x-ray transient grating spectroscopy, providing valuable insights into the intricacies of the experimental workflow required for this novel technique. Furthermore, we discuss the potential for extending this methodology to an x-ray pump/x-ray probe scheme, envisioning a future direction that holds promise for enhancing the capabilities and scope of x-ray transient grating spectroscopy, opening new opportunities for studying ultrafast processes with unprecedented temporal and spatial resolutions.

Optics↗
DOE OSTI2022

Entangled two-plasmon generation in carbon nanotubes and graphene-coated wires

Here, we investigate the two-plasmon spontaneous decay of a quantum emitter near single-walled carbon nanotubes (SWCNTs) and graphene-coated wires (GCWs). We demonstrate efficient, enhanced generation of two-plasmon entangled states in SWCNTs due to the strong coupling between tunable guided plasmons and the quantum emitter. We predict two-plasmon emission rates more than twelve orders of magnitude higher than in free space, with average lifetimes of a few dozen nanoseconds. Given their low dimensionality, these systems could be more efficient for generating and detecting entangled plasmons in comparison to extended graphene. Indeed, we achieve a tunable spectrum of emission in GCWs, where sharp resonances occur precisely at the plasmons' minimum excitation frequencies. We show that by changing the material properties of the GCW's dielectric core, one could tailor the dominant modes and frequencies of the emitted entangled plasmons while keeping the decay rate ten orders of magnitude higher than in free space. By unveiling the unique properties of two-plasmon spontaneous emission processes in the presence of low-dimensional carbon-based nanomaterials, our findings set the basis for a novel material platform with applications to on-chip quantum information technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Constraining properties of asymmetric dark matter candidates from gravitational-wave observations

The accumulation of certain types of dark matter particles in neutron star cores due to accretion over long timescales can lead to the formation of a mini black hole. In this scenario, the neutron star is destabilized and implodes to form a black hole without significantly increasing its mass. When this process occurs in neutron stars in coalescing binaries, one or both stars might be converted to a black hole before they merge. Thus, in the mass range of ~1–2M ⊙ , the Universe might contain three distinct populations of compact binaries: one containing only neutron stars, the second population of only black holes, and a third, mixed population consisting of a neutron star and a black hole. However, it is unlikely to have a mixed population as the various timescales allow for both neutron stars to remain or collapse within a short timescale. In this paper, we explore the capability of future gravitational-wave detector networks, including upgrades of Advanced LIGO and Virgo, and new facilities such as the Cosmic Explorer and Einstein Telescope (XG network), to discriminate between different populations by measuring the effective tidal deformability of the binary, which is zero for binary black holes but nonzero for binary neutron stars. Furthermore, we show that observing the relative abundances of the different populations can be used to infer the timescale for neutron stars to implode into black holes, and in turn, provide constraints on the particle nature of dark matter. Furthermore, the XG network will infer the implosion timescale to within an accuracy of 0.01 Gyr at 90% credible interval and determine the dark matter mass and interaction cross section to within a factor of 2 GeV and 10 cm –2 , respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

DIMPLES: Distributed Influence Maximization for Pandemic pLanning on Exascale Systems

We study exascale parallel algorithms for the selection of intervention or monitoring strategies in massive realistic socio-technical networks through scalable Influence Maximization (InfMax) algorithms. We employ novel techniques to enable efficient scaling on up to 8k nodes of OLCF Frontier, with 65k AMD GPUs and 458k AMD CPU cores. Current state-of-the-art InfMax tools are limited to networks with only a few million actors (vertices) and a few hundred million interactions (edges). By overcoming these limitations, we show that our approach is capable of processing a realistic social contact network of the United States with 285 million nodes and about 8 billion edges. This two orders-of-magnitude improvement over the previous state-of-the-art is obtained by leveraging algorithmic advancements for the InfMax problem and designing several problem-specific approaches to overlap communication with computation, improve GPU efficiency, and lower the application’s memory requirements. We evaluate strong scaling for computing 10k most influential seeds using up to 8k nodes of an exascale system, and weak scaling from 128 to 8k system nodes for seed sets ranging from 625 to 40k seeds. We achieve the fastest-known runtime of 25 minutes while performing 48 million diffusion simulations totaling 2.31 petabytes to identify 40k influential seeds using 8k nodes, and take 5.75 minutes to identify 10k seeds while using 4k nodes.

