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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluation of High Level Waste Sludge Processing Behavior

The U.S. Department of Energy’s (DOE) Hanford Site has 177 underground storage tanks that contain wastes from past nuclear fuel reprocessing and waste-management operations. Over 20% of this waste is in the form of an insoluble sludge that will require slurry modification before its transfer to the Waste Treatment and Immobilization Plant (WTP). Specific WTP acceptance criteria for waste feed delivery describe the physical and chemical characteristics of the waste that must be met before the waste is transferred to the WTP. One challenging requirement relates to the undissolved solids (UDS) composition in a waste feed because the waste contains solid particles that settle, and their concentration and relative proportion can change during the transfer of the waste in individual batches. A key uncertainty is the ability to transfer and mix wastes with large variations in UDS concentrations and resulting settling rates. To address this uncertainty, a number of small scale mixing and settling tests have been conducted to determine the mobilization performance of variable chemistry simulants. Comparison of the size and density of the particulate for each simulant to that of southeast area Hanford sludge was made using metrics for particle mobilization, suspension, settling, and pipeline transfer where dependance on particle size and density may be different, including: 1. Settling velocity, 2. Critical shear stress for erosion, 3. Just-suspended impeller speed, and 4. Pipeline critical transport velocity. Existing high-level waste sludge data has shown the effect that increasing Al concentration has on resulting settled solids. This differential settling of particles in the sludge has the possibility of resulting in solids segregation during feed preparation and uneven particle distribution during pipeline transportation or mixer jet pump operations. Understanding the predictive capabilities of HLW solids settling and transport as well as potential remedies for addressing disparate sludge behaviors can help provide technical guidance during HLW flowsheet planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Quantum AI Based Enhanced Detection of Dementia

Quantum computing has the potential to significantly improve the early detection of Alzheimer's Disease and Related Dementias (ADRD). Quantum-enhanced machine learning can be used to perform an early screening of Alzheimer's disease using brain imaging data based on dataset of MRI scans from both healthy individuals and those diagnosed with Alzheimer's. This study aims to demonstrate the potential of quantum transfer learning to enhance the performance of the classical deep learning model for dementia detection. Using the MRI sagittal images available in the OASIS-2 (64 demented and 72 non-demented subjects between 60 and 96 years), we show how quantum techniques can transform a suboptimal classical model into a more effective solution for dementia detection, highlighting their potential impact on advancing healthcare technology. We begin with a simple classical deep learning model with a significantly smaller number of parameters, which gives suboptimal performance on the problem. Then, we apply different configurations of quantum transfer learning based on the pre-trained weak classifier (Figure 1). We fix the weak classifier's initial convolutional layers at their fixed pre-trained parameters and replace the last set of dense layers with a dressed quantum circuit (DQN), which we train to enhance performance. We performed 4-fold cross-validation for both the classical and the hybrid quantum models and trained them using Pennylane's `default.qubit' simulator and IonQ's Aria-1 simulator (noisy simulation). We showed that with significantly fewer parameters, the quantum transfer learning-based hybrid models showed significant performance enhancement over the base weak classical deep learning model for dementia detection. To classify between a demented and non-demented subject, the accuracy of quantum-based AI methods improved by 6 to 14% compared to classical methods. The sensitivity of the models improved by 4 to 17%. This shows that there are fewer chances of misclassifying demented patients. Figure 2 compares the performance of the hybrid quantum models and their base classical model, and Table 1 summarizes the results. We illustrated that with assistance from quantum machine learning, it is possible to enhance detection for dementia based on brain images. This shows the potential for practical utility of quantum computing in ADRD research.

