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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SMR safety through HTTF modeling and benchmark efforts for code validation for gas-cooled reactor applications

Accurate modeling and simulation tools for thermal-hydraulics calculations are a key element needed to design and license new advanced reactors including Small Modular Reactors (SMR) and Microreactors. Uncertainties in modeling and simulation can have significant safety and economic implications. The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled prismatic-block nuclear reactors. High-quality measurement data is available from the HTTF that is suitable for a thermal-hydraulics code validation benchmark for gas-cooled reactor simulations. Here, this paper summarizes individual HTTF modeling efforts to date for tool validation at Idaho National Laboratory (INL), Argonne National Laboratory (ANL), Oregon State University (OSU) and Canadian Nuclear Laboratories (CNL) using system thermal-hydraulics codes, Computational Fluid Dynamics (CFD) codes and system-CFD code couplings. Also, the paper introduces the ongoing OECD Nuclear Energy Agency (NEA) High Temperature Gas Reactor Thermal-Hydraulics (HTGR T/H) benchmark that allows for better comparisons of results between different international modeling teams. The benchmark provides well defined computational problems that include code-to-code comparisons and comparisons to measured data. These problems provide an avenue for quantifying accuracy and identifying sources of uncertainty in thermal-hydraulics calculations, including in measured thermophysical properties, as part of validation for gas-cooled reactor simulation tools.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Dissolved Oxygen Redox as the Source of Hydrogen Peroxide and Hydroxyl Radical in Sonicated Emulsive Water Microdroplets

Sonicated emulsive water microdroplets (SEWMs) accelerate and enable a variety of catalyst-free chemical transformations. However, significant unanswered questions remain regarding the chemical intermediates they form and their possible redox origin. In this study, we identified dissolved O 2 as the primary originator of reactive oxygen species (ROS) such as OH• and H 2 O 2. We uncovered the role of dissolved O 2 redox by using a combination of microelectrochemical methods to detect H 2 O 2 , isotopic methods to identify the source of H 2 O 2 , and a combination of electron spin resonance and the DMPO spin trap to detect radicals such as OH•. Notably, we found that H 2 O 2 production is correlated with O 2 content via a reduction pathway enabled by a sufficiently large reducing power that can additionally generate H 2 and even perform Pb electroless deposition on Au and Cu metal substrates. Building on our findings, continuous O 2 bubbling of SEWMs showed accumulation of H 2 O 2 up to ∼88 mM in the aqueous phase within 1 h of sonication, demonstrating the scale-up promise of this method. Distinct to sonochemistry of a single phase, this study advances our understanding of the confluence of redox and chemical reaction mechanisms within SEWMs as a biphasic system. This insight paves the way for improving their reaction kinetics, yield, and selectivity, positioning these attractive redox microreactors as alternatives to traditional electrolyzers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Low-Temperature Non-Oxidative Coupling of Methane on Atomically Dispersed Titanium–Aluminum–Boron Nanopowder

Nonoxidative coupling of methane represents a long-standing challenge in heterogeneous catalysis, as it requires activation of the carbon–hydrogen (C–H) bond, controlled carbon–carbon (C–C) bond formation, and effective hydrogen management without relying on oxidants. Here, we report a low-temperature C–H activation and nonoxidative C–C coupling of methane over atomically dispersed titanium–aluminum–boron nanopowder (Ti–Al–B NP) utilizing a catalytic microreactor coupled to synchrotron single-photon photoionization reflectron time-of-flight mass spectrometry. The soft-ionization, in situ probing method detects the nascent reaction products and radical intermediates under operando conditions, including methyl radical, C2 hydrocarbons, and molecular hydrogen. Methane activation is initiated at 800 K, approximately 700 K below the gas-phase decomposition threshold, leading predominantly to ethylene formation with selectivity reaching up to 78% among the C–C coupled products. Electronic structure calculations on model Ti–Al–B clusters elucidate a cooperative catalytic mechanism in which titanium enables methane adsorption and C–H activation, boron acts as a reversible hydrogen reservoir, and aluminum stabilizes methylene intermediates, thereby facilitating selective C–C coupling and dehydrogenation. These findings establish a distinct catalyst architecture for nonoxidative methane coupling based on earth abundant elements alternative to expensive platinum and other noble metal-containing conventional catalysts and provide molecular-level design principles for controlling dehydrogenation and subsequent C–C bond formation in challenging light alkane conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗
DOE OSTI2025

Natural nanoparticle complexes at water-water interfaces

Aqueous two-phase systems (ATPSs) with multifunctional attributes have significant promise as biomimetic materials, but current approaches do not harness their full potential. Here, we show that ATPSs can be stabilized to form microcapsules by the interfacial assembly of chitin nanofibers (ChNF) and rod-like cellulose nanocrystals (CNC). The high structural stability of the ChNF/CNC complexes integrates permeability and transport across the membrane at the liquid/liquid interface. Driven by density and osmotic stress gradients, the microcapsules show switchable motility, including cyclic meniscus-climbing and subsurface transport. These observations demonstrate a self-regulating system with potential for cargo transfer, cell biomimicry, as well as ATPSs-based microreactors and microrobots.

