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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Simulated Polarimetric Fields of Ice Vapor Growth Using the Adaptive Habit Model. Part II: A Case Study from the FROST Experiment

Abstract A new adaptive habit model (AHM) grows ice crystals through vapor deposition while evolving ice particle properties, including shape and effective density. The AHM provides an opportunity to investigate observed microphysical processes through the computation of polarimetric variables and corroboration with microphysical model output. This study is unique because the polarimetric scattering calculations are computed using predicted microphysical parameters rather than a priori assumptions that are imposed within the scattering calculations in the forward simulator, allowing for a more effective comparison to radar observations. Through the simulation of a case in the Front Range of the Rocky Mountains in Colorado using the Advanced Research version of the Weather Research and Forecasting Model, it is found that the AHM approximates ice mass, shape, cloud vertical structure, and temporal evolution as reflected through polarimetric quantities compared to observations. AHM reflectivity magnitudes are similar to those observed with radar and are an improvement over spherical ice crystal assumptions. Further analyses are completed to examine the effect of microphysical processes on the evolution of the differential reflectivity and specific differential phase, both of which are simulated using the AHM. Simulations reveal a polarimetric response to ice crystal mass, number, size, density, and aspect ratio. While results reveal the need for model improvements (e.g., parameterizations for aggregation rate), testing forward-simulated radar fields against observations is a first step in the validation of model microphysical and precipitation processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures [Machine Learning a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures]

Alloy oxide heterostructures are essential for a wide variety of energy applications, including anticorrosion coatings, bifunctional catalysis, energy storage, as well as emerging platforms for multilevel nonvolatile memory and neuromorphic devices. The key role played by oxide composition, density, and stoichiometry in governing electrochemical reactions, interface structure, and ionic transport in alloy oxides remains largely unknown. This is primarily due to the lack of variable charge interatomic potential models that can adequately describe the various atomic/ionic interactions in alloy oxides within a unified framework. Here, we introduce a charge transfer ionic potential (CTIP) model for Cu/Hf/O alloy system and demonstrate its ability to accurately capture the complex potential energy surface owing to dynamically varying interactions, including metallic (Cu/Hf), ionic (Cu/Hf/Ox), mixed environment (interfaces). We leverage supervised machine learning methods powered by genetic algorithms coupled with local simplex optimization to efficiently navigate through a high-dimensional parameter space and identify an optimum set of an independent set of CTIP parameters. We train our model against an extensive first-principles based data set that includes lattice constants, cohesive energies, equations of state, and elastic constants of various experimentally observed polymorphs of hafnia, copper oxide, hafnium, as well as copper. Our machine-learned CTIP model captures the structure, elastic properties, thermodynamics, and energetic ordering of various polymorphs. It also accurately predicts the surface properties of both oxides and their metals. To demonstrate the suitability of our CTIP model for investigating dynamic processes, we employed it to identify the atomistic scale mechanisms associated with the initial nanoscale oxidation and surface oxide growth on Cu-doped hafnia surfaces. Here, our machine-learned CTIP model can be used to probe the dynamic response of Cu/Hf/O alloy interfaces subjected to external stimuli (e.g., electric field, pressure, temperature, strain, etc.) and a variety of atomistic phenomena including the dynamics of switching in emerging neuromorphic platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-moisture pelleting of corn stover using pilot- and commercial-scale systems: Impact of moisture content, L / D ratio and hammer mill screen size on pellet quality and energy consumption

Here, high-moisture pelleting of corn stover was tested in pilot- and commercial-scale systems. For the pilot-scale study, a 6.35 mm screen size hammer mill ground corn stover was reconditioned to moisture between 14 and 29.6% (w.b.), and 5, 7 and 9 L/D ratio pellet die were used. At 29% corn stover moisture content and L/D ratios of 5 and 9, the bulk density and durability of the pellets were ≤450 kg/m 3 and <90% and >540 kg/m 3 and >90%, respectively. Increasing the feedstock moisture and L/D ratio increased the pelleting energy. Increasing the hammer mill screen size to 11.11 mm reduced the bulk density but not the durability. The response surface models adequately described the pelleting process (R 2 ≥ 0.88), and analysis of variance showed a strong interaction between the process variables and pellet properties. Commercial-scale testing of high-moisture pelleting using 6.35 mm ground corn stover bales in the moisture range 24–26% (w.b.) produced pellets with a density of >675 kg/m 3 and durability of >98%, whereas increasing the hammer mill screen size to 11.11 mm reduced the bulk density by about 100 kg/m 3 but not the durability. The energy consumption of the commercial-scale unit operations for the high-moisture pelleting process was in the range 98–124 kW h/ton, which is 64–72% less energy than conventional pelleting that requires energy about 350 kW h/ton for biomass drying from 30% (w.b.) to 10% (w.b.) moisture content before pelleting. Pellets produced using high-moisture pelleting met International Organization for Standardization and Pellets Fuel Institute international standards. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

09 BIOMASS FUELS↗
DOE OSTI2026

Decadal Spiciness Variability in the Subtropical-Tropical Pacific in the CESM2 Large Ensemble

Tropical Pacific decadal variations impact weather and climate around the world and are also connected to variations in the global warming trend. The mechanisms driving these long-term modulations, particularly the role of subsurface ocean dynamics, are still debated. Here, we investigate the dynamics of spiciness (density-compensated temperature and salinity) anomalies in the tropical and subtropical Pacific, which are hypothesized as a possible driving mechanism of decadal climate variability. Based on the analysis of 100 realizations from the Community Earth System Model Version 2 Large Ensemble (CESM2-LE), we demonstrate a coupling between the subtropics and the equatorial Pacific by propagating spiciness anomalies at decadal time scales. The CESM2-LE simulates spiciness variability along a subduction path from the subtropics to the equator with frequency spectra that show the highest power at low frequencies and a power decay proportional to a −4 slope for frequencies greater than 0.01 cycles per months, corresponding to periods smaller than ∼8.5 years. Signals that originate in the Southern Hemisphere (SH) dominate and arrive with a larger magnitude at the equator compared to spiciness anomalies from the Northern Hemisphere (NH). Spiciness anomalies from the SH have shorter propagation times and are strengthened along their pathway as stochastic wind stress curl forcing generates anomalous baroclinic ocean pressure gradients. These pressure gradients generate spiciness anomalies via anomalous advection across climatological spiciness gradients in the SH. We conclude that the observed spiciness variance at decadal time scales is consistent with a forcing by stochastic wind variations that are low-pass filtered by ocean dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A mixed-integer PDE-constrained optimization formulation for constructing electromagnetic cloaks with multiple materials

We study the design of an electromagnetic cloak from multiple materials with an additional constraint on the mass of the cloak. Our problem is an example of a topology optimization problem, and we formulate this problem as a mixed-integer partial-differential equation constrained optimization (MIPDECO) problem, where Maxwell’s equation models the propagation of the wave through the cloak and surrounding medium. We use binary variables to model the assignment of the different materials, and their relevant properties (permittivity and density). The mass constraint adds a nontrivial constraint to this problem. We propose a two-phase strategy to solve this problem. In the first phase, we solve a continuous relaxation, and then propose a new variant of the feasibility pump that exploits the structure of the PDE to obtain an initial integral solution candidate. In the second phase, we use a trust-region approach to improve this incumbent. We also consider a continuation or mesh-sequencing approach to find better solutions faster on consecutively finer meshes. We present detailed numerical results to illustrate the effectiveness of our approaches for constructing multi-material cloaks with a mass constraint.

Calculus of Variations and Optimization↗
DOE OSTI2026

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗
DOE OSTI2026

Many-Body Benchmark of Electronic Charge and Spin Densities for Li 1–x NiO 2

Accurate benchmarks are particularly important for highly correlated oxides as mean-field approximations often fail to describe the subtle balance of charge transfer and magnetism in these materials with an accuracy comparable to experimental needs. Here we present accurate diffusion Monte Carlo (DMC) results of the electronic charge and spin densities for the tunable highly correlated oxide Li 1–x NiO 2 for x = 0, 1/2, and 1. To enable quantitative comparisons, we introduce a robust density-partitioning scheme, extending Voronoi analysis to assign atomic charges from spatially noisy DMC densities. We then benchmark common approximations used in density functional theory (DFT). Comparison against DMC shows that r 2 SCAN delivers the most balanced performance across charge, spin, and radial density descriptors, nearly reproducing DMC results for LiNiO 2 and apical Ni sites in Li 0.5 NiO 2 . Hybrid functionals (PBE0, SCAN0) perform unexpectedly poorly, and PBE + U + V yields inconsistent trends between charge and spin densities. Therefore, the r 2 SCAN functional minimizes errors relative to DMC while capturing the variable valence of the Ni ion and also retaining the computational efficiency of DFT for large-scale simulations of the tunable structural and electronic phases of Li1−xNiO2. Our study highlights the importance of accurate benchmarking of the fundamental quantities involved in DFT to select appropriate DFT approximations in order to advance the predictive modeling of charge-transfer-driven phenomena in correlated electron systems.

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

Conformational motions and ligand-binding underlying gating and regulation in IP 3 R channel

Inositol-1,4,5-trisphosphate receptors (IP3Rs) are activated by IP 3 and Ca 2+ and their gating is regulated by various intracellular messengers that finely tune the channel activity. Here, using single particle cryo-EM analysis we determined 3D structures of the nanodisc-reconstituted IP 3 R1 channel in two ligand-bound states. These structures provide unprecedented details governing binding of IP 3 , Ca 2+ and ATP, revealing conformational changes that couple ligand-binding to channel opening. Using a deep-learning approach and 3D variability analysis we extracted molecular motions of the key protein domains from cryo-EM density data. We find that IP 3 binding relies upon intrinsic flexibility of the ARM2 domain in the tetrameric channel. Our results highlight a key role of dynamic side chains in regulating gating behavior of IP 3 R channels. This work represents a stepping-stone to developing mechanistic understanding of conformational pathways underlying ligand-binding, activation and regulation of the channel.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Decomposition pathways and mitigation strategies for highly-stable hydroxyphenazine flow battery anolytes

Aqueous organic redox flow batteries are a promising technology for large-scale energy storage. The stability of the redox active organic molecules is increasingly being recognized as one of the major hurdles. Upon extended flow battery cycling, 7,8-dihydroxyphenazine-2 sulfonic acid (DHPS) undergoes desulfonation and reduction of a phenolic C–O bond to yield a mixture of 7/8-hydroxyphenazine-2-sulfonic acid, as well as hydrogenation of the aromatic ring system. Density functional theory (DFT) analysis of the charged DHPS, its ring-hydrogenated products, and variably substituted hydroxy phenazines has led to the development of a series of dihydroxylated phenazine isomers which provide insight into the effects of substitution pattern on solubility and stability. Seven dihydroxyphenazine (DHP) isomers were synthesized and their solubilities, electrochemical properties, flow battery cycling performance, and degradation pathways have been investigated. Based on theoretical and experimental results, hydroxyl substitution at the 1, 4, 6 and 9 positions yields highly stable derivatives, while substitution at the 2, 3, 7, and 8 positions results in unstable derivatives. Flow cells of 1,4- and 1,6-DHPs coupled with ferro/ferricyanide achieved high stabilities, with temporal capacity loss of 0.029 and 0.031% per day, respectively. Decomposition of 1,8- and 2,7-DHPs were found to arise from irreversible hydrogen rearrangement (tautomerization), yielding redox-inactive species. These results provide a detailed understanding of decomposition pathways and mitigation strategies for phenazine-based anolytes, and can provide general design guidelines for the development of stable redox-active organics.