Bhowmik, Sounak [University of Tennessee, Knoxvill↗
DOE OSTI2025

Exploring the impact of surface topography on Rayleigh-Bénard dry convection in the Pi cloud chamber using OpenFOAM: In cylindrical and rectangular geometries

The Pi convection-cloud chamber can generate steady-state turbulence in both rectangular and cylindrical shapes via Rayleigh-Bénard convection (RBC) by maintaining warm bottom and cold top surfaces. Although most experiments in the Pi chamber were conducted in cylindrical shapes, all previous Pi chamber simulations were conducted in a rectangular shape due to the limitations of those models to discretize a cylindrical domain when using the finite difference method therein. Here, we use OpenFOAM, an open-source finite-volume-based Computational Fluid Dynamics (CFD) software package, to conduct Large-Eddy Simulation (LES) of dry RBC in the Pi chamber at high Rayleigh numbers (10 8 to 10 9 ). Results show that large-scale circulation (LSC) direction varies in the chamber with a constant side wall temperature. Imposing a slight temperature imbalance at the side wall ranging from 0.1 to 0.7 degrees can lock the LSC, aligning better with Pi chamber observations, particularly at higher Rayleigh numbers. In addition, we examine the impact of surface topography on LSC and heat transfer in RBC systems within cylindrical and rectangular shapes under varying conditions. Results show that roughing top/bottom surfaces by adding bars of a few tens millimeters height can strengthen thermal plumes and enhance temperature fluctuations in the chamber. Furthermore, we observe that different bar height configurations lead to notable changes in LSC orientation and thermal stratification, highlighting the complex interactions between surface features and convection patterns. This finding highlights how surface topography and chamber geometry affect Rayleigh-Bénard convection, improving understanding of turbulent heat transfer and atmospheric boundary-layer processes. Direct Numerical Simulations (DNS) are also conducted to validate LES results. In conclusion, while LES effectively captures qualitative behaviors seen in DNS, it tends to underestimate velocity variances near walls, illustrating a trade-off between computational efficiency and accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Spatiotemporal Variability in Transport and Reactive Processes Across a First- to Fifth-Order Fluvial Network

Fluvial networks integrate and transport constituents from terrestrial and aquatic ecosystems. To date, most research on water quality dynamics has focused on process understanding at individual streams and, as a result, there is a lack of studies analyzing how small-scale, physical and biogeochemical drivers scale across fluvial networks. We performed tracer tests in five stream orders of the Jemez River continuum in New Mexico, USA, to quantify reach-scale hyporheic exchange during two different seasonal periods to address: how do hyporheic zone contributions to riverine processing change with space and time? And does the spatiotemporal variability of hyporheic exchange scale across fluvial networks? Combining conservative (i.e., bromide) and reactive (i.e., resazurin) tracer analyses with solute transport modeling, we found a dominance of reaction-limited transport conditions in space (for all stream orders) and time (two contrasting flow regimes). Moreover, we found a trend toward more reaction-limited conditions with increasing discharge across all stream orders. While our studied fluvial network did not consistently follow the expectations of decreasing hyporheic exchange contributions with increasing stream order, as it has been previously suggested from modeling studies, we found that processing rate coefficients and Damköhler numbers consistently decreased along the continuum with increasing discharge. Our findings suggest that knowledge transferability of hyporheic zone processing along fluvial networks may be possible if the scaling patterns that we found hold true in other catchments. Thus, more research on scaling patterns along fluvial networks is highly needed.

Gootman, Kaylyn S.↗
DOE OSTI2020

Surface photovoltage spectroscopy observes junctions and carrier separation in gallium nitride nanowire arrays for overall water-splitting

Gallium nitride (GaN) nanowire arrays on silicon are able to drive the overall water-splitting reaction with up to 3.3% solar-to-hydrogen efficiency. Photochemical charge separation is key to the operation of these devices, but details are difficult to observe experimentally because of the number of components and interfaces. Here, we use surface photovoltage spectroscopy to study charge transfer in i-, n-, and p-GaN nanowire arrays on n+ -Si wafers in the presence and absence of Rh/Cr 2 O 3 co-catalysts. The effect of the space charge layer and sub-bandgap defects on majority and minority carrier transport can be clearly observed, and estimates of the built-in potential of the junctions can be made. Transient illumination of the p-GaN/n + -Si junction generates up to -1.4 V surface photovoltage by carrier separation along the GaN nanowire axis. This process is central to the overall water-splitting function of the n + -Si/p-GaN/Rh/Cr 2 O 3 nanowire array. Overall, these results improve our understanding of photochemical charge transfer and separation in group III–V semiconductor nanostructures for the conversion of solar energy into fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Row spacing as a controller of solar module temperature and power output in solar farms

We report that when the temperature of solar photovoltaic modules rises, efficiency drops and module degradation accelerates. The spatial arrangement of solar modules can affect convective cooling and, consequently, module temperatures. However, the impact of row spacing on convective cooling in realistic solar farms has not yet been studied. Here, we develop six solar farm arrangements consisting of a fixed number of rows with varying streamwise row spacing. We model the flow and heat transfer of each solar farm using high-resolution large-eddy simulations. Results indicate that increasing row spacing can enhance convective cooling by 14.8%, which reduces module temperature by 6.6 °C and increases power output by 4.0% on average.

14 SOLAR ENERGY↗
DOE OSTI2022

Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports

One of the goals of the Surveillance, Epidemiology, and End Results (SEER) program is to estimate incidence, prevalence, and mortality of all cancers. To that end, cancer registries across the country maintain a massive database of cancer pathology reports which contain rich information to understand cancer trends. However, these reports are stored in the form of unstructured text, and human annotators are required to read and extract relevant information. In this article, we show that existing deep learning models for automating information extraction from cancer pathology reports can be significantly improved by using ensemble model distillation. We found that by training multiple predictive models and transferring their knowledge to a single, low-resource model, we can reduce the number of highly confident wrong predictions. Our results show that our implemented methods could save 1000s of manual annotation hours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

First Simultaneous Determination of Inclusive and Exclusive | V u b |

The first simultaneous determination of the absolute value of the Cabibbo-Kobayashi-Maskawa matrix element V ub using inclusive and exclusive decays is performed with the full Belle data set at the $Υ$(4S) resonance, corresponding to an integrated luminosity of 711 fb -1 . We analyze collision events in which one B meson is fully reconstructed in hadronic modes. This allows for the reconstruction of the hadronic X u system of the semileptonic b → $πℓe_ℓ$ decay. We separate exclusive B → $πℓ\overline{ν}_ℓ$ decays from other inclusive B → $X_uℓ\overline{ν}_ℓ$ and backgrounds with a two-dimensional fit that utilizes the number of charged pions in the X u system and the four-momentum transfer q 2 between the B and X u systems. Combining our measurement with information from lattice QCD and QCD calculations of the inclusive partial rate as well as external experimental information on the shape of the B → $πℓe_ℓ$ form factor, we determine |$V^{excl}_{ub}$| = (3.78 ± 0.23 ± 0.16 ± 0.14) × 10 -3 and |$V^{incl}_{ub}$| = (3.88 ± 0.20 ± 0.31 ± 0.09) x 10 -3 , respectively, with the uncertainties being the statistical error, systematic errors, and theory errors. The ratio of |$V^{excl}_{ub}$|/|$V^{incl}_{ub}$| 0.97 ± 0.12 is compatible with unity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Direct Measurement of Diffusion Coefficients: Evidence for Diffusive Stochastic Heating in Collisionless Plasmas

Open questions in collisionless plasma dissipation can be addressed using space-based observations in different astrophysical environments, with implications for both astrophysical and laboratory plasma systems. We study a low-𝛽, highly imbalanced, sub-Alfvénic stream observed by Parker Solar Probe (PSP) to identify and distinguish between signatures of stochastic heating (SH) and resonant heating (RH) by parallel ion cyclotron waves (∥-ICWs). Prior work studying this stream [Trevor A. Bowen et al., Stochastic heating in the sub-Alfvénic solar wind, Phys. Rev. Lett. 135, 255201 (2025)] showed that the SH rate, accounting for intermittency, matched the amplitude of the local energy transfer (LET) rate, while the RH rate did not. This comparison relied on a number of assumptions regarding the nature of the diffusive process and the calculation of the LET rate. We introduce a novel technique of inverting the proton guiding center equation to empirically measure velocity-space diffusion coefficients using three-dimensional proton velocity distribution functions, from the ion electrostatic analyzer (the Solar Probe Analyzer for Ions) on PSP. Measured diffusion coefficients are used to determine phase-space heating rates, leading to a calculation of a fully kinetic heating rate independent of assumptions made in prior work. We show that scale-dependent analytic expressions for SH via noncoherent fluctuations match the empirical measurements from PSP data, provided that we account for intermittency in the heating calculation. In contrast, the derived heating rates for SH that accounts for the effects of the helicity barrier and heating rates for RH via ∥-ICWs do not peak in the same region of velocity space as the empirical measurements, nor do they reach the required magnitude. Our approach provides novel methodology to uniquely identify and constrain heating processes in collisionless plasmas and shows evidence of a Fokker-Planck-like diffusive process in the near-Sun solar wind.

Plasma kinetic theory↗
DOE OSTI2020

Experimental Investigation of Sweeping Jet Film Cooling in a Transonic Turbine Cascade

Abstract The sweeping jet (SJ) film cooling hole has shown promising cooling performance compared to the standard shaped hole in low-speed conditions. The present work demonstrates the first attempt of SJ film cooling at an engine relevant Mach number. An experimental investigation was conducted to study the SJ film cooling on a nozzle guide vane suction surface. A well-established additive manufacturing technique commonly known as stereolithography (SLA) was utilized to design a transonic, engine representative vane geometry in which a row of SJ holes was used on the vane suction surface. Experiments were performed in a linear transonic cascade at an exit Mach number of 0.8 and blowing ratios of BR = 0.25–2.23. The measurement of heat transfer was conducted with the transient IR method, and the convective heat transfer coefficient (HTC) and adiabatic film cooling effectiveness were estimated using a dual linear regression technique (DLRT). Aerodynamic loss measurements were also performed with a total pressure Kiel probe at 0.25Cax downstream of the exit plane of the vane cascade. Experiments were also conducted for a baseline-shaped hole (777-hole) for a direct comparison. Results showed that the SJ hole has a wider coolant spreading in the lateral direction near the hole exit due to its sweeping motion that improves the overall cooling performance particularly at high blowing ratios (BR > 1). Aerodynamic loss measurement suggested that the SJ hole has a comparable total pressure loss to the 777-shaped hole.

Engineering↗
DOE OSTI2023

Heat Transfer and Pressure Loss of Additively Manufactured Internal Cooling Channels With Various Shapes

Abstract Additive manufacturing (AM) provides the ability to fabricate highly customized internal cooling passages that are relevant to gas turbine components. This experimental study examines the pressure loss and heat transfer performance of a range of fundamental channel shapes that were produced using direct metal laser sintering. Circular, hexagonal, pentagonal, elliptical, diamond, square, rectangular, trapezoidal, and triangular channel cross sections were investigated. To maintain the same convective surface area between shapes, the wetted perimeters of the channel cross sections were kept constant. Parallel computational fluid dynamic simulations were performed to understand the relationships in cooling performance between several channel shapes. Several characteristic length scales were evaluated to scale the pressure loss and heat transfer measurements. Among the channel shapes investigated, the diamond channel showed the lowest Nusselt number and friction factor. The pentagon exhibited a similar Nusselt number as the circular channel despite having a lower friction factor. There was no difference in scaling the friction factor or Nusselt number results of the different channel shapes between using the square root of cross-sectional area compared to hydraulic diameter as the characteristic length scale

Engineering↗
DOE OSTI2023

Benchmarking the AirSquared All-Metal Scroll Pump Against the Normetex 15 - Preliminary report