Bioinspired materials↗
DOE OSTI2025

Unconventional low temperature decomposition of a saturated hydrocarbon over atomically-dispersed titanium-aluminum-boron catalyst

Sonochemically-synthesized atomically-dispersed titanium-aluminum-boron nanopowder (TiAlB NP) exhibits a remarkable low-temperature catalytic activation of aliphatic C-H bonds at 750 K followed by C-C bond activation thus emerging as a potent low-cost alternative to expensive platinum group metals. Here, the model saturated hydrocarbon, exo-tetrahydrodicyclopentadiene (C10H16), undergoes catalytic decomposition on TiAlB NPs in a chemical microreactor to produce 1,3-cyclopentadiene (c-C5H6), cyclopentene (c-C5H8), and molecular hydrogen (H2) as detected in situ via isomer-selective, single-photon ionization time-of-flight mass spectrometry. Extensive electronic structure theory calculations on model clusters of the catalyst decode a unique synergy among the atomic constituents of the catalyst and chemical bonding in this stepwise, retro Diels Alder reaction: Ti, although insensitive to C-H activation in its metallic state, initiates the catalysis via chemisorption of the hydrocarbon, adjacent B centers readily abstract hydrogen atoms and store them during the catalytic cycle, while Al stabilizes the catalyst structure yet providing space for critical docking sites for the departing hydrocarbons.

Biswas, Souvick↗
DOE OSTI2025

A MOOSE-Based Model for Fission Product Transport and Source Term Estimation for High-Temperature Gas-Cooled Reactors

Thanks to fuel elements containing tristructural isotropic (TRISO) particles combined with a low core power density and passive feedback mechanisms leading to modest temperature rises in the event of accidental events, high-temperature gas-cooled reactors (HTGRs) offer a high degree of reliability in terms of fission product retention. While the anticipated source term for HTGRs is expected to be very low, it is important to provide a quantitative estimate of radiological releases during nominal and accidental conditions. Here, we propose a computationally efficient mechanistic source term methodology relying on the Multiphysics Object Oriented Simulation Environment (MOOSE) for tracking fission product transport from TRISO particles up to the coolant pressure boundary, as well as modeling the transport and potential deposition of these nuclides inside the reactor coolant loop. The proposed computational scheme is applied to estimate source term inventories for a representative 10-MW(thermal) prismatic high-temperature microreactor and is qualitatively compared against known release fractions. In addition to providing an alternate analysis tool, this MOOSE model can help reactor designers quantify the influence of key design parameters relevant for studies of radiological dose consequences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

RELAP5-3D Capabilities for High-Temperature Gas-Cooled Reactor Analysis

RELAP5-3D is the premier systems thermal-hydraulic code in the world. The code has been used significantly for high-temperature gas-cooled reactor (HTGR) analyses over the last 10 years, but there has not been a comprehensive summary of RELAP5-3D capabilities and methods for HTGR modeling. In this paper, we provide a guide for how novice users can build models for prismatic HTGRs. This guide includes best practices for developing heat structures and setting up radiation and conduction heat transfer. We also provide a summary of relevant validation studies. These studies are divided into three categories: separate effects tests, integral effects tests, and nuclear reactor studies. We present a comprehensive review of RELAP5-3D HTGR applications for reactor modeling over the last 10 years. These applications include work for the Modular High-Temperature Gas-Cooled Reactor benchmark, design activities for a prismatic HTGR as part of the U.S. Department of Energy’s Advanced Demonstration and Test Reactor Options Study, and studies performed to design gas-cooled microreactors. Following the comprehensive literature review, we present a gap analysis highlighting capabilities of RELAP5-3D that are available and missing for a complete analysis of HTGR thermal hydraulics. We also discuss the limitations of existing code capabilities and potential improvements that could improve analyses. Current research efforts have yet to fully validate RELAP5-3D for a prismatic HTGR analysis; however, some of this is attributable to confounding factors in the available experimental data as opposed to code capabilities. In conclusion, this paper presents the most comprehensive review to date on RELAP5-3D capabilities, limitations, and applications for HTGR analysis.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Optimizing Hydride Stability in U-ZrH x Nuclear Fuel: The “Goldilocks Radius”