25 ENERGY STORAGE↗
DOE OSTI2018

Conditions for successful range shifts under climate change: The role of species dispersal and landscape configuration

Abstract Aim Ongoing climate change is currently modifying the geographical location of areas that are climatically suitable for species. Understanding a species’ ability to successfully shift its geographical range would allow us to assess extinction risks and predict future community compositions. We investigate how habitat configuration impedes or promotes climate‐driven range shifts, given different speeds of climate change and dispersal abilities. Location Theoretical, but illustrated with European examples. Methods We model how a species’ ability to track a directional shift in climatic conditions is affected by (a) species’ dispersal abilities; (b) speed of climatic shift; and (c) spatial arrangement of the habitat. Our modelling framework includes within‐and between‐patch population dynamics and uses ecologically realistic habitat distributions and dispersal scenarios (verified with data from a set of European mammal species) and, as such, is an improvement of classical range shift models. Results In landscapes with a homogeneous distribution of suitable habitats, all but the least dispersive species will be able to range shift. However, species with high dispersal ability will have lower population densities after range shift. In heterogeneous landscapes species’ ability to range shift is far more variable and heavily dependent on the habitat configuration. This means that landscape configuration in combination with the speed of climate change and species dispersal abilities give rise to nonlinear effects on population sizes and survival after a climatic shift. Main conclusions Our analyses point out the importance of accounting for the interplay of species dispersal and the landscape configuration when estimating future climate impact on species. These results link ecologically important attributes of both species and their landscapes to outcomes of species range shift, and thereby long‐term persistence of ecological communities.

Årevall, Jonatan↗
DOE OSTI2019

Impedance Spectroscopy Characterization of PEM Fuel Cells with Fe-N-C-Based Cathodes

We report impedance spectroscopy analysis of PEM fuel cells built with platinum group metal-free (PGM-free) Fe-N-C cathodes with the catalyst loading and ionomer to catalyst ratio being variable parameters. The dependence of key cathode transport and kinetic parameters on the cell current density J are obtained in the range from 0.025 to 0.4 A cm -2 . The electrode performance is evaluated using the characteristic current densities for proton and oxygen transport in the cathode catalyst layer. Overall, certain electrode configurations demonstrate proton and oxygen transport properties comparable to those of Pt/C systems, making them promising substitutes for platinum at cathodic side of PEM fuel cells.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of short-read sequencing on the misassembly of a plant genome

Abstract Background Availability of plant genome sequences has led to significant advances. However, with few exceptions, the great majority of existing genome assemblies are derived from short read sequencing technologies with highly uneven read coverages indicative of sequencing and assembly issues that could significantly impact any downstream analysis of plant genomes. In tomato for example, 0.6% (5.1 Mb) and 9.7% (79.6 Mb) of short-read based assembly had significantly higher and lower coverage compared to background, respectively. Results To understand what the causes may be for such uneven coverage, we first established machine learning models capable of predicting genomic regions with variable coverages and found that high coverage regions tend to have higher simple sequence repeat and tandem gene densities compared to background regions. To determine if the high coverage regions were misassembled, we examined a recently available tomato long-read based assembly and found that 27.8% (1.41 Mb) of high coverage regions were potentially misassembled of duplicate sequences, compared to 1.4% in background regions. In addition, using a predictive model that can distinguish correctly and incorrectly assembled high coverage regions, we found that misassembled, high coverage regions tend to be flanked by simple sequence repeats, pseudogenes, and transposon elements. Conclusions Our study provides insights on the causes of variable coverage regions and a quantitative assessment of factors contributing to plant genome misassembly when using short reads and the generality of these causes and factors should be tested further in other species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Key process parameters to modify the porosity of cerium dioxide microspheres formed in the internal gelation process

Recently, an internal gelation study demonstrated that the use of heated urea and hexamethylenetetramine can have a pronounced impact on the porosity and sintering characteristics of cerium dioxide (CeO 2 ) microspheres. This effort has identified process variables that can significantly change the initial porosity of the CeO 2 microspheres with slight modifications. A relatively small difference in the sample preparation of cerium ammonium nitrate and ammonium hydroxide solution had a large reproducible impact on the porosity and slow pour density of the produced microspheres. Increases in the gelation temperature as small as 0.5 K also produced a noticeable increase in the slow pour density. If the gelation temperature was increased too high, the use of the heated hexamethylenetetramine and urea was no longer observed to be effective in increasing the porosity of the CeO 2 microspheres. In conclusion, the final process variable was the amount of dispersing agent, Span™ 80, which can increase the slow pour density and produce significantly smaller microspheres.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mapping the Binary Covalent Alloy Space to Pursue Superior Nitrogen Reduction Reaction Catalysts

The electrochemical nitrogen reduction reaction (NRR) has the potential to decarbonize industrial ammonia production. However, NRR has poor activity and selectivity versus the competing hydrogen evolution reaction for catalysts that adhere to scaling relations. Overcoming the limitations imposed by scaling relations requires more complex catalyst materials, however, evaluating materials beyond simple metal systems is a large combinatorial problem that requires an improved understanding of the electrocatalyst surface to rationally guide the discovery of superior catalysts. The study uses grand canonical density functional theory to uncover NRR trends on a large and disparate set of binary covalent alloys (BCA) with variable compositions and active-site geometries. The studied BCAs generally follow scaling relations, albeit with larger variance and several systems that significantly break scaling. BCAs with early- to mid-transition metals tend to lie near the volcano peak and activate the N 2 triple bond via a side-on binding configuration. Trends in the BCA space cannot be readily predicted using simple electronic descriptors, which is ascribed to the large geometric variability of the BCA surfaces. Furthermore, it is anticipated that these findings will provide a foundation for the rational design of superior NRR electrocatalysts with increasing material complexity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Three-dimensional charge density wave in the dual heavy fermion system UPt 2 Si 2

Heavy fermion liquids offer via their Kondo lattice diverse possibilities for exotic ground states. Using variable-temperature atomic pair distribution function analysis, we study the local atomic structure of the "dual" heavy fermion liquid UPt 2 Si 2 , which exhibits antiferromagnetism consistent with localized 5f-electron states and transport properties characteristic to itinerant 5f-"spd" hybridized electron systems. We show that UPt 2 Si 2 exhibits periodic lattice distortions (PLDs) involving both uranium and platinum atoms that are characteristic to three-dimensional charge density waves. Here, the temperature evolution of the PLDs tracks that of the transport and magnetic properties, suggesting the presence of little-known 5f-electron-lattice interactions. We argue that PLDs in heavy fermion liquids in general, and in particular in UPt 2 Si 2 , appear as new degrees of freedom that entangle competing electronic states and, as such, must be accounted for when their rich physics is considered.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identifying Periodic Variable Stars and Eclipsing Binary Systems with Long-term Las Cumbres Observatory Photometric Monitoring of ZTF J0139+5245

We present the results of our search for variable stars using the long-term Las Cumbres Observatory (LCO) monitoring of white dwarf ZTF J0139+5245 with the two 1.0 m telescope nodes located at McDonald Observatory using the Sinistro imaging instrument. In this search, we find 38 variable sources, of which 27 are newly discovered or newly classified (71%) based on comparisons with previously published catalogs, thereby increasing the number of detections in the field of view under consideration by a factor of ≈2.5. We find that the improved photometric precision per exposure due to longer exposure time for LCO images combined with the greater time sampling of LCO photometry enables us to increase the total number of detections in this field of view. Each LCO image covers a field of view of 26' × 26' and observes a region close to the Galactic plane (b = -9.°4) abundant in stars with an average stellar density of ≈8 arcmin{sup -2}. We perform aperture photometry and Fourier analysis on over 2000 stars across 1560 LCO images spanning 537 days to find 28 candidate BY Draconis variables, three candidate eclipsing binaries of type EA, and seven candidate eclipsing binaries of type EW. In assigning preliminary classifications to our detections, we demonstrate the applicability of the Gaia color–magnitude diagram as a powerful classification tool for variable-star studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Canopy tree mortality and crown exposure data from the Amacayacu Forest Dynamics Plot, Northwestern Amazon

