A molecular dynamics study on the Mie-Grüneisen equation-of-state and high strain-rate behavior of equiatomic CoCrFeMnNi
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36 MATERIALS SCIENCE↗
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Results for “behavioral sciences”
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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An Initial Exploration of Coupled Transient Mechanical and Electrochemical Behaviors in Lithium Ion Batteries
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Electrochemistry↗
BobGAT: Towards Inferring Software Bill of Behavior with Pre-Trained Graph Attention Networks
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Mathematics and Computing, Computer science, Infor↗
Computational thermodynamics and its applications
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.
36 MATERIALS SCIENCE↗
Isothermal and Cyclic Oxidation of Haynes 282 Processed by Electron Beam Melting (EBM) and Laser Powder Bed Fusion (LPBF) in Dry Air at 800 and 950°C
Here, the isothermal and cyclic oxidation behavior of Haynes 282 (H282) processed by laser powder bed fusion and electron beam melting was compared to its cast counterpart during exposures in air at 800 and 950°C. The specific microstructure of the AM alloys compared to coarse-grain cast 282 resulted in differences in oxidation rates, internal oxidation and spallation behavior. At 800°C, faster Ti diffusion to the surface due to the smaller grain size of the AM alloys led to Ti doping of the Cr 2 O 3 scale and faster oxidation rates. The higher density of grain boundaries also resulted in more pronounced internal oxidation. At 950°C, a duplex Cr 2 O 3 scale was observed with a dense inner layer and porous cracked outer layer with embedded TiO 2 particles. The impact of the external and internal oxide compositions and oxidation-induced elemental depletions on the oxidation lifetime, creep properties and spallation behavior is discussed.
36 MATERIALS SCIENCE↗
Influence of interfacial responses of Berea Sandstone in low-salinity waterflooding environments
Wetting conditions and fluid-fluid interfacial properties are essential to understanding oil recovery in the context of low-salinity and smart waterflooding. Many have deemed wettability alteration to be the dominant interaction, while some highlight the importance of fluid-fluid interactions. In some rock-fluid systems, benefits from the use of additives can arise to favor hydrocarbon production. Understanding the balance between the fluid-fluid and rock-fluid interactions when utilizing additives is crucial to evaluate benefits in improved efficiency. Ultimately, this understanding will shed light on recovery mechanisms. Regarding oil recovery, previous studies indicate that the injection of a naphthenic acid (NA) blend dissolved in an injection brine improves oil recovery in Berea Sandstone, particularly under low-salinity conditions. Interfacial rheology results for the brine-oil interface correlated well with the recovery response. This observation was speculated to serve as a potential improved recovery mechanism through oil-trapping suppression. However, the said studies did not evaluate potentially concurrent rock wettability alteration during recovery or the initial wetting condition. The purpose of this work is to determine the production behavior in systems with NAs, namely NA-10 (3-Cyclohexanepropinoic acid), NA-14 (Cyclopentane carboxylic acid), NA-18 (Cyclohexane carboxylic acid), and NA-mix (Naphthenic acid mixture), at different initial wetting conditions under spontaneous imbibition. In addition, we tested the NAs ability to alter wettability in Berea Sandstone and determine each “additive’s” capacity to improve recovery. Here, time-domain nuclear magnetic resonance (TD-NMR), contact angle, and Amott cell tests, i.e. spontaneous imbibition, were used to analyze the influence of the selected naphthenic acids on oil displacement under different initial wetting conditions. Our results indicate that individual naphthenic acids indeed have potential as additives in low-salinity waterflooding for oil-wet systems while negatively impacting recovery in water-wet systems. However, results suggest that the evolution of the interfacial properties and wettability conditions are equally important on the recovery behavior.
54 ENVIRONMENTAL SCIENCES↗
Unexpected Hydride: Ce 4 B 2 C 2 H 2.42 , a Stuffed Variant of the Nd 2 BC Structure Type
Ce 4 B 2 C 2 H 2.42 was grown as large crystals from a cerium/copper eutectic flux. The structure was characterized by single-crystal X-ray and neutron diffraction and was found to be a stuffed variant of Nd 2 BC with the addition of two interstitial hydrogen positions. The tetrahedral hydrogen position is fully occupied, while the octahedral position has an occupancy of 42(3)%. Initial synthesis was due to hydrogen contamination of the cerium metal but has been successfully repeated using anthracene as a carbon and hydrogen source. Density of states calculations suggest that the incorporation of hydrogen stabilizes the compound with respect to the nonhydrided model. Magnetic susceptibility data show a complex magnetic ordering at 7.7 K that originates from the localized electron on the Ce 3+ in the structure. The trivalent state is also supported by X-ray photoelectron spectroscopy measurements. Heat capacity and electrical resistivity data show that the phase transition is broad in temperature, which may be due to structural disorder. Furthermore, the large low temperature value of C/T also indicates possible heavy fermion behavior.
36 MATERIALS SCIENCE↗
Rheology of bacterial superfluids in viscous environments
Dense suspensions of pusher-type bacteria give rise to 'superfluids' in which the effective viscosity of the suspension is drastically reduced through collective motion, and in this study we investigate how a viscous environment affects this behavior.
54 ENVIRONMENTAL SCIENCES↗
Cleavable magnetic materials from van der Waals layered transition metal halides and chalcogenides
The study of exfoliated 2D magnetic materials is a vibrant and rapidly progressing field and is impacting many areas of condensed matter research including fundamental magnetism, spintronics and optoelectronics, and topological spin and electronic systems. The availability of promising candidate materials has enabled much of the progress in this field. Here, I present my perspective on the development of cleavable magnetic materials with a focus on transition metal halides and chalcogenides and an emphasis on crystal structure and magnetic order. To give proper context for these discussions, brief and incomplete surveys of recent work are included, focusing on specific aspects that I find most useful for guiding work on emerging materials and motivating expansion into other compounds and material families. Several instances of structural changes that can differentiate behaviors of bulk and ultrathin specimens are noted. Probing and understanding potential structural differences present a challenge but also an opportunity for material and device development, if they can be predicted and controlled. It is clear that careful investigations of structure, layer stacking, and defects in materials, how they may relate to the crystal chemistry, and how they may be different in crystals and mono- or few-layer specimens provide invaluable context for understanding the behavior of van der Waals layered magnetic materials.
36 MATERIALS SCIENCE↗
Understanding the Effect of Electrochemical Properties and Microstructure on the Microgalvanic Corrosion of Mg Alloys via Phase-Field Simulations
In this work, we apply a phase-field model to gain insights into the corrosion behavior of Mg alloys. Specifically, we study the effect of electrochemical properties of the materials and their environment and the spatial distribution of second phases in a magnesium alloy. To this end, we perform sensitivity analyses in which we separately vary the exchange current density and corrosion potential of the second phase, as well as the electrolyte conductivity. We describe the effects of these parameters on the corrosion current and the resulting corrosion-front morphology. We also confirm that the ratio between the Wagner length, calculated for the anodic phase, and the initial width of the anodic domain is a good predictor of the morphological characteristic of the corroding surface. In addition, we examine the effect of the microstructure on the corrosion behavior in both 2D and 3D systems by varying the shape, size, and distribution of the second-phase regions. Our findings provide insights into the influence of the two-phase microstructure on the corrosion behavior in a magnesium alloy.
Electrochemistry↗
A directional microcrack damage theory for brittle solids based on continuous hyperplasticity
We present a novel microcrack-damage theory for brittle solids under compression. Instead of using internal variables like zeroth, second or fourth rank damage tensors, the state of material damage is represented by an internal function that encapsulates the information of direction, density and size of microcracks. Just like other internal variables, the evolution of this state function must obey the second law of thermodynamics for arbitrary loading paths. This is done by casting the model in the framework of continuous hyperplasticity and enforcing a non-negative dissipation rate functional. The proposed framework offers predictions on the continuous evolution of microcrack density and the induced material anisotropy along with the macroscopic stress-strain curves. The use of continuous damage function grants the model significantly enhanced resolution in characterizing the direction-dependent response of cracked solids compared to classical models that are based on damage tensors. Two scenarios are considered in developing the theory, one assumes frictionless cracks and the other incorporates friction between crack surfaces. The results highlight that inelasticity, pressure dependence, and loading-unloading hysteresis exhibited by brittle solids are natural consequences of frictional microcracks. The proposed theory offers a generic and versatile framework to upscale micromechanical processes operating at individual crack scale to explain the macroscopic behavior of cracked solids.
Materials Science↗
Benchmarking Microscale Ductility Measurements (Final Report of the Project DE-NE0008799)
Conventional macroscale experimentation is generally considered to be straightforward with few limitations. Conversely, micro/nanoscale experimentation presents numerous challenges in loading device design, sample preparation and handling, as well as accurate understanding of grain size and local texture effects on recorded measurements. Despite these challenges, nanopillar compression, MEMs based micro-tension, and nanoindentation approaches have been able to provide fundamental contributions to the understanding of material behavior at small lengthscales. However, the overarching shortcoming of these micro/nanoscale experimentation approaches, is the inability to directly translate measurements evaluated at the nm and µm length scales (e.g., hardness) to macroscale tensile material behavior (i.e., elastic modulus, yield strength, and ductility). The objectives of the proposed study are, 1) to establish best practices for obtaining tensile microscale ductility measurements, and 2) to validate methodologies to for comparing microscale ductility measurements to macroscale ductility measurements. In order to achieve these objectives, a multi-lengthscale, multi-temperature testing protocol and simulation framework are executed first on copper as a model material to validate the following approach, and second on reactor grade Zircaloy-2. Experiments are conducted on specimens extracted from the same test piece to ensure nominally identical grain size and texture from specimens to specimen. Motivated by the need to isolate the contribution of size-effects on obtained mechanical property measurements, specimens are manufactured with thicknesses at the micro- (1-10 µm), meso- (10-100's µm), and macroscales (sub-sized ASTM E8). In-situ full-field deformation techniques (scanning electron microscopy (SEM) grid methods and optical DIC) are incorporated into testing at each specimen length-scale to capture plasticity localization and evolution. Experimental testing for all specimens is conducted at both room temperature and elevated temperatures to probe the role of thermal activation on plastic deformation accommodation processes. Simulation efforts focus on examining the mechanical behavior of microscale specimens using a finite element approach with explicitly resolved grain morphologies, and an embedded crystal plasticity model. The cost-efficient implementation method allows for the modeling of a statistically significant number of both real (i.e., digital twin) and generated microstructures to obtain an understanding of the interrelationships between specimen microstructure and geometric variables (grain size, texture, specimen geometry, etc.) on microscale mechanical behavior.
36 MATERIALS SCIENCE↗
Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science
Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior due to drifts in the data. The drifts can arise from both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with non-stationary data streams.Online learning can be used to continuously adapt the models with new data as it is acquired. However, traditional online learning can suffer from short-term performance degradation, as ground truth are not available before making the prediction. To address this challenge, we propose uncertainty aware ensemble approach for online learning. We use Deep Gaussian Process Approximation (DGPA) technique for calibrated uncertainty estimation and use the uncertainty values to guide a meta-algorithm that produces predictions based on ensemble of learners. Moreover, DGPA also provides uncertainty estimation along with the predictions for decision makers. This paper demonstrates that the proposed method outperforms traditional online learning approach, and a naive ensemble without uncertainty guidance by about 7% and 6%, respectively, on B-coil deflection prediction at DIII-D Fusion Facility.
Rajput, Kishansingh [Thomas Jefferson National Acc↗
Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science
Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior due to drifts in the data. The drifts can arise from both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with non-stationary data streams.Online learning can be used to continuously adapt the models with new data as it is acquired. However, traditional online learning can suffer from short-term performance degradation, as ground truth are not available before making the prediction. To address this challenge, we propose uncertainty aware ensemble approach for online learning. We use Deep Gaussian Process Approximation (DGPA) technique for calibrated uncertainty estimation and use the uncertainty values to guide a meta-algorithm that produces predictions based on ensemble of learners. Moreover, DGPA also provides uncertainty estimation along with the predictions for decision makers. This paper demonstrates that the proposed method outperforms traditional online learning approach, and a naive ensemble without uncertainty guidance by about 7% and 6%, respectively, on B-coil deflection prediction at DIII-D Fusion Facility.
Rajput, Kishansingh [Thomas Jefferson National Acc↗
ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling
Traditional entropy-based methods—such as cross-entropy loss in classification problems—have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence algorithms. However, the rapid growth of data across various domains has introduced new challenges, particularly the integration of heterogeneous datasets with intrinsic disparities. To address this, we introduce a zentropy-enhanced neural network (ZENN), extending zentropy theory into the data science domain via intrinsic entropy, enabling more effective learning from heterogeneous data sources. ZENN simultaneously learns both energy and intrinsic entropy components, capturing the underlying structure of multisource data. To support this, we redesign the neural network architecture to better reflect the intrinsic properties and variability inherent in diverse datasets. We demonstrate the effectiveness of ZENN on classification tasks and energy landscape reconstructions, showing its superior generalization capabilities and robustness-particularly in predicting high-order derivatives. In image and text classification tasks, ZENN demonstrates superior generalization by introducing a learnable temperature variable that models latent multisource heterogeneity, allowing it to surpass state-of-the-art models on CIFAR-10/100, BBC News, and AG News. As a practical application in materials science, we employ ZENN to reconstruct the Helmholtz energy landscape of Fe3Pt using data generated from density functional theory and capture key material behaviors, including negative thermal expansion and the critical point in the temperature–pressure space. Overall, this work presents a zentropy-grounded framework for data-driven machine learning, positioning ZENN as a versatile and robust approach for scientific problems involving complex, heterogeneous datasets.
36 MATERIALS SCIENCE↗
Structural stability of mechanically alloyed amorphous (FeCoNi) 70 Ti 10 B 20 under high-temperature and high-pressure
Nanostructured (FeCoNi) 70 Ti 10 B 20 (at%) alloy was synthesized by mechanical alloying from elemental powder mixture of Fe, Co, Ni, Ti and B using ball milling. The effect of ball milling time on the evolution of structure and morphology was investigated by X-ray diffraction, scanning and transmission electron microscopy and differential thermal analysis. It was observed that the formation of solid solution of (FeCoNi) 70 Ti 10 B 20 started from the very onset of the milling process. Crystallite size and lattice strains seemed to be leveled off after 20 h of milling with no further major changes. The milling process for longer periods introduced severe plastic deformations causing formation of amorphous phase of (FeCoNi) 70 Ti 10 B 20 . The amorphous alloