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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Tailoring Thermal and Mechanical Performance Through Multimaterial Laser Powder Directed Energy Deposition of Copper and 17-4PH Stainless Steel

This study investigates the additive manufacturing (AM) processing, microstructural evolution, and resulting mechanical and thermal properties of multimaterial components combining 17-4PH stainless steel and pure copper (Cu) fabricated via laser powder directed energy deposition (LP-DED). Conventional tooling steels exhibit limited thermal conductivity, significantly constraining production throughput in high-volume processes. Incorporating Cu, with its superior thermal conductivity, could significantly enhance tool performance, though Cu and steel present metallurgical incompatibilities when processed via AM. A systematic investigation was conducted across compositions ranging from 0 to 100 wt% Cu, revealing critical thresholds influencing solidification behavior, defect formation, microstructure, hardness, and thermal transport. Optical microscopy, electron backscatter diffraction (EBSD), hardness testing, and thermal conductivity measurements provided comprehensive process–structure–property correlations. Severe hot cracking occurred at low-Cu contents (6–25 wt%), aligning generally well with crack susceptibility modeling, with an unexpected discrepancy at 25 wt%. Porosity remained low (≥99% dense) throughout the compositional spectrum. EBSD analysis revealed a transformation from columnar martensitic structures at low-Cu contents to equiaxed FCC Cu-dominated structures at higher Cu concentrations, highlighting the complex microstructural transitions driven by Cu-induced changes in solidification and phase stability. Hardness decreased from 330 HV (pure 17-4PH) to 62 HV (pure Cu), consistent with microstructural changes. Concurrently, thermal conductivity improved substantially from 13.5 W/m K to 367.9 W/m K, emphasizing Cu’s dominant role in thermal transport. The findings highlight the feasibility of leveraging compositional gradients between 17-4PH and Cu to achieve tailored tooling with optimized thermal and mechanical performance.

17-4PH↗
DOE OSTI2025

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Thermomechanical properties of stereolithographic 3D-printed zinc oxide nanocomposites

Stereolithography (SLA) is a highly versatile additive manufacturing technique that utilizes various ink formulations to fabricate 3D-printed nanocomposite structures with desired properties. Zinc oxide (ZnO) is a promising candidate due to its excellent mechanical and thermal stability, and compatibility with various polymeric matrices. Here, in this work, varying ink formulations containing ZnO nanoparticles, along with employing appropriate post-printing curing parameters to fabricate SLA 3D-printed acrylate-based nanocomposites with improved mechanical and thermal properties, were reported. This study can significantly contribute to expanding its potential use in practical applications such as biomedical and structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Completion of Transport Property Measurements on Multiple Actinide Fluoride Mixtures

One of the missions of the US Department of Energy’s Office of Nuclear Energy (DOE-NE) Molten Salt Reactor (MSR) Campaign under the Advanced Reactor Technology program has been to experimentally measure thermophysical properties of MSR-relevent salt systems, with the intent of supporting the development of the Molten Salt Thermal Properties Database (MSTDB). This database is jointly funded by the DOE-NE Nuclear Energy Advanced Modeling and Simulation Program and the MSR Campaign. Multiple DOE national laboratories, including Oak Ridge National Laboratory (ORNL), have been conducting measurements of thermophysical properties to support MSTDB development and provide MSR developers with access to new data that has been measured using modern methodologies and more advanced sample characterization techniques. These data may either fill gaps in the database or provide updated higher quality data to replace legacy data. Researchers at ORNL have recognized significant gaps in the transport property data of actinide-bearing fluoride salt systems of MSR industry interest. Moreover, for the data present in MSTDB in this category, the uncertainty margins are generally high, leading to questionability in our current understanding of the thermophysical characterization of actinide fluoride mixtures. As such, the focus of this study has been to generate new transport property data of actinide fluoride mixtures that are of immediate interest to MSR developers. Specifically, the mixtures NaF-UF 4 (78 - 22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been studied—NaF-UF 4 for thermal conductivity and viscosity and NaF-KF-UF 4 for viscosity. Thermal conductivity measurements have been conducted with a variable gap apparatus, whereas viscosity has been measured with a rolling ball viscometer. Methodological and calibration details are provided for both measurement processes, along with measurement system updates that have enabled easier manufacturing of components and fewer challenges associated with conducting the measurements themselves. The resultant data collected for NaF-UF 4 (78–22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been compared with relevant mixture data within the thermophysical arm of the MSTDB (MSTDB-TP).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Material extrusion additive manufacturing of wood pulp-reinforced epoxy composites

