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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Techno-economic prospects for producing Fischer-Tropsch jet fuel and electricity from lignite and woody biomass with CO 2 capture for EOR

This work explores the prospective techno-economic performance of facilities that produce low- and net-negative-carbon liquid transportation fuels and electricity with CO 2 capture for enhanced oil recovery. The lignite and biomass-to-jet fuel process is based on KBR’s TRIG gasifier, Rectisol (for sulfur removal and CO 2 capture), fixed-bed low temperature Fischer-Tropsch synthesis of liquid fuels, and Brayton/Rankine combined cycles to convert synthesis/refining off-gases and waste heat to electricity. This work leverages a recent, highly-detailed assessment of a prospective first-of-a-kind (FOAK) demonstration facility to develop highly detailed Aspen Plus process simulations for nine prospective N th -of-a-kind (NOAK) plant equipment configurations. Component-level capital costs from the FOAK study are scaled and adjusted to reflective prospective learning-by-doing to estimate capital costs for the NOAK designs. NOAK plant economic performance is found to be largely insensitive to variations in plant configurations and electricity output fraction, but biomass input fraction significantly affects profitability. Facilities that consume only carbon–neutral biomass, with no lignite co-feed, have significantly net-negative carbon emissions and the most favorable prospective economics when carbon emissions are priced. For these facilities, the crude oil price required for plant economic viability falls rapidly from $\$$100/bbl as carbon emission prices increase above $\$$120/tonne CO 2eq . In general, plants that co-fire lignite with biomass are less profitable (than 100% biomass plants) due to their higher net greenhouse gas emissions.

09 BIOMASS FUELS↗
DOE OSTI2024

Hydrothermal Corrosion of Latest Generation of FeCrAl Alloys for Nuclear Fuel Cladding

After the Fukushima nuclear disaster, the nuclear materials community has been vastly investing in accident tolerant fuel (ATF) concepts to modify/replace Zircaloy cladding material. Iron–chromium–aluminum (FeCrAl) alloys are one of the leading contenders in this race. In this study, we investigated FA-SMT (or APMT-2), PM-C26M, and Fe17Cr5.5Al over a time period of 6 months in simulated BWR environments and compared their performance with standard Zirc-2 and SS316 materials. Our results implied that water chemistry along with alloy chemistry has a profound effect on the corrosion rate of FeCrAl alloys. Apart from SS316 and Zirc-2 tube specimens, all FeCrAl alloys showed a mass loss in hydrogen water chemistry (HWC). FA-SMT displayed minimal mass loss compared to PM-C26M and Fe17Cr5.5Al because of its higher Cr content. The mass gain of FeCrAl alloys in normal water chemistry (NWC) is significantly less when compared to Zirc-2.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Flame acceleration and transition to detonation in a pre-/main-chamber combustion system

Numerical simulations are performed to study the mechanism of deflagration to detonation transition (DDT) in a pre-/main-chamber combustion system with a stoichiometric ethylene–oxygen mixture. A Godunov algorithm, fifth-order in space, and third-order in time, is used to solve the fully compressible Navier–Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The two-dimensional simulation shows that a laminar flame grows in the pre-chamber and then develops into a jet flame as it passes through the orifice. A strong shock forms immediately ahead of the flame, reflecting off the walls and interacting with the flame front. The shock–flame interactions are crucial for the development of flame instabilities, which trigger the subsequent flame development. The DDT arises due to a shock-focusing mechanism, where multiple shocks collide at the flame front. A chemical explosive mode analysis (CEMA) criterion is developed to study the DDT ignition mode. Preliminary one-dimensional computations for a laminar propagating flame, a fast flame deflagration, and a Chapman–Jouguet detonation are conducted to demonstrate the validity of CEMA on the chemical-diffusive model, as well as to determine the proper conditioning value for CEMA diagnostic. The two-dimensional analysis with CEMA indicates that the DDT initiated by the shock-focusing mechanism can form a strong thermal expansion region at the flame front that features large positive eigenvalues for the chemical explosive mode and dominance of the local autoignition mode. Thus, the CEMA criterion proposed in this study provides a robust diagnostic for identifying autoignition-supported DDT, of which the emergence of excessive local autoignition mode is found to be a precursor. The effect of grid size, initial temperature, and orifice size are then evaluated, and results show that although the close-chamber DDT is highly stochastic, the detonation initiation mechanism remains robust.

