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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effect of Extended Aging and Oxidation on Linear Poly(propylenimine)-Mesoporous Silica Composites for CO 2 Capture from Simulated Air and Flue Gas Streams

Physical aging or degradation of amine-containing polymers and supported amine adsorbents is a critical issue that could limit practical application of such materials for CO 2 capture. However, to date, there is a scarcity of studies that evaluate the long-term stability of amine-based sorbents without the exclusive use of accelerated aging tests. Here, we demonstrate that extended aging (~2 years) of linear poly(propylenimine) (LPPI) confined in mesoporous silica (SBA-15) supports does not drastically impact the CO 2 adsorption performance under simulated flue gas (10% CO 2 ) and direct air capture (DAC, 400 ppm CO 2 ) conditions, although the behavior of the aged sorbents and polymers in the two CO 2 concentration regimes differs. Sorbents made with aged LPPI had modestly decreased CO 2 uptake performance (<~20% lower) compared to the fresh polymers, with overall good CO 2 cycling performance. The data indicate that only slow degradation occurs under the deployed ambient storage conditions. Even after extended aging, the LPPI-based sorbents preserved their ability to display stable temperature-swing cycling performance. In parallel, the impact of blending LPPI polymers of different number-average molecular weights, M n , is evaluated, seeking to understand its impact on adsorbent performance. We find that the results demonstrate that blends of two M n aged LPPI give similar CO 2 adsorption performance to adsorbents made from a single M n LPPI, suggesting that molecular weight will not negatively impact adsorbent performance in the studied M n range. After an accelerated oxidation experiment, the aged LPPI sorbents retained a larger portion of the samples’ original performance when cycling under simulated flue gas conditions than under DAC conditions. However, in each case, the oxidized sorbents could be cycled repeatedly with consistent uptake performance. Overall, these first of their kind extended aging tests suggest that LPPI-based amine adsorbents offer promise for long term, stable use in carbon capture applications.

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

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
DOE OSTI2023

Machining of Alloy 709 Creep-fatigue Specimens from G. O. Carlson Heat

Alloy 709 has been selected as the next candidate material for Section III, Division 5 qualification in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC) for elevated-temperature nuclear construction. The qualification data package requires an assortment of information and material data including tensile, creep, and creep-fatigue performance at elevated temperatures from different material heats. The goal of the project is to generate a dataset to support qualification of Alloy 709 material for ASME BPVC design code. Working towards the project goal, Idaho National Laboratory needs to conduct a series of tests on three different heats to support the A709 code case development. At present, there is a gap in the data package for one of the heats: Heat number 58776 manufactured by G.O. Carlson. To address this data gap, Argonne National Laboratory transmitted five plates of A709 heat 58776 manufactured by G.O. Carlson to Idaho National Laboratory. These plates were solution annealed at 1150°C and heat treated at 775°C for 10 hours. The objective of this specification is to procure a series of creep-fatigue specimens to support the qualification data package. The creep-fatigue specimen design captures the cyclic material performance at elevated temperature. The material performance data generated from specimens machined herein will support the ASME BPVC code case development and establish design limits, and design life curves for Alloy 709 material.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Initial Engineering and Design for CO 2 Capture from Ethanol Facilities

The Energy & Environmental Research Center, in partnership with the U.S. Department of Energy (DOE) and North Dakota ethanol producer Red Trail Energy, LLC (RTE) and with technical support from Trimeric Corporation and the KLJ engineering firm, completed an initial engineering design (IED) for a hybrid capture system to estimate associated costs for retrofitting the operational RTE ethanol plant. The project goal supports the DOE objective to achieve negative emissions using commercially available technologies to attain Technology Readiness Level 6+ from a facility emitting >100,000 tonnes of carbon dioxide (CO 2 ) annually. The RTE CCS (carbon capture and storage) Project is currently operating a CO 2 capture facility, adjacent to the RTE ethanol facility in western North Dakota, and injecting the CO 2 more than a mile below RTE property for permanent storage. This novel hybrid capture system would process about 310,000 tonnes of CO 2 annually for the RTE host site and includes CO 2 capture and compression from bioprocessing as well as capturing CO 2 produced from natural gas boilers. The bioprocessing capture process, based on past RTE studies investigating ammonia liquefaction technology with CO 2 produced from natural gas boilers captured utilizing chemical absorption with amine, was shown to be technically feasible for the RTE site. Activities conducted to support the project goal included 1) designing a hybrid capture system using CO 2 emissions from both bioprocessing and heat production at the host site facility; 2) conducting a pre-front-end engineering and design analysis of the hybrid capture system to include environmental health and safety, a constructability report, identification of permits, and corporate approvals; and 3) performing a techno-economic assessment in accordance with DOE’s methodology, as demonstrated by the bituminous baseline study. In addition, a life cycle assessment (LCA) was completed for the RTE site to estimate the carbon life cycle for ethanol-CCS implementation using the designed hybrid capture system to determine potential for net-negative carbon emissions. Results of the IED showed the hybrid system to be technically viable, with a moderate estimated cost of $55/tonne CO 2 captured for the hybrid system. The cradle-to-gate LCA showed preliminary net-negative carbon emissions potential anticipated from implementing a hybrid CCS system at a commercial scale. Recommended next steps toward potential implementation include hybrid capture system demonstration testing for detailed engineering and LCA model comparisons with low-carbon fuel incentive programs for financial support.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Capturing many-body correlation effects with quantum and classical computing