Direct ink writing (DIW) is an extrusion-based form of 3D-printing that has gained popularity over the last decade. DIW uses thixotropic fluid extrusion to form a particular shape. In order to form stable structures, the rheology of the paste is important to allow for extrusion from the syringe, stability of the growing print, and prevention of unwanted seeping flow during jog moves. In this work, we use wood pulp as a bio-based filler that can provide shear thinning properties to the ink, which produces a stable ink for DIW processing. Additionally, the filler imparts improved mechanical and thermal performance compared to neat resin. The wood pulp provided the shear thinning behavior necessary for DIW printing, and pulp loadings greater than 6 wt%, provided sufficient yield stress so that the composite could self-support during printing. Nanoclay was utilized to further improve ink rheology and appearance to enable larger scale printing. Overall, this work showed successful DIW of an epoxy resin with a sustainable filler improving its stiffness and thermal properties and provides an avenue for further development of bio-based inks for DIW towards various applications.

Lamm, Meghan E. [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Boride-based Ceramic Super-high Temperature Thermocouples in Harsh Environments (Final Scientific/Technical Report)

An electromotive force (emf) can be generated along a temperature gradient between the cold end and hot end of a thermoelectric material, termed the Seebeck effect. Based on the Seebeck effect, metallic alloys have been extensively employed to detect temperatures for centuries, named thermocouples. However, commercially available thermocouple alloys suffer from limitations, such as oxidation, chemical degradation, and poor long-term stability under high-temperature harsh environments. This DOE-funded project aimed to develop high-temperature, chemically tolerant thermocouples suitable for operation in extreme environments relevant to semiconducting thermoelectric materials. The research focused on boride-based semiconducting thermoelectric compounds as candidates for next-generation thermocouples with enhanced oxidation resistance, chemical stability, and thermal robustness under conditions representative of charcoal-fired electricity facilities. During the funded years, boride materials were synthesized using an arc-plasma technique under ambient air and argon atmospheres, enabling scalable and cost-effective production compared with conventional boride fabrication methods. The synthesized borides were processed into nanostructured powders, followed by consolidation into dense bulk materials using a spark plasma sintering (SPS) bottom-up approach. Comprehensive characterization was performed, including microstructural analysis, electrical transport measurements, and optical and thermal property evaluation. Both p-type and n-type boride electric legs were fabricated and integrated into boride-based thermocouples. The thermal and irradiation stabilities of the boride nanomaterials and bulk thermoelectric materials were systematically evaluated to assess suitability for long-term operation in harsh environments. Additionally, 12 students were broadly hands-on trained spanning the full research workflow, including word processing and technical editing (e.g., LATEX for manuscript and poster preparation), data collection and analysis (using Python and related libraries and hardware interfaces), sample preparation (including arc-plasma synthesis and spark plasma sintering), and advanced characterization techniques (such as X-ray diffraction, UV–vis spectroscopy, electron microscopy, differential thermal analysis (DTA), and Seebeck coefficient measurements, etc). Overall, this project demonstrated the feasibility of boride-based thermoelectric materials as durable high-temperature thermocouples, providing a promising pathway toward robust temperature sensing technologies aligned with DOE energy infrastructure and extreme-environment monitoring needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Annealing-Driven Phase Control Enables Plasmonic Tunability in Alloy Nanoparticles

A critical aspect of designing and realizing useful solid state materials is controlling phase and structure to tailor physical properties. While common for semiconductor and quantum materials, plasmonic materials have inhabited a narrow phase space typically comprising one or two elements, e.g., face-centered cubic metals. While this simplicity has enabled robust use and understanding of Au and Ag nanoparticles, it has also limited the design and manipulation of solid state properties. Here, we show that by tuning the phase and elemental composition of binary Au−Sn nanoparticles, the steady-state absorbance and ultrafast thermalization properties of plasmonic nanoparticles can be controlled. Solid state characterization suggests this is due to the dealloying of Sn and destabilization of the AuSn phase, leading to higher quality Au 5 Sn intermetallic phases alongside Au. Consequently, this work shows that phase control can profoundly influence the properties of plasmonic nanoparticles, providing important tunability for applications in catalysis, photothermal heating, and sensing.