42 ENGINEERING↗
DOE OSTI2026

Development of MOSCATO: A CFD-Level Electrochemistry and Corrosion Simulator for Molten Salt Systems

For both coolant and fueled variants of molten salt reactors (MSRs), the corrosion of structural materials is a significant challenge. The corrosion stems from chemical and electrochemical reactions initiated by fissile material, fission products, and impurities in the salt. Lower-fidelity models rely on empirical correlations for mass transfer, simplified lumped temperature profiles, and similar assumptions. They do not capture detailed spatial variations in complex geometries, creating the need for high-fidelity modeling to bridge this gap.As we approach the demonstration and possible deployment of MSRs in this decade, the development of a high-fidelity, high-performance simulator becomes imperative. To simulate the complex electrochemical environment and corrosion within molten salt systems, we have developed the Molten Salt Chemistry And TranspOrt (MOSCATO) code. This endeavor is comprised of three essential components. First, mass transfer equations are coupled with the Navier-Stokes equations in order to account for the transport of species in the salt. Second, the diffusion of alloy constituents, such as Cr, Fe, Ni, etc. is simulated within the structural metals. Third, the alloy and salt domains are coupled to account for the heterogeneous chemical and electrochemical reactions that occur at the salt-alloy interface.MOSCATO manages all three components within the framework of the highly scalable, open-source spectral element method computational fluid dynamics code Nek5000/NekRS. This integration enables MOSCATO to harness the immense computational power of modern high-performance computing resources, ensuring both high fidelity and computational speed.In addition to code development, we have initiated a comprehensive verification and validation campaign, utilizing data from diverse sources. First, MOSCATO's electrochemical solver was verified with reference numerical data. Then validation occurred against experiments: one of a thermal galvanic cell and the other for corrosion in flowing molten salt of FLiNaK (LiF-NaF-KF). This campaign verified and validated MOSCATO as a reliable tool for simulating electrochemical environments and corrosion in molten salt systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Thermal and hydraulic performance of volumetrically heated triply periodic minimal surface heaters

Advanced heat transfer surfaces, mainly Triply Periodic Minimal Surfaces (TPMSs) have great potential to increase heat transfer performance over traditional heat transfer surfaces due to their tortuous flow path and higher surface area-volume ratio. The emergence of additive manufacturing of nuclear fuel motivates experimental investigation of such advanced geometries in the context of a nuclear reactor core. Here, this study employed a novel method to explore the performance of gyroid and diamond TPMS geometries. Volumetrically heated heaters were additively manufactured from conductive polymer filament, and airflow was used to simulate the convective heat transfer from the core within a nuclear reactor. The mass flow and volumetric generation rates were varied, local Nusselt number correlations were obtained using embedded thermocouples to measure the solid and fluid temperature, and friction factor correlations were developed using differential pressure measurements. The gyroid TPMS presented a friction factor 1.5 times higher than the diamond TPMS and 90 times that of the rod bundle. TPMS geometries showed Nusselt numbers 8–10 times higher than that of the rod bundle, also maintaining colder internal temperatures, which suggested that they could sustain 250–275 % higher power density than the rod bundle for a given centerline temperature. Hence, having the potential to greatly increase the safety margins and power output of a nuclear reactor core with similar volume.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Failure analysis of nuclear transient-tested UN tristructural isotropic fuel particles in a 3D printed SiC matrix