Theoretical descriptions of excited states of molecular systems in high-energy regimes are crucial for supporting and driving many experimental efforts at light source facilities. However, capturing their complicated correlation effects requires formalisms that provide a hierarchical infrastructure of approximations. These approximations lead to an increased overhead in classical computing methods and, therefore, decisions regarding the ranking of approximations and the quality of results must be made on purely numerical grounds. The emergence of quantum computing methods has the potential to change this situation. Here, in this study, we demonstrate the efficiency of the quantum phase estimator (QPE) in identifying core-level states relevant to x-ray photoelectron spectroscopy. We compare and validate the QPE predictions with exact diagonalization and real-time equation-of-motion coupled-cluster formulations, which are some of the most accurate methods for states dominated by collective correlation effects.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Development of a kinetic model to describe six types of symbiotic interactions in a formate utilizing microalgae-bacteria cultivation system

This study investigated an algae/formate-utilizing-bacteria system that has been developed for carbon capture. This photomixotrophic consortium consumed formate to support bacterial growth so that the resulting respiration CO 2 could be simultaneously used by algae to avoid CO 2 gas-lipid mass transfer limitation. To understand biomass growth and population interactions in this unique system, a kinetic model has been developed to describe algae and bacteria multiplication, formate and nitrogen utilizations, CO 2 mass transfer, O 2 generation and consumption, lighting condition and shading effect. The simulation indicated that this ecosystem could form six types of interactions (mutualism, commensalism, parasitism, neutralism, amensalism, and competition) depending on the light intensity and nutrient availability. Furthermore, the simulation of both batch culture and chemostat, along with parameter sensitivity tests and experimental observations, offered insights into optimal applications of algae-bacteria consortium based photobiorefinery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures

Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures of multi-protein complexes and other macromolecular machines. A standalone prototype data resource for integrative structures called PDB-Dev was built, based on recommendations of the Integrative and Hybrid Methods (IHM) Task Force of the Worldwide Protein Data Bank (wwPDB). This effort included developing data standards and software tools for collecting, curating, validating, visualizing, archiving, and disseminating integrative structures that span diverse spatiotemporal scales and conformational states. Mechanisms have been created to validate integrative structures based on the experimental data underpinning them. Building upon this foundational framework, PDB-Dev has been further expanded to handle large dynamic macromolecular systems and integrative structures that combine, for example, experimental restraints with atomic coordinates computed by machine learning algorithms. Data standards and supporting tools have also been extended to capture information about biomolecular dynamics, such as conformational transitions and related kinetic data derived from biophysical methods. Recently, PDB-Dev was unified with the PDB archive and rebranded as PDB-IHM (pdb-ihm.org), further promoting FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data stewardship for integrative structural biology.

IHMCIF↗
DOE OSTI2024

Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability

As global change processes modify the extent and functions of terrestrial-aquatic interfaces, the variability of critical and dynamic transitional zones between wetlands and uplands increases. However, it is still unclear how fluctuating water levels at these dynamic boundaries alter groundwater biogeochemical cycling. Here, we used high-temporal resolution data along gradients from wetlands to uplands and during fluctuating water levels at freshwater coastal areas to capture spatiotemporal patterns of groundwater redox potential (E h ). We observed that topography influences groundwater E h that is higher in uplands than wetlands; however, the high variability within TAI zones challenged the establishment of distinct redox zonation. Declining water levels generally decreased E h , but most locations exhibited significant E h variability, which is associated with rare instances of short-term water level fluctuations introducing oxygen. The E h -oxygen relationship showed distinct hysteresis patterns, reflecting redox poising capacity at higher E h , maintaining more oxidizing states longer than dissolved oxygen presence. Surprisingly, we observed more frequent oxidizing states in transitional areas and wetlands than in uplands. We infer that occasional oxygen entering specific wetland-upland boundaries acts as critical biogeochemical control points. Finally, high-resolution data can capture such rare yet significant biogeochemical instances, supporting redox-informed models and advancing the predictability of climate change feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Designing an innovation system to support profitable electro- and bio-catalytic carbon upgrade