Gold↗
DOE OSTI2025

Self-Heating Conductive Ceramic Composites for High Temperature Thermal Energy Storage

The absence of affordable and deployable large-scale energy storage poses a major barrier to providing zero-emission energy on demand for societal decarbonization. High temperature thermal energy storage is one promising option with low cost and high scalability, but it is hindered by the inherent complexity of simultaneously satisfying all of the material requirements. Here we design a class of ceramic–carbon composites based on co-optimizing mechanical, electrical, and thermal properties. Further, these composites demonstrate stability in soak-and-hold tests and direct self-heating up to 1,936 °C and 750 thermal cycles from 500 to 1,630 °C without degradation. This thermal performance derives from their composition and microstructural design as verified by in situ high-temperature transmission electron microscopy and X-ray diffraction. They offer both higher energy density and lower cost than conventional storage technologies with a projected system Levelized Cost of Storage below the U.S. Department of Energy’s 2030 target 5 ¢/kWh (electric).

25 ENERGY STORAGE↗
DOE OSTI2025

Enhancing The Thermal Resistivity of Rigid Polyisocyanurate Foam Insulation

The development of rigid polyurethane foam insulation has garnered considerable attention because of its promising applications in the buildings and construction industry. Its low thermal conductivity makes it an attractive choice for improving energy performance in buildings. Current Rigid Polyurethane foams have thermal resistivity (R-value/in.) 5.5 to 6.5 h.ft2F/BTU/in.· that could be further improved by diminishing the heat transfer through the foam matrix. Nevertheless, minimizing both conduction (through gas and solid) and radiation simultaneously in porous solids is a significant challenge due to the trade-off between these two mechanisms. This study focuses on improving the R-value of the insulation foams via several strategies: such as type and the amount of the surfactants, blowing agent content and precooling and premixing polyol mixture. These methods optimized thermal properties of the PIR foams, achieving R/in. as high as 8.3. This excellent R/in. is anticipated to be a critical factor in significantly advancing the thermal insulation performance of rigid polyurethane cellular foams, thereby enhancing their efficacy in energy-efficient building applications.

Wanasinghe Mudiyanselage Pahala Gedara, Shiwanka V↗
DOE OSTI2026

Infrared thermography NDT for in-situ defect detection in sandwich composite panel manufacturing

Composite manufacturing presents numerous challenges, as defects can arise from various sources throughout the process. In sandwich composite structures, the integration of a foam core introduces additional complexity and increases the likelihood of defect formation like delamination. To mitigate these issues and reduce the risk of future structural failures, in-situ monitoring during manufacturing is essential. This study investigates infrared (IR) thermography as a non-destructive technique for detecting manufacturing defects in foam-core sandwich composite panels under thermally excited conditions representative of in-situ processing. A stationary FLIR A8590 IR camera (640 × 512 pixels, 30Hz, 17mm lens, 9 ft stand-off distance) was used to monitor prefabricated panels subjected to controlled external heating simulating compression molding and resin cure exotherm. Interlaminar delamination defects with characteristic sizes ranging from 0.25 × 0.25in² to 5 × 5in² produced measurable surface temperature depressions of approximately 4–10°C during transient cooling, exceeding the effective noise floor of the camera by more than two standard deviations. Thicker laminates exhibited prolonged defect detectability windows due to increased thermal diffusion time. In contrast, embedded Teflon inclusions generated weak thermal contrasts of ≤ 3°C, approaching the measurement noise floor, due to limited thermal property contrast with the surrounding glass fiber composite. These results establish quantitative detectability limits for stationary thermographic inspection of sandwich composite panels under manufacturing-representative thermal cycles.