Minutoli, Marco [Pacific Northwest National Labora↗
DOE OSTI2020

Sample Identifiers and Metadata Reporting Format for Environmental Systems Science

The ESS-DIVE sample identifiers and metadata reporting format primarily follows the System for Earth Sample Registration (SESAR) Global Sample Number (IGSN) guide and template, with modifications to address Environmental Systems Science (ESS) sample needs and practicalities (IGSN-ESS). IGSNs are associated with standardized metadata to characterize a variety of different sample types (e.g. object type, material) and describe sample collection details (e.g. latitude, longitude, environmental context, date, collection method). Globally unique sample identifiers, particularly IGSNs, facilitate sample discovery, tracking, and reuse; they are especially useful when sample data is shared with collaborators, sent to different laboratories or user facilities for analyses, or distributed in different data files, datasets, and/or publications. To develop recommendations for multidisciplinary ecosystem and environmental sciences, we first conducted research on related sample standards and templates. We provide a comparison of existing sample reporting conventions, which includes mapping metadata elements across existing standards and Environment Ontology (ENVO) terms for sample object types and environmental materials. We worked with eight U.S. Department of Energy (DOE) funded projects, including those from Terrestrial Ecosystem Science and Subsurface Biogeochemical Research Scientific Focus Areas. Project scientists tested the process of registering samples for IGSNs and associated metadata in workflows for multidisciplinary ecosystem sciences. We provide modified IGSN metadata guidelines to account for needs of a variety of related biological and environmental samples. While generally following the IGSN core descriptive metadata schema, we provide recommendations for extending sample type terms, and connecting to related templates geared towards biodiversity (Darwin Core) and genomic (Minimum Information about any Sequence, MIxS) samples and specimens. ESS-DIVE recommends registering samples for IGSNs through SESAR, and we include instructions for registration using the IGSN-ESS guidelines. Our resulting sample reporting guidelines, template (IGSN-ESS), and identifier approach can be used by any researcher with sample data for ecosystem sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML)

Although the interest in the use of artificial intelligence (AI) and machine learning (ML) in nuclear energy is increasing rapidly, at present their implementation is limited. This rapid increase in interest is not surprising considering that implementing AI and ML technology would allow for continuous monitoring, facilitate the implementation of predictive maintenance with optimized staffing plans, enable automation and autonomy opportunities that could drastically reduce fixed operation and maintenance costs, and provide training for operations and maintenance. Other industries are using AI for construction, and in the nuclear arena AI could provide great benefit in decommissioning activities. The ability of AI and ML to operate in real time vastly increases their potential impact. Before AI can be used in design, operations, or as a regulatory tool, the specifics on the regulations applicable to the use of AI for nuclear power applications need to be established. The difficulty is that the specific use cases will dictate the applicability of regulations. For example, even within the application domain associated with operations, the regulations might vary if the AI is used to create a virtual reference for plant operations or is used for training, optimization of maintenance intervals, prioritization of maintenance activities, etc. Different still is if the AI is to be used for design or setting technical specifications, which will introduce additional requirements. US Nuclear Regulatory Commission (NRC) licensing reviews are based on an applicant’s design meeting its performance assessment based on (1) safety goals and objectives, (2) deterministic and/or probabilistic analysis of accident scenarios, and (3) quantitative assessment of design alternatives against the safety goals and objectives using accepted engineering tools, methodologies, and performance criteria. The current regulatory framework does not explicitly address AI or autonomous control. However, as implementing AI technology will require the use of a digital platform, it must meet the requirements of an instrumentation and control (I&C) system. The regulatory requirements for AI, which will be incorporated into the I&C system, will be very dependent on how it is used (i.e., its functionality, safety classification, etc.). The licensing process is primarily risk-based with the identification of components and systems as nonsafety, important to safety, or safety related. A risk-informed approach allows further gradation of components and systems based on risk metrics such as core damage frequency or large early release fractions. Thus, the use cases and the risk categorization of impacted systems and components will determine the regulatory requirements. Regardless of how AI is used it presents new opportunities for risk-informing operating, maintenance, and regulatory decisions. Trustworthiness, transparency, and the ability to validate and verify the results will be paramount in showing that the systems and plant still meet their performance requirements. This report describes the results of research to identify regulatory implications of AI technologies and their uses. Specifically, this report reviews current regulatory guidance relevant to the application of AI for design (including design changes or new designs including advanced reactors), construction, operations, training, maintenance, research, testing, and as a regulatory tool. AI can be automated at different levels from purely informative purposes to autonomous controls. The focus of this review included determination of constraints on the application of AI technology, identification of any regulatory gaps or uncertainties, and clarification of anticipated technical basis information likely to be important for regulatory acceptance of these technologies. Currently, any use of AI at nuclear power plants is focused on nonsafety-related applications. The NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than create new regulations to address the use of AI and ML. This approach seems to be the best to encourage AI development without adding regulatory uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The Role of Hydrophobic Nodes in the Dynamics of Class A β-Lactamases