Fully ceramic microencapsulated fuel elements containing UN tristructural isotropic (TRISO) fuel particles within a 3D printed SiC matrix were subjected to transient testing with varying energy depositions. Detailed post-irradiation examinations were performed, including leaching in hot HNO3 and post-leaching X-ray computed tomography, to quantify the percentage of failed TRISO particles and crack propagation within the particles and surrounding fuel matrix. In parallel, detailed finite element analyses were performed for comparison with experimental findings and to better evaluate transient failure modes. The lowest transient energy deposition—which still exceeded bounding values for high-temperature gas-cooled reactor applications—resulted in no detectable TRISO particle failures or matrix cracking, which was consistent with the simulations. Simulations of the higher-energy transients for which significant TRISO particle failure was expected were generally able to reproduce the transient temperatures and matrix cracking. Thus, the TRISO particle failures were explained based on the effects of local SiC matrix thickness and porosity. Results generally confirmed the high strength of the additively manufactured SiC matrix but also affirmed the need for a modified UN TRISO architecture to prevent SiC matrix cracks from propagating through TRISO layers. This unique failure mode has not historically been considered for TRISO fuels contained in weaker graphite matrices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

FY2021 Progress Report on BISON Metallic Fuel Model Development and V&V Using EBR-II Legacy Data

In this report, the activities and achievements made by Argonne National Laboratory for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) BISON code metallic fuel validation and verification project in FY2021 are summarized. The cladding degradation model based on the FCCI/CCCI wastage calculations has been developed and implemented into BISON. A comprehensive evaluation of the cladding degradation model was performed based on FIPD data of the IFR experiment X447. BISON objects were also developed to enable direct use of time-varying cladding outer surface temperature profile as temperature boundary conditions, which proved to provide more accurate temperature predictions for the metallic fuel pins irradiated in EBR-II. Additionally, a new BISON object was implemented to enable direct comparison between BISON predicted data and FIPD-based post-irradiation examination (PIE) results, which would significantly facilitate BISON metallic fuel verification and validation (V&V) activities. These new BISON-FIPD integration features were used in the establishment of a low-burnup fuel swelling evaluation framework as demonstration. The framework was successfully used to evaluate current fuel swelling models based on the IFR experiment X423.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Testing of an Optical Fiber--Based Gamma Thermometer in the High Flux Isotope Reactor Gamma Irradiation Facility

This report describes the design, thermal modeling, and gamma irradiation testing of an optical fiber–based gamma thermometer (OFBGT), which was irradiated in the High Flux Isotope Reactor (HFIR) Gamma Irradiation Facility (GIF). OFBGTs are a promising technology for application in nuclear reactors because they can provide a distributed measurement of gamma ray heating rate, unlike thermocouple-based gamma thermometers, which are fixed in-core sensors that can be used in boiling water reactors to calibrate local power range monitors. OFBGTs measure gamma ray heating rate by measuring the temperature difference between a pair of optical fibers; one fiber is in thermal contact with a heat sink (usually the reactor coolant), and the other is in thermal contact with a thermally isolated mass. The device can be calibrated with a heating wire within the thermal mass. The OFBGT that was designed and fabricated at Oak Ridge National Laboratory can measure distributed gamma ray heating rate over an effective measurement length of 61 cm, and the outer diameter of the sensor is 12.7 mm, giving the prototypical sensor design a relatively small footprint. The sensor housing is backfilled with Ar to ensure a well-predicted thermal response that is not affected by humidity or chemical interactions during operation. For calibration, the sensor design uses a Ni–Cr wire, which can be supplied with currents from 0 to 1 A to capture the wide range of potential gamma ray heating rates expected in HFIR’s spent fuel elements. The OFBGT was thermally modeled analytically and numerically; both models account for temperature-dependent thermal conductivities of the materials and show good agreement. The thermal response of the sensor inside spent HFIR fuel elements was simulated for times up to 1 year after discharge of the fuel element. Out-of-pile open-air tests indicated that the steady-state response of the sensor matches modeled results within experimental uncertainty. Calibration tests were performed using electrical heating in the HFIR spent fuel pool, above the fuel elements, to establish a relationship between the difference in spectral shift measured by optical fibers located inside and outside the OFBGT and the applied electrical heating. Subsequently, the OFBGT was placed within the the spent fuel element from HFIR cycle 501 to measure the spatial profile of the gamma heating rates. Results showed good agreement between the theoretical and measured gamma dose rate profiles, with maximum deviations of ~10% or less.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

BISON High Burnup Structure Modeling Capabilities Validated with a Selection of the Halden IFA-650 Rods

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS)program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. This document continues analysis and refinement of capabilities added to BISON early this calendar year in regards to the incorporation of capabilities applicable to extended burnups in response to industry interest. Details are provided on high burnup thermal conductivity models, a refitting of the high-burnup structure (HBS) porosity formation model to include additional data, the coupling of the HBS volume fraction model to thermal conductivity and fine fragmentation models, and validation activities. The IFA-650.4 and IFA-650.9 loss of coolant accident (LOCA) analyses are revisited with the latest developments in this report. A new validation case, IFA-650.14 has also been added to the BISON test suite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Development of dispensing hardware for safe fueling of heavy duty vehicles

The development of safe dispensing equipment for the fueling of heavy duty (HD) vehicles is critical to the expansion of this newly and quickly expanding market. This paper discusses the development of a HD dispenser and nozzles assembly (nozzle, hose, breakaway) for these new, larger vehicles where flow rates are more than double compared to light duty (LD) vehicles. This equipment must operate at nominal pressures of 700 bar, -40o C gas temperature, and average flow rate of 5-10 kg/min at a high throughput commercial hydrogen fueling station without leaking hydrogen. The project surveyed HD vehicle manufacturers, station developers, and component suppliers to determine the basic specifications of the dispensing equipment and nozzle assembly. The team also examined existing codes and standards to determine necessary changes to accommodate HD components. From this information, the team developed a set of specifications which will be used to design the dispensing equipment. In order to meet these goals, the team performed computational fluid dynamic, pressure modelling, and temperature analysis in order to determine the necessary parameters to meet existing safety standards modified for HD fueling. The team also considered user, operational, and maintenance requirements, such as freeze lock which has been an issue which prevents the removal of the nozzle from LD vehicles. The team also performed a failure mode and effects analysis (FMEA) to identify the possible failures in the design. The dispenser and nozzle assembly will be tested separately, and then installed on an innovative, HD fueling station which will use a HD vehicle simulator to test the entire system.

08 HYDROGEN↗
DOE OSTI2020

Deep learning-based model for progress variable dissipation rate in turbulent premixed flames

A deep neural network (DNN) based large eddy simulation (LES) model for progress variable dissipation rate in turbulent premixed flames is presented. The DNN model is trained using filtered data from direct numerical simulations (DNS) of statistically planar turbulent premixed flames with n-heptane as fuel. Training data was comprised of flames with varying turbulence levels leading to a range of Karlovitz numbers. Through a-priori tests the DNN model is shown to predict the subfilter contribution to progress variable dissipation rate accurately over a range of filter widths and for all Karlovitz numbers examined in this study. Superior performance of the DNN model relative to an established physics-based model is also demonstrated. Additionally, transferability of the DNN model is highlighted by a-priori evaluation of the model using filtered DNS data from multiple cases with different Karlovitz numbers and fuel species than those that were used for training the model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Simulating competition in the US bioeconomy to produce hard‐to‐electrify transportation fuels using limited biomass resources

This study presents a novel bioeconomy optimization framework, BiOpt, designed to address critical questions regarding the strategic use of limited US biomass resources for biofuel production. By integrating detailed techno-economic analyses, life cycle assessments, and resource assessment data, BiOpt optimizes resource distributions across competing technologies to maximize economic performance and/or minimize greenhouse gas emissions. Using feedstock scenarios from the 2023 Billion Ton Study, the analysis explores optimal biomass allocations across sustainable aviation fuel, diesel, and marine biofuel conversion pathways given varying production targets and policy incentives. Results demonstrate distinct feedstock preferences and pathway utilizations when prioritizing economic returns vs. emissions reductions. For instance, fats, oils, and greases were highly favored in cost-optimized scenarios, while low-carbon feedstocks such as wet waste dominated greenhouse gas-minimized strategies. The findings underscore the pivotal role of policy incentives and technological advances in shaping biofuel supply chains and provide actionable insights for scaling sustainable biofuel production to decarbonize hard-to-electrify sectors. This framework offers a robust tool for policymakers and stakeholders to evaluate biofuel strategies that balance energy output, economic viability, and environmental impact.

09 BIOMASS FUELS↗
DOE OSTI2022

XE-100 modeling and simulation for neutronic analysis in MCNP6.2

XE-100 is a generation IV helium-cooled, graphite-moderated, pebble-bed reactor (HTGR). As part of the pathway toward a conceptually designing and licensing this reactor, an independent Monte Carlo model was created in MCNP6.2, and several distinct neutronic analyses were then performed. The double heterogeneity of TRISO fuel within graphite pebbles introduces unique modeling challenges related to particle and pebble clipping. The results show that for neutron and photon heating of ex-core components such as the reflector, RCSS, core barrel (CB), the model that contains clipping produces higher heating values. It is therefore concluded that removing clipping via compression of the particles and pebbles within the model distributes the neutrons and gammas preferentially toward the core center, and reduces the heating that is experienced toward the reactor periphery. Thus, the most conservative model for ex-core heating contains particle and pebble clipping. Also presented are results on the impact of chamfers that exist on the corners of graphite reflector blocks. As these chamfers could potentially create streaming paths, the neutron and gamma flux from the core to the CB were analyzed. It was determined that the chamfers do not significantly impact the neutron or gamma signatures on the CB, in that the shape of the neutron and photon flux on a detector imposed on the CB shows no preferential streaming path. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Final Report on Predictive Analyses of PRD as Function of Anomalies

This report summarizes the work completed in FY-2024 to analyze the power reactivity decrement (PRD) concepts of the ARC-100 core. The PRD has been traditionally defined by the reactivity change from a hot zero power (HZP) to a particular power. Consequently, the PRD accounts for the core reactivity changes due to increase coolant temperature gradient axially and radially across the core, and increased fuel temperature. The coolant temperature gradient leads to sodium and structure density changes, to radial core expansion from assembly flowering and bowing (due to axial and radial temperature gradients within the assemblies), and to control rod driveline thermal expansion. The fuel temperature increase associated with coolant temperature and power increases leads to Doppler effect and axial thermal expansion. In this work, the normal operating Hot Full Power (HFP) state is the only power level of interest, so analyses focus on the PRD calculated from HZP to HFP. The PRD has been used to assess the reactor safety features asymptotically in unprotected accident scenarios, including the loss of heat sink (LOHS), loss of flow (LOF), and transient overpower (TOP) without scram. The PRD concept relies on the “global” reactivity coefficients A, B, and C that are estimated based on “individual” reactivity effects (Doppler, sodium density, etc.). The objectives of this work are: 1) to improve and verify the methodology used to calculate the ABC coefficients used in the PRD, 2) to assess if the PRD can be used to reliably identify abnormal events. This report fulfills the FY-2024 scope of WBS#1.15.8.3 activity, “ANL0120 – Predictive Analyses of PRD as function of deformation”. The PRD concept is described in Sections 2. Additional effort in refining the methodology for core bowing modeling is performed in Sections 3. Then, two verification exercises are proposed in Section 4 to benchmark these coefficients based on direct neutronic-only calculations and on dynamic core transient simulations. Finally, the PRD approach is assessed for the detection of several unexpected events, such as primary flow perturbation or improper fuel loading, in Section 5.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Sensitivity of UO 2 fuel performance to microstructural evolutions driven by dilute additives

Use of dilute additives to nuclear fuel is being considered to increase the security of commercial fuel management through traceability of fabricated fuel elements. Taggants, as additives are denoted when included for traceability purposes, may also improve fuel performance, as demonstrated in Cr-containing uranium dioxide as described in the literature, and they may also improve fuel safety. In fact, studies have shown that some additives affect fuel material properties such as grain size and density after sintering. Given the possible range of elements that could be used as additives, the impact of such fuel property variations on the fuel’s thermomechanical behavior becomes relevant. These effects can be evaluated through a sensitivity study of standard fuel models to analyze changes in these properties using a fuel performance code. In this work, the BISON code is being used to investigate these effects through a 2D axisymmetric model of smeared UO 2 fuel pellets and ZIRLO® cladding under realistic pressurized water reactor core irradiation conditions. Here, randomly sampled densities and grain sizes within specified ranges are used as input parameters in the simulations, and several fuel model-related outputs are evaluated. The thermomechanical response of the cladding is also addressed in this study. The simultaneous variation of both input parameters offers a more comprehensive path to identify key sensitivities. Outputs explored include temperature, fission gas release, creep, and radial stress. Results show that although most of these outputs are sensitive to grain size to a certain extent, density mainly affects fuel temperature and elastic strain. Furthermore, sensitivities can vary depending on the radial position within the fuel pellet.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A pyrolysis study of allylic hydrocarbon fuels

The pyrolysis of selected C 3 –C 5 allylic hydrocarbons has been studied using a single-pulse shock tube. A new single-pulse shock tube has been designed and constructed by recommissioning an existing conventional shock tube. This facility enables the investigation of high-temperature chemical kinetics with an emphasis on combustion chemistry. The modifications performed on the existing shock tube are described, and the details of the sampling system to analyze the species concentration using a gas chromatography-mass spectrometry-flame ionization detection (GC-MS with a flame ionization detector) system are also provided. This facility is characterized and validated by performing cyclohexene pyrolysis experiments. Furthermore, the performance of the shock tube is demonstrated by reproducing previous literature measurements on the pyrolysis of isobutene. Postvalidation, this setup is used to study the pyrolysis of trans-2-butene and 2-methyl-2-butene (2M2B). A newly developed mechanism, NUIGMech1.0, is used to simulate the experimental data of propene, isobutene, 2-butene, and 2M2B, allylic hydrocarbon fuels. A description using two different kinetic simulation approaches is provided using our isobutene experiments as a reference. We found no significant differences between the two methods. Additionally, the contribution of different reaction classes on fuel consumption is detailed and the influence of geometry on fuel consumption and first aromatic ring: benzene is discussed.

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

Molten pool dynamics and humping suppression in high-speed laser welding via tailored beam configurations

High-speed laser welding is essential for increasing the production rate of fuel cell fabrication. However, when the welding speed exceeds a critical limit, humping occurs and reduces the weld quality. In this study, two tailored beam configurations, including an adjustable ring mode and a dual-beam configuration, were employed to suppress humping. Computational fluid dynamics simulations were performed to elucidate the underlying suppression mechanisms. Here, the results show that, in the adjustable ring mode, humping mitigation arises from a reduced backward cross-sectional melt flow rate and a more stable molten pool. In the dual-beam configuration, humping suppression is attributed to the deceleration of melt flow, the conduction-mode behavior of the trailing beam, and the widening of the molten pool induced by the trailing laser. Furthermore, because the dual-beam configuration directly modifies the trailing molten pool dynamics, it achieves more effective humping suppression, extending the welding speed limit to 1.50 m/s, compared with 1.00 m/s for the adjustable ring mode.

08 HYDROGEN↗
DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