Carbon capture, utilisation, and storage (CCUS) can mitigate an estimated 14–20% of CO 2 emissions by 2050. Here, we evaluate an integrated electrocatalysis and biocatalysis CCUS pathway, using externally-supplied renewable electricity to convert over 12 MtCO 2 to poly(3-hydroxybutyrate) via methanol and formate intermediates. A techno-economic and policy-innovation analysis provides insight into global CCUS innovation. Results suggest that innovation should focus on improving methanol faradaic efficiency, formate biocatalysis efficiency, electrocatalysis current density, and catalyst performance. Methanol and formate composition influences performance, but higher formate content can improve economics by US$3.8B over a 30 year lifetime. Profitable scenarios hinge on reducing methanol separation costs – through innovation or reduced energy usage – along with cheap renewable electricity and/or carbon pricing. Our evaluation of the global innovation status signifies that coordinated strategies are required to realise emissions cuts from CCUS. Innovation can be spurred by targeted investments and policies that promote emissions reductions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Adsorption of Radioactive Iodine Using Nanocarbon on ETS-10 as Adsorbent

Here, laboratory-synthesized nanocarbon pelletized with titanosilicate (ETS-10) as a support matrix has been investigated for the capture of radioactive iodine present as methyl iodide (CH 3 I) in the off-gas streams produced during aqueous reprocessing of used nuclear fuel. The mass fraction of carbon in the sorbent matrix was 0.10. The effects of residence time and CH 3 I concentration were investigated using a continuous flow column setup to quantify the adsorption and desorption capacities of adsorbent under dynamic conditions from an air stream containing CH 3 I present at concentrations representative of those expected in the off-gas streams. Air with CH 3 I gas as a source in the column resulted in quantifiable CH 3 I adsorption with 0.98 mg/g of adsorption capacity. Laboratory-made nanocarbons had a larger adsorption capacity than those of the other carbons reported in the literature. Additionally, the adsorption capacity of nanocarbon on ETS-10 is compared to that of nanocarbon coated on cordierite in previous studies.

ETS-10↗
DOE OSTI2025

Coupled Induction Machine and HVAC Models for Simulating HVAC Performance Considering Grid Dynamics in Buildings

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R 2 ) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Synchronization of Alternative Models in a Supermodel and the Learning of Critical Behavior

“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, interscale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the midlatitudes and a pair of ECHAM5 models of the tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with intermodel connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. In conclusion, for supermodels of both types, power spectra indicate enhanced interscale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Chemical Analysis of the Brightest Star of the Cetus II Ultrafaint Dwarf Galaxy Candidate*

We present a detailed chemical abundance analysis of the brightest star in the ultrafaint dwarf (UFD) galaxy candidate Cetus II from high-resolution Magellan/MIKE spectra. For this star, DES J011740.53-173053, abundances or upper limits of 18 elements from carbon to europium are derived. Its chemical abundances generally follow those of other UFD galaxy stars, with a slight enhancement of the α-elements (Mg, Si, and Ca) and low neutron-capture element (Sr, Ba, and Eu) abundances supporting the classification of Cetus II as a likely UFD. The star exhibits lower Sc, Ti, and V abundances than Milky Way (MW) halo stars with similar metallicity. This signature is consistent with yields from a supernova originating from a star with a mass of ∼11.2 M$_{⊙}$. In addition, the star has a potassium abundance of [K/Fe] = 0.81, which is somewhat higher than the K abundances of MW halo stars with similar metallicity, a signature that is also present in a number of UFD galaxies. A comparison including globular clusters and stellar stream stars suggests that high K is a specific characteristic of some UFD galaxy stars and can thus be used to help classify objects as UFD galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Storage Futures Study - Distributed Solar and Storage Outlook: Methodology and Scenarios

This presentation discusses the fourth report in NREL’s Storage Futures Study (SFS) publications. The SFS is a multiyear research project that explores the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. This report describes the expanded capabilities of the Distributed Generation Market Demand (dGen) model to analyze the economics of distributed (behind-the-meter) PV paired with battery storage systems and presents projections of adoption for the contiguous United States out to 2050 under a range of scenarios. These scenarios use technology cost and performance assumptions consistent with the National Renewable Energy Laboratory’s 2020 Standard Scenarios paired with updated battery cost projections and existing policies. Additional scenarios evaluate sensitivities to the value of backup power and DER compensation mechanisms, collectively characterizing the future potential for behind-the-meter storage and identifying key drivers of adoption. Adoption projections of DER and battery storage at high spatial and temporal resolution, as presented in this report, can enable informed planning of technical infrastructure that can help planners capture the benefits and mitigate challenges to support the ongoing trend toward distributed electricity generation.

backup power↗
DOE OSTI2025

Critical Component/Technology Gap in 21 st Century Power Plant Gasification Based Polygeneration: Advanced Ceramic Membranes/Modules for Ultra Efficient Hydrogen (H 2 ) Production/Carbon Dioxide (CO 2 ) Capture for Coal-Based Polygeneration