Class A β-lactamases are known for being able to rapidly gain broad spectrum catalytic efficiency against most β-lactamase inhibitor combinations as a result of elusively minor point mutations. The evolution in class A β-lactamases occurs through optimisation of their dynamic phenotypes at different timescales. At long-timescales, certain conformations are more catalytically permissive than others while at the short timescales, fine-grained optimisation of free energy barriers can improve efficiency in ligand processing by the active site. Free energy barriers, which define all coordinated movements, depend on the flexibility of the secondary structural elements. The most highly conserved residues in class A β-lactamases are hydrophobic nodes that stabilize the core. To assess how the stable hydrophobic core is linked to the structural dynamics of the active site, we carried out adaptively sampled molecular dynamics (MD) simulations in four representative class A β-lactamases (KPC-2, SME-1, TEM-1, and SHV-1). Using Markov State Models (MSM) and unsupervised deep learning, we show that the dynamics of the hydrophobic nodes is used as a metastable relay of kinetic information within the core and is coupled with the catalytically permissive conformation of the active site environment. Finally, our results collectively demonstrate that the class A enzymes described here, share several important dynamic similarities and the hydrophobic nodes comprise of an informative set of dynamic variables in representative class A β-lactamases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

An Additively Manufactured Fe-3Si Stator for a High-Performance Electrical Motor

Additive manufacturing (AM) has the potential to produce novel high-performance electrical machines, enabling the direct printing of complex shapes and the simultaneous processing of multiple feedstocks in a single build. We examined the properties and functional performance of Fe-3 wt.% Si materials that were printed via selective laser melting, machined down to thin laminates, and stacked to form a stator core of a prototype brushless permanent-magnet electrical motor. Big Area Additive Manufacturing of Nd2Fe14B (NdFeB)–polyphenylene sulfide (PPS) bonded magnets was performed, with them then being magnetized and used for the rotor. The magnetic, mechanical, and electrical properties of the as-printed and various heat-treated thin laminates and the back electromotive force (EMF) of the electrical motors at different rotational speeds were measured. The thin laminates exhibit a maximum relative permeability of 7494 at an applied field of 0.8 Oe and a core loss of about 20 W/lb at 60 Hz with the maximum induction of 15 kg. In addition to the demonstration of AM printing, motor assembly, and complete characterization of printed Fe-3 wt.% Si, this report highlights the areas of improvement needed in printing technologies to achieve AM built electrical motors and the need for isotropic microstructure refinements to make the laminates appropriate for high-mechanical-strength and low-loss rotational electrical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Upgrades of the ATLAS Zero Degree Calorimeter System for Run 3 at the Large Hadron Collider

Experimental studies of ultra-relativistic heavy ion collisions at the Large Hadron Collider (LHC) depend crucially on Zero Degree Calorimeters (ZDCs) that measure neutrons produced at near-beam rapidity in nucleus-nucleus collisions. In hadronic nuclear collisions these neutrons are mainly spectator neutrons, those that do not scatter from opposing nucleons during the collision. As a result, the ZDCs provide a vital probe of heavy ion collision geometry. The ZDCs are also essential in the study of ultra-peripheral collisions that are initiated by photons associated with the electric fields of one or both nuclei. Coherent photon emission typically leaves the photon emitter intact, making the observation of no ZDC signal, on one or both sides, a tag of such processes. The ATLAS ZDCs, built prior to Run 1 were substantially upgraded for LHC Run 3. The primary upgrades included replacement of the quartz Cherenkov radiator with $\text{H}_2$-doped fused silica rods; installation of fast air-core signal cables between the ZDC and the ATLAS USA15 cavern; new LED-based calibration system; and new electronics implemented for readout and fully-digital triggering. The ZDCs were also augmented with new "Reaction Plane Detectors" (RPDs) designed to measure the transverse centroid of multi-neutron showers to allow event-by-event reconstruction of the directed-flow plane in nuclear collisions. The Run~3 ZDC detectors, including the RPDs, are described in detail with emphasis on aspects that are new for Run~3.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