Barakat, Abdallah [ORNL] (ORCID:0000000296141398)↗
DOE OSTI2025

Implications of point defect accumulation on UO 2 thermal conductivity and fission gas release under accelerated fuel irradiation

Evaluation of thermal properties is a crucial factor for nuclear fuel performance. During reactor operation, the accumulation of fission products and irradiation-induced lattice defects are responsible for degradation in thermal conductivity. Consequently, it affects fuel temperature and fission gas release (FGR) among other Multiphysics processes important for economics and safety analysis. We analyze the implications of point defects (PD) accumulation described using a rate theory (RT) Model on lattice thermal conductivity of UO 2 . Here, we demonstrate that fission rate-dependent point defect concentrations have the largest impact on in-pile thermal conductivity in the periphery of light water reactor fuels below a temperature threshold governed by the migration barrier of defects. Our analysis provides a mechanistic description of this phenomena which current fuel performance codes treat empirically. The reduction of thermal conductivity in the low -temperature rim region acts as additional thermal resistance and leads to a temperature notably larger than suggested by Lucuta thermal conductivity correlation. These effects are anticipated to have notable impacts when fuels are exposed to accelerated radiation. The impact of such point defect-informed treatment of thermal conductivity on fuel performance is evaluated by a detailed analysis of fission gas behavior and its release. We consider several models capturing different stages of fission gas bubble evolution and fission gas release (FGR). Finally, a new fission rate-dependent correction to the Lucuta correlation is proposed. The results show a significant reduction in thermal conductivity at the fuels’ periphery and an increase in fuel centerline temperature specifically at low burnups. Ultimately a modified LC shows a higher FGR compared to the original LC, while the acceleration process results in a reduction in overall FGR.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The impact of pulse width modulation on heat accumulation in AlGaN channel HEMTs

The poor thermal properties of Aluminum–Gallium Nitride (AlGaN) channel High Electron Mobility Transistors (HEMTs) on sapphire limit the device’s maximum switching frequency due to high channel temperatures. Extracting the correct thermal time constants can provide guidelines for the device’s safe frequency operation. This study experimentally quantifies the impact of pulse width and duty cycle on the transient thermal dynamics of multi-finger AlGaN channel HEMTs. In most transient thermal metrology, lock-in averaging approaches are leveraged to increase signal-to-noise ratio and measure the device’s relative temperature rise. Assuming no heat accumulation, the temperature rise is used to quantify the device’s thermal resistance under continued pulsed biasing. For devices grown on sapphire substrates, however, heat accumulation leads to elevated reference temperatures and causes the differential measurement to underestimate the peak temperature. This study demonstrates the capability of transient Gate Resistance Thermometry (tGRT) to measure the absolute temperature, which is required to precisely evaluate the device’s thermal resistance. When an absolute temperature measurement is not feasible (such as thermoreflectance imaging), a solution is proposed to derive the peak temperature under pulsed biasing based on the differential temperature under pulsing and the steady-state thermal resistance (which is typically easier to obtain). Finally, additional tGRT (without averaging) is performed to demonstrate the temperature-dependent thermal time constants required to minimize heat accumulation effects.

Field effect transistors↗
DOE OSTI2024

Accelerating the Scalability of PrintCast structures using High Pressure Die Casting

PrintCast composites are fabricated by infiltrating a metal mesh or preform (e.g., an additively-manufactured 316L lattices) with molten metal of a lower melting temperature (e.g., A380 aluminum). The resulting PrintCast composite has been shown in the literature to produce diverse and unique mechanical properties that are controllable at the local or global level by adjusting volume-fraction and/or topology of the preforms geometry and overall volume fraction. Although promising mechanical and thermal properties have been achieved at the laboratory scale level, the scalability from laboratory to full scale components has been limited using conventional casting infiltration. This work highlights how using high pressure die casting can significantly advance the development and eventual deployment of PrintCast approaches at large scales. We have successfully produced 9-inch by 6-inch by 1-inch thick PrintCast 316L stainless steel/A380 aluminum “bricks” via high pressure die casting. Initial findings show excellent infiltration and production capability. The resulting approach demonstrates the scalability and manufacturability of hybrid cost effective metal-metal matrix composites at larger length scales with high quality infiltration results.

Splitter, Derek↗