The 21 st Century Power Plant Gasification Based Polygeneration power plant layout is a relatively straightforward retrofit of well-established ammonia synthesis technology to the baseline IGCC process and envisions co-production of power and chemicals from coal in the context of carbon capture. A Dual Stage Membrane Process (DSMP) for pre-combustion CO 2 capture in a coal fired IGCC power plant has been demonstrated by Media and Process Technology Inc (MPT) (DE-FE0013064) in bench-scale live gas testing at the NCCC. This work, however, highlighted the importance of permeate purge capability to deliver deep H 2 recovery at moderate pressures and high carbon capture performance. Further, in the area of warm gas processing, a permeate purgeable membrane support for a wide range of inorganic high-performance membrane materials (CMS, Pd-alloy, zeolite, ZIF, graphene, etc.) was not available and hence had been a common and significant barrier to their commercialization. Hence, the Critical Technology Gap to implementing the DSMP in the Polygeneration power plant and more broadly in advanced warm gas separation applications was the inability to permeate purge the membranes coupled with the lack of the availability of a high packing density scalable package design. To overcome this Critical Technology Gap, in this project, the primary objective was the development of a permeate purgeable full ceramic support for these high-performance inorganic membranes and the complementary high packing density housing. Our goal and approach were to extend our “candle filter” design to a “dual end open” package to enable permeate purge and scalability. Microporous ceramic membranes have been proven to be a low cost, stable material for high temperature applications under harsh environment. They are the leading support choice of researchers in advanced inorganic membrane development in applications such as pre-combustion CO 2 capture. The new 2nd Generation “dual end open” bundle developed in this project is a universal support for these existing and emerging inorganic membrane technologies that up to now have lacked a pathway out of the laboratory. The full ceramic permeate purgeable support represents a transformational technology and opens the door to commercialization of these advanced membrane materials in a wide array of mega scale commercial applications in gas (and liquid) processing under aggressive conditions not suited to conventional polymeric membranes.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Surface and Buried Thermal, and RGB Unexploded Ordnance Data Collection

This document provides a description of a data collection campaign of unexploded ordnance (UXOI) set. The dataset captures a controlled UAV imaging campaign designed to support detection of UXO across varied environmental conditions. Data were collected during three campaigns in Norris and Northeast Knoxville, Tennessee, using RGB, and thermal sensors mounted on Parrot UKR. In total, the dataset contains 9925 images, 26 full-motion video, and approximately 81.99 GB of data, collected across late spring/summer conditions, every hour during sunlight, and multiple surface contexts, including tall grass, short grass, gravel, as well as buried in sand, and other gravel mixtures. The collection was designed to capture thermal and visual variability relevant to UXO detection in agricultural land, bare earth, and subsurface. Review of the imagery showed that ordnance was most detectable during periods of changing solar input, especially approximately 10-60 minutes after sunrise, approximately 20-60 minutes after sunset, and 2-3 min after cloud cover interrupted prolonged solar heating. These conditions increased thermal contrast because many ordnance items retained or released heat differently than the surrounding vegetation and ground surface. This dataset provides a useful resource for developing and evaluating airborne UXO detection methods under realistic field conditions. All ordnance used in the study was inert, and thermal behavior may differ from that of live ordnance. In addition, variation in ordnance type, composition, and placement introduced differences in thermal response that should be considered when interpreting results.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Deformation, dislocation evolution and the non-Schmid effect in body-centered-cubic single- and polycrystal tantalum

A physically-informed continuum crystal plasticity model is presented to elucidate deformation mechanisms, dislocation evolution and the non-Schmid effect in body-centered-cubic (bcc) tantalum widely used as a key structural material for mechanical and thermal extremes. We show the unified structural modeling framework informed by mesoscopic dislocation dynamics simulations is capable of capturing salient features of the large inelastic behavior of tantalum at quasi-static (10 -3 s -1 ) to extreme strain rates (5000 s -1 ) and at low (77 K) to high temperatures (873 K) at both single- and polycrystal levels. Here we also present predictive capabilities of the model for microstructural evolution in the material. To this end, we investigate the effects of dislocation interactions on slip activities, instability and the non-Schmid behavior at the single crystal level. Furthermore, ex situ measurements on crystallographic texture evolution and dislocation density growth are carried out for polycrystal tantalum specimens at increasing strains. Numerical simulation results also support that the modeling framework is capable of capturing the main features of the polycrystal behavior over a wide range of strains, strain rates and temperatures. The theoretical, experimental and numerical results at both single- and polycrystal levels provide critical insight into the underlying physical pictures for micro- and macroscopic responses and their relations in this important class of refractory bcc materials undergoing large inelastic deformations.

36 MATERIALS SCIENCE↗