The Simulation EnviRonment for Geomorphology, Hydrodynamics, and Ecohydrology in Integrated form (SERGHEI) is a multi-dimensional, multi-domain, and multi-physics model framework for environmental and landscape simulation, designed with an outlook towards Earth system modelling. At the core of SERGHEI's innovation is its performance-portable high-performance parallel-computing (HPC) implementation, built from scratch on the Kokkos portability layer, allowing SERGHEI to be deployed, in a performance-portable fashion, in graphics processing unit (GPU)-based heterogeneous systems. In this work, we explore combinations of MPI and Kokkos using OpenMP and CUDA backends. In this contribution, we introduce the SERGHEI model framework and present with detail its first operational module for solving shallow-water equations (SERGHEI-SWE) and its HPC implementation. This module is designed to be applicable to hydrological and environmental problems including flooding and runoff generation, with an outlook towards Earth system modelling. Its applicability is demonstrated by testing several well-known benchmarks and large-scale problems, for which SERGHEI-SWE achieves excellent results for the different types of shallow-water problems. Finally, SERGHEI-SWE scalability and performance portability is demonstrated and evaluated on several TOP500 HPC systems, with very good scaling in the range of over 20 000 CPUs and up to 256 state-of-the art GPUs.

58 GEOSCIENCES↗
DOE OSTI2020

thornado-transport: Anderson- and GPU-accelerated nonlinear solvers for neutrino-matter coupling

Algorithms for neutrino-matter coupling in core-collapse supernovae (CCSNe) are investigated in the context of a spectral two-moment model, which is discretized in space with the discontinuous Galerkin method, integrated in time with implicit-explicit (IMEX) methods, and implemented in the toolkit for high-order neutrino-radiation hydrodynamics (thornado). The model considers electron neutrinos and antineutrinos and tabulated opacities from Bruenn (1985), which includes neutrino-electron scattering and pair processes. The nonlinear system arising from implicit time discretization of the equations governing neutrino-matter coupling is iterated to convergence using Anderson-accelerated fixed-point methods, which avoid formation of Jacobians and inversion of dense linear systems. Numerical experiments show that, for a given tolerance, a nested iteration scheme which aims to reduce opacity evaluations can lower the computational cost. Our initial port to GPUs, using both OpenMP and OpenACC, shows an overall speedup of up to ~ 100× when compared to results using a single CPU core. These results indicate that the algorithms implemented in thornado are well-suited to GPU acceleration.

Laiu, Paul↗
DOE OSTI2025

Understanding Pore Filling Processes and Adsorption/Desorption Hysteresis in Nanoporous Metal–Organic Frameworks: Insights from Grand Canonical Monte Carlo Simulations and Free Energy Calculations

Grand canonical Monte Carlo (GCMC) simulations were used to investigate pore filling and hysteresis in nanoporous metal-organic frameworks (MOFs). Adsorption and desorption isotherms were calculated for argon at 87 K in 1866 MOFs from the CoRE MOF database and for short n-alkanes in selected MOFs, keeping the adsorbent structure rigid. Analysis of the molecular configurations showed two different mechanisms and origins of hysteresis: one involving a transition of the adsorbate arrangement in the pores similar to a gas-to-liquid transition associated with a large change in the loading and one more similar to a liquid-to-solid transition associated with a relatively small change in the loading. Our GCMC simulations in MOFs with diverse pore topologies indicate exceptions to an empirical relationship for the minimum diameter of a cylindical pore required for hysteresis as a function of the adsorbate diameter and reduced temperature. The simulations reveal some structures where isotherms exhibit two steps in the adsorption branch and only one step in the desorption branch. Hysteresis loops with a different number of adsorption and desorption steps are not common. Here, to better understand why hysteresis is observed in the GCMC simulations, the concept of the transition probability for observing a step in the adsorption isotherm at a given pressure in a GCMC simulation is introduced. We used two different methods to calculate the transition probabilities and find that these yield comparable results. Furthermore, the transition probability provides a measure for the length of GCMC simulations to yield reliable results.

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

Role of microtearing mode in DIII-D and future high- β p core plasmas

This paper provides modeling evidence for a new variant of microturbulence instability that regulates the electron thermal fluxes in the transport barrier region of DIII-D "high β p " discharges. This scenario is being investigated as a possible scenario for future steady-state reactors, and thus it is essential to understand the physics processes which govern its performance in order to confidently extrapolate to future devices. Additional analysis examining the extrapolation of this scenario to ITER shows that while the new microtearing mode identified here is unlikely to be unstable in that regime (due to increased temperatures and reduced collisionality), the large shift in magnetic axis (Shafranov shift) that arises in these plasmas may still favor stabilization of common ballooning instabilities which peak on the low field side, but destabilize electrostatic slab modes on the high field side.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Sequential Infiltration Synthesis of Cadmium Sulfide Discrete Atom Clusters

Exposure of soft material templates to alternating volatile chemical precursors can produce inorganic deposition within the permeable template (e.g. a polymer thin film) in a process akin to atomic layer deposition (ALD). While such sequential infiltration synthesis (SIS) processes have now been demonstrated for many metal oxides, we report an SIS process for a transition metal sulfide – CdS. Gas phase dimethyl cadmium and hydrogen sulfide precursors infiltrated into poly(4-vinylpyridine) thin films result in the 3D-nucleation of clusters consistent with a cubane-type Cd 4 S 4 core that are variably terminated with methyl, thiol and hydroxy capping ligands. First principles models and simulation of few-atom Cd-based clusters are consistent with electronic and vibrational spectroscopy and grazing-incidence total X-ray scattering measurements of 3D-cluster-arrays synthesized at 80 °C. The direct synthesis of few-atom transition metal sulfide clusters within polymer thin films will provide a versatile new route to precision architectures for light-absorbing materials including solar energy harvesting and conversion applications.

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

Chemical characteristics of iron meteorite parent bodies

The projected relative abundances of the highly siderophile elements (HSE; Re, Os, Ir, Ru, Pt, and Pd) for bulk parent bodies of 10 magmatic iron meteorite groups/grouplet (IC, IIAB, IIC, IID, IIF, IIIAB, IIIF, IVA, IVB, and South Byron Trio) are broadly similar and show no resolvable differences between noncarbonaceous (NC) and carbonaceous (CC) genetic heritage. The processes driving genetic isotopic heterogeneity in the early Solar System, therefore, evidently did not leave discernable chemical fingerprints with respect to HSE relative abundances on the bulk planetesimal scale. By contrast, the absolute abundances of HSE projected for parent body cores, which reflect core size, are more variable and, on average, higher in CC bodies compared to NC bodies. Overall, bulk core chemical compositions, as well as core size, are linked to the distribution of Fe within a parent body, which is controlled by its oxidation state. The CC parent bodies are constrained to have formed under heterogeneous oxidizing conditions which were, on average, more oxidizing than those of the NC environment.

Hilton, Connor D.↗
DOE OSTI2021

Molecular dynamics simulations of radiation cascade evolution near cellular dislocation structures in additively manufactured stainless steels

The dislocation dense cellular structures observed in additively manufactured (AM) stainless steels can allow these materials to have enhanced strength and ductility compared to conventionally manufactured materials. Effective design of radiation resistant materials often necessitates creating microstructures containing of a high density of dislocations that act as sinks for radiation induced defects. This work uses molecular dynamics simulations to study the impact of pre-existing defects on radiation damage in stainless steel 316L fabricated by the laser powder bed fusion process. The evolution of synthetically generated dislocations in a crystal system in response to multiple radiation collision cascades suggest that dislocation dense regions reduce the probability of surviving point defects forming clusters. This finding seems to result from the dislocation cores’ ability to absorb point defects, thereby limiting the formation of clusters during the recombination phase. However, after successive cascades, the ability of the dislocation entanglement to prevent defect formation is diminished and defect cluster formation trends to an equilibrium. Accordingly, it is hypothesized that in an experimental setting the dislocation cells will initially act as neutral sinks for point defects, potentially delaying the onset of radiation damage effects; but, these structures will be degraded due to radiation-enhanced diffusion and lose their effectiveness at doses above 1.5–2 displacements per atom. Nevertheless, the ability to produce complex and feature-specific microstructures suggests promise for the design of radiation tolerant materials using AM methods.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hermetically sealed porous-wall hollow microspheres enabled by monolithic glass coatings: Potential for thermal insulation applications

Thermal insulation materials are crucial to improve the energy performance of buildings and industrial applications. We report an approach to create hermetically vacuum-sealed silica-based hollow microspheres that can lower the thermal conductivity of closed-cell insulation materials. The wall structure of these hollow microspheres includes a reticulated network of pores or channels that extend through the thickness of the wall. When a thin layer of glass material is applied to the wall exterior, followed by a vacuum-assisted thermal treatment process, the coated microsphere surfaces display a highly dense conformal coverage and near-complete elimination of surface porosity. The sealing efficiency of these microspheres is verified by trapping argon within their cavities as well as through evacuating their hollow cores. Notably, incorporating the evacuated microspheres into a polymer matrix resulted in ~27% enhancement in its thermal insulation performance and no notable loss of performance was observed following three months of exposure to ambient conditions. Thus, we believe that the present study offers a commercially viable strategy that opens the door to applications of such inorganic hollow particles in areas ranging from vacuum-based thermal insulation systems to catalysis, separation technologies, and medical fields.

36 MATERIALS SCIENCE↗