Data on the mortality of 984 canopy trees, their crown exposure to light (relative to total crown area), growth deviations (relative to conspecifics), tree size, and species’ wood density collected between 2013 and 2019 in 18 ha of the Amacayacu Forest Dynamics Plot, Northwestern Amazon. This dataset contains a single CSV data file. Variable definitions: 1. Species: [character] species identification 2. Family: [character] family of the species 3. tag: [character] unique consecutive for the tree 4. status: [character] status of the tree in the third census (ALIVE or DEAD) 5. wsg: [numeric]: species’ wood density (g cm-3) 6. growth_r1: [numeric]: annual growth rate of the tree between the first and second census (cm y-1) 7. growth_r2: [numeric]: annual growth rate of the tree between the second and third census (cm y-1) 8. gt1: [numeric] modulus transformed growth rate with a lambda of 0.4 for the annual growth rate of the tree between the first and second census (cm y-1) 9. gt2: [numeric]: modulus transformed growth rate with a lambda of 0.4 for the annual growth rate of the tree between the second and third census (cm y-1) 10. rgr1: [numeric] relative growth rate between the first and second census (cm y-1) 11. rgr2: [numeric] relative growth rate between the second and third census (cm y-1) 12. sa_gt: [numeric] species-adjusted modulus transformed growth rate 13. sa_rgr: [numeric] species-adjusted relative growth rate 14. gr_n: [numeric] number of individuals of the species used to calculate the mean and species modulus transformed growth rate 15. dbh_flight: [numeric] diameter at breast height (1.3 m) estimated at the time of the drone flight (cm) 16. eca: [numeric] exposed crown area calculated as the area of the crown polygon delineated in the orthomosaic (m2) 17. total_ca: [numeric] total crown area estimated from a crown area model (m2) 18. rcel: [numeric] relative crown exposure to light (m2) 19. time_flight_census3: [numeric] time in years from the drone flight date to the third census for that tree (yr)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A phase-field fracture formulation for generalized standard materials: The interplay between thermomechanics and damage

Accurately modeling fracture of ductile materials poses open challenges in the field of computational mechanics due to the multiphysics nature of their failure processes. Integrating the interplay between thermodynamics and damage into ductile fracture models is vital for predicting critical failure modes. Here, in this paper, we develop a versatile phase-field (PF) framework for modeling ductile fracture, taking into account finite-strain elasto-plasticity. The framework stems from a variational formulation of constitutive relations for generalized standard materials (GSMs), whose response is described by a Helmholtz free energy and a dissipation pseudo-potential. Its variational structure is based on a minimum principle for a functional that expresses the sum of power densities for reversible and irreversible processes. By minimizing this functional with a constraint on a von Mises yield function, we derive the evolution equation for the equivalent plastic strain and an associative flow rule. This constrained optimization problem is analytically solved for a wide class of thermo-viscoplasticity models. The key innovations of the current work include (i) a cubic plastic degradation function that accounts for a non-vanishing damage-dependent yield stress, (ii) closed-form expressions of the Helmholtz free energy and dissipation pseudo-potential for three thermo-viscoplasticity models, (iii) an extended Johnson–Cook plasticity model with a nonlinear hardening law, and (iv) a plastic work heat source that depends on the plastic degradation function and a variable Taylor–Quinney (TQ) coefficient. The capabilities of the proposed framework are tested with the aid of four ductile fracture problems, including the Sandia Fracture Challenge. In each of these problems, we examine the evolution of relevant field variables such as the PF order parameter, the equivalent plastic strain, the temperature, and the internal power dissipation density, in addition to the overall structural response quantified by the force–displacement curve. These numerical studies demonstrate that the proposed framework effectively represents ductile fracture, yielding computational results that exhibit good agreement with experimental data.

36 MATERIALS SCIENCE↗