Nuclear-powered microreactors show great promise for opening new nuclear energy markets due to the flexibility offered by their rapid/streamlined in-factory fabrication, transportability, and self-regulating nature. The economic benefits of any commercialized nuclear reactor, however, rely on the system’s ability to produce large amounts of heat and efficiently convert that heat into electrical power reliably for long periods of time. Uranium-zirconium hydride (U-ZrH x ) is currently being considered for compact reactor designs because it is a well-known nuclear fuel system that is self-moderating, but this fuel, which has historically been used for research reactors, has not been optimized for commercial power production. Here, this paper analyzes the hydride stability of standard 304 stainless steel–clad U-ZrH x fuel under commercially relevant conditions. Fuel element design parameters, including physical dimensions, as-fabricated hydrogen content, burnup, peak fuel temperature, temperature gradient, operational fuel cycle duration, and volumetric heat generation rate, are discussed with a focus on hydrogen distribution and phase stability within the fuel element. Hydride stability declines more rapidly as the coolant temperature, burnup, and fuel cycle duration increase. Using a fuel-cladding gap material with heat transfer properties superior to air, such as helium or sodium, is essential to prolonging fuel hydride stability. The fuel’s physical dimensions are also important. At very small fuel diameters, the H/Zr ratio in the fuel meat decreases too rapidly due to the hydrogen content’s dependence on fuel meat volume. Conversely, the fuel meat temperature and temperature gradient exacerbate hydrogen loss at very large fuel diameters. We find that the most important parameter to consider when optimizing the hydride stability of U-ZrH x fuel is the relationship between the fuel meat radius and the power density in the fuel. A simple equation is empirically determined that relates the “Goldilocks radius,” that is, the fuel radius for which the H/Zr ratio is most stable, to the power density in the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Welch Method and Bootstrapping Applied to Subcritical Gamma Noise

We measured the prompt neutron decay constant 𝛼 of the CROCUS zero-power reactor at the Swiss Federal Institute of Technology Lausanne using cross-power spectral density (CPSD) analysis of gamma-gamma correlations from two trans-stilbene organic scintillators positioned near the reactor core. We measured critical and subcritical states, with water levels ranging from 960 mm (critical) to 800 mm (𝜌=−1.4 $ subcritical). Our analysis used the Welch method, dividing signal segments for fast Fourier transform (FFT) frequency analysis and applying bootstrapping uncertainty quantification that uses Welch-defined segments. Results demonstrated a clear increase in the measured 𝛼 as reactor reactivity decreased, distinguishing critical from subcritical conditions. At the 960-mm critical level, 𝛼 was estimated at 155.9 ± 0.7 s −1 , and for the 800-mm subcritical level, 𝛼 increased significantly to 367.3 ± 6.9 s –1 . A linear regression of subcritical states yielded a critical estimate of 154.0 ± 3.1 s –1 , aligning with the static 𝛼 estimate at critical. The bootstrapping method produced normally distributed 𝛼 estimates, confirming data consistency. The gamma CPSD 𝛼 estimates clearly distinguish reactor states and improve monitoring of zero-power reactors. The future deployment of modular and microreactors as potential candidates for noise analysis is demonstrated in CROCUS, particularly zero-power mock-ups of new designs. The improvement of noise analysis in the subcritical domain from this work will support experimental data for reactor deployment and procedure.

CROCUS↗
DOE OSTI2025

SCALE Shielding Calculations for Advanced Reactor Accident Scenarios

The study results presented in this paper demonstrate the capabilities of the SCALE computer code for non–light water reactor (non-LWR) radiation source term and shielding calculations in support of the U.S. Nuclear Regulatory Commission non-LWR fuel cycle demonstration project. Representative non-LWR types, including the sodium-cooled fast reactor (SFR), the molten salt reactor (MSR), and the heat pipe microreactor (HPMR), were analyzed to evaluate dose rates associated with postulated accident scenarios (SFR and MSR), reactor operation (MSR and HPMR), and fuel self-protecting characteristics (HPMR). New features were implemented in SCALE depletion codes to better simulate MSR operation.

MSR↗
DOE OSTI2026

Evaluation of Radiation Transport Through a Nuclear-Grade Sandwich Composite

The development and deployment of microreactors are often synonymous with their transportability; however, designing a shield which is appropriate for both transportation and operations is challenging. A recent approach is the use of composite style shield which combines the reactor pressure vessel and biological shielding into a single unit to enhance the shields effectiveness without degrading the structural properties. To assess the viability of a nuclear grade sandwich composite (NGSC), and understanding of how radiation transports through the shield needs to be understood to select the appropriate materials. This work examines a two-layered NGSC of varying thicknesses with two primary shielding materials (tungsten-tetraboride cermet and boron carbide). To assess the NGSC, quantities of interest including neutron attenuation, photon attenuation, energy deposition, displacements per atom, helium generation, and dose are examined. Altogether, it is found that a combination of both tungsten-tetraboride and boron carbide are necessary to act as an appropriate shield, where the order in which these materials are place in the composite are important to their effectiveness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos↗
DOE OSTI2025

Gas-phase synthesis of anthracene and phenanthrene via radical-radical reaction induced ring expansions

Unraveling reaction mechanisms of aromatic and resonance-stabilized radicals is critical to understanding molecular mass growth processes to polycyclic aromatic hydrocarbons (PAHs) and carbonaceous nanoparticles in distinct astrophysical environments (molecular clouds, circumstellar envelopes) and combustion systems. Using photoelectron photoion coincidence spectroscopy (PEPICO), we explored the gas-phase reaction of the methyl radical (CH 3 • ) with the aromatic and resonance-stabilized fluorenyl radical (C 13 H 9 • ) under high-temperature conditions in a chemical microreactor. Anthracene and phenanthrene were detected isomer-selectively using photoionization efficiency (PIE) curves and mass-selected threshold photoelectron (ms-TPE) spectra. While phenanthrene is produced through a radical-radical recombination of the carbon-centered radicals, anthracene may plausibly be formed through an unconventional radical addition to a low spin-density fluorenyl carbon. These pathways result in five-membered ring expansion—a critical mechanism crucial to PAH mass growth converting bent PAHs into planar nanostructures.

Goettl, Shane J. [University of Hawai‘i at Mānoa, ↗
DOE OSTI2025

Comparison of nested geometry treatments within GPU-based Monte Carlo neutron transport simulations of fission reactors

Monte Carlo (MC) neutron transport provides detailed estimates of radiological quantities within fission reactors. This involves tracking individual neutrons through a computational geometry. CPU-based MC codes use multiple polymorphic tracker types with different tracking algorithms to exploit the repeated configurations of reactors, but virtual function calls have high overhead on the GPU. The Shift MC code was modified to support GPU-based tracking with three strategies: dynamic polymorphism with virtual functions, static polymorphism, and a single tracker type with tree-based acceleration. On the Frontier supercomputer these methods achieve 77.8%, 91.2%, and 83.4%, respectively, of the tracking rate obtained using a specialized tracker optimized for rectilinear-grid-based reactors. This indicates that all three methods are suitable for typical reactor problems in which tracking does not dominate runtime. The flexibility of the single tracker method is highlighted with a hexagonal-grid microreactor problem, performed without hexagonal-grid-specific tracking routines, providing a 2.19× speedup over CPU execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Hydrogen transport in yttrium hydride under asymmetric heat

Metal hydrides are a promising moderator material for high temperature fission reactors. Yttrium hydride can be loaded to a high hydrogen density with relatively high hydrogen stability at temperatures up to 800°C. This makes yttrium hydride a potential moderator material for microreactors as foreseen in the fission surface power program. However, during the operation of such advanced reactors temperature gradients are expected which can change the local hydrogen density in the moderator. Hydrogen diffusion in metals is driven by a concentration gradient (Fick’s law) and thermal diffusion (Soret diffusion). Thermal diffusion is the transport of hydrogen, or other species, due to a temperature gradient. For example, hydrogen might migrate from the hot side of a sample to the cold side of a sample. Measuring Fickian diffusion is achieved through various permeation or absorption experiments, however measuring thermal diffusion is challenging and has rarely been performed. The Hydrogen Experimental Apparatus for Thermal Diffusion (HEATD) experiment is designed to induce thermal diffusion in samples and quench those samples so that the hydrogen distribution can be analyzed using hot vacuum extraction (HVE). One side of the sample was heated to a high temperature e.g., 800°C, while the other side of the sample is at a lower temperature. The sample was held under the applied temperature gradient for a given time until the anticipated hydrogen diffusion has occurred. The actual time depends depend on the sample composition and hydrogen concentration. The results from HVE showed that thermal diffusion took place in the specimen and the Soret coefficient was calculated.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A versatile approach to stabilize liquid-liquid interfaces using surfactant self-assembly

Stabilizing liquid–liquid interfaces, whether between miscible or immiscible liquids, is crucial for a wide range of applications, including energy storage, microreactors, and biomimetic structures. In this study, a versatile approach for stabilizing the water-oil interface is presented using the morphological transitions that occur during the self-assembly of anionic, cationic, and nonionic surfactants mixed with fatty acid oils. The morphological transitions underlying this approach are characterized and extensively studied through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. Dissipative particle dynamics (DPD) as a simulation tool is adopted to investigate these morphological transitions both in the equilibrium ternary system as well as in the dynamic condition of the water-oil interface. Such a versatile strategy holds promise for enhancing applications such as liquid-in-liquid 3D printing. Moreover, it has the potential to revolutionize a wide range of fields where stabilizing liquid–liquid interfaces not only offers unprecedented opportunities for fine-tuning nanostructural morphologies but also imparts interesting practical features to the resulting liquid shapes. These features include perfusion capabilities, self-healing, and porosity, which could have significant implications for various industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