Tritium operations require specialized equipment for material compatibility, safety, and waste considerations. Non-metallic pump materials (polymer, oil, or grease) on a tritium-wetted surface can absorb tritium and/or undergo isotope exchange between tritium and more common protium, creating tritiated compounds that can result in material property modification via beta-radiolysis, inventory loss, reduced performance and special waste considerations, all of which increase the operating cost for a facility. Vacuum pumps move gas via a pressure differential between volumes of an operation. Several types of all-metal vacuum pumps exist for this application including metal bellows, diaphragm and scroll pumps. A metal bellows pump incorporates only metal components at the wetted surfaces. The common metal bellows pump employed in tritium facilities, the MB601 (Senior Metal Bellows, Sharon, PA, USA) creates a gas-motive force with a vacuum pressure between 30-40 torr. These pumps can efficiently move gas from one process step to another, as long as sub-30 torr pressures are not required. However, for higher vacuum demand, an all-metal scroll pump can be used with the bellows pump serving as a “backing” pump. This configuration typically provides an achievable vacuum of less than 20 mTorr. All-metal scroll pumps are a technology uniquely applicable to tritium gas handling. The industry standard all-metal scroll pump for glovebox-scale tritium operations is the Normetex 15 m 3 /hr, typically referred to as the Normetex 15 (Normetex Pompes, Pont Audemer, France). However, the final Normetex pumps were manufactured in 2012, rendering them no longer available. Eumeca SaRL (formerly Normetex) has developed and is marketing a scroll pump based on the design of the Normetex 15. A US company, AirSquared (Broomfield, Colorado), has developed and is marketing a potential alternative to the Normetex 15. The Gas Transfer Systems group (Q-7) of the Los Alamos National Laboratory (LANL) procured serial number 0001 of the AirSquared All Metal Vacuum Scroll pump model number V16H034A-C01 in 2019. The LANL Hydrogen Processing Laboratory (HPL) has been evaluating the performance of the pump compared to a Normetex pump as a potential replacement in tritium and fusion facilities requiring this type of pump.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

NRC Multiphysics Analysis Capability Deployment FY21: Part 3

This report details the progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Support for Advanced Non-Light Water Reactors.” The deliverables completed for this report are: Deliverable 1c: the capability to model gas mixtures was added to Pronghorn. A test problem mimicking the conditions achieved in a depressurized loss of forced cooling (DLOFC) event was solved with both RELAP-5 and Pronghorn. Pronghorn employed a finite vol ume method with the Kurganov-Tadmor discretization. The comparison between the mass fraction spatial profiles computed with RELAP-5 and Pronghorn clearly shows the presence of numerical artifacts (i.e., overly diffusive behavior at low Mach numbers). We confirmed that the problem disappears at higher Mach numbers. We recommend future work on the implementation of a low Mach finite volume formulation to better treat low Mach number problems. Deliverable 2a: we demonstrated two approaches to model the radiation/conduction/natural convection heat transfer across a stagnant gas for the PBMR-400 design using Pronghorn. The first approach is based on the net radiation method, which relies on the computation of view factors with the Multiphysics Object-Oriented Simulation Environment (MOOSE) ray tracing capability. The second method is a traditional thermal resistance approach. The test problems include both 2D and 3D geometries. In all cases, the results show very good agreement during a DLOFC transient. This confirms that the faster thermal resistance method produces solutions that are equivalent to the net radiation method for this geometry. Deliverable 3d: we demonstrated the use of the advection kernel for the delayed neutron precursor equation in Griffin with a 2D MSFR model. The results appear physical but further verification is recommended. We also recommend the addition of conjugate heat transfer to compute the temperatures and model the thermomechanic behavior of the reflectors and other structures. Significant memory and performance issues were encountered in the 3D axisymmetric model. Future work is recommended in this area. Task 8g: this task allows multidimensional MOOSE applications to be coupled to system codes (RELAP-7 and SAM). We implemented a faster multiphysics iteration coupling algorithm, which provides an overall 6× acceleration of the 3D-1D coupling of the core multidi- mensional fluid flow solver and the 1D primary and secondary loop model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Peregrine Software Development: Report on the Code Conversion From Python to C++

This work package seeks to convert the Peregrine software tool from its original Python implementation to a production version based on the C++ language. Peregrine is a powerful research platform with a multitude of advanced data analytics and data visualization functionalities. Developed by scientists to explore multimodal and multidimensional data related to the production of components using powder bed additive manufacturing processes, the tool implements state-of-the-art algorithms to assist machine users in making build or part quality determinations. Given that Peregrine is data-intensive, the goal of this conversion is to enhance the tool’s flexibility and interactivity and reduce the number of code dependencies to facilitate its deployment as part of the ongoing technology transfer campaign. This brief document provides an overview of Peregrine’s functionalities and capabilities, along with a detailed description of the core functionalities that have been implemented to date in the new C++ version. This document serves as a development update at the end of the first year of the ongoing conversion and will be regularly updated as progress continues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Microscopic predictions for the production of neutron-rich nuclei in the reaction Yb 176 + Yb 176

Background: Production of neutron-rich nuclei is of vital importance to both understanding nuclear structure far from stability and to informing astrophysical models of the rapid neutron capture process (r-process). Multinucleon transfer (MNT) in heavy-ion collisions offers a possibility to produce neutron-rich nuclei far from stability. Purpose: The 176 Yb + 176 Yb reaction has been suggested as a potential candidate to explore the neutron-rich region surrounding the principal fragments. The current study has been conducted with the goal of providing guidance for future experiments wishing to study this (or similar) system. Methods: Time-dependent Hartree-Fock (TDHF) and its time-dependent random-phase approximation (TDRPA) extension are used to examine both scattering and MNT characteristics in 176 Yb + 176 Yb. TDRPA calculations are performed to compute fluctuations and correlations of the neutron and proton numbers, allowing for estimates of primary fragment production probabilities. Results: Both scattering results from TDHF and transfer results from the TDRPA are presented for different energies, orvientations, and impact parameters. In addition to fragment composition, scattering angles and total kinetic energies, as well as correlations between these observables are presented. Conclusions: 176 Yb + 176 Yb appears to be an interesting probe for the midmass neutron-rich region of the chart of nuclides. Lastly, the predictions of both TDHF and TDRPA are speculative, and will benefit from future experimental results to test the validity of this approach to studying MNT in heavy, symmetric collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Evolution of the Electronic Gap of Directly Synthesized Versus Mechanically Transferred WS 2 Monolayer to Multilayer Films

The electronic properties of 2D materials play a critical role in determining their potential for device applications. Despite rapid developments in 2D semiconductors, studies of fundamental electronic parameters, including the electronic gap and ionization energy, are limited, with significant discrepancies in reported values. The study focuses on tungsten disulfide (WS₂) and investigates the electronic structure of films comprising an increasing number of layers deposited with two different methods: direct synthesis via metal–organic chemical vapor deposition (MOCVD) and additive mechanical transfer of exfoliated single layers. The films are characterized via Raman, UV–vis, and photoluminescence spectroscopies, as well as ultraviolet photoelectron and inverse photoemission spectroscopies (UPS/IPES). The electronic gap of WS₂ is found to decrease from 2.43 eV for the monolayer to 1.97 eV for the trilayer, indicating a bulk transition at the trilayer thickness. This reduction in the electronic gap is primarily due to the downward shift of the conduction band minimum relative to the valence band maximum. A comparative analysis with MOCVD-grown WS₂ reveals a slightly larger electronic gap for MOCVD-grown samples, attributed to differences in defect densities. The electronic levels evaluated through UPS/IPES highlight the significant influence of preparation methods on the electronic properties of WS₂.

2D materials↗
DOE OSTI2020

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T g ) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T g predictions of various polymers with different chemistries, polymer side chain lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Representations and strategies for transferable machine learning improve model performance in chemical discovery

Strategies for machine-learning (ML)-accelerated discovery that are general across material composition spaces are essential, but demonstrations of ML have been primarily limited to narrow composition variations. By addressing the scarcity of data in promising regions of chemical space for challenging targets such as open-shell transition-metal complexes, general representations and transferable ML models that leverage known relationships in existing data will accelerate discovery. Over a large set (~1000) of isovalent transition-metal complexes, we quantify evident relationships for different properties (i.e., spin-splitting and ligand dissociation) between rows of the Periodic Table (i.e., 3d/4d metals and 2p/3p ligands). We demonstrate an extension to the graph-based revised autocorrelation (RAC) representation (i.e., eRAC) that incorporates the group number alongside the nuclear charge heuristic that otherwise overestimates dissimilarity of isovalent complexes. To address the common challenge of discovery in a new space where data are limited, we introduce a transfer learning approach in which we seed models trained on a large amount of data from one row of the Periodic Table with a small number of data points from the additional row. We demonstrate the synergistic value of the eRACs alongside this transfer learning strategy to consistently improve model performance. Analysis of these models highlights how the approach succeeds by reordering the distances between complexes to be more consistent with the Periodic Table, a property we expect to be broadly useful for other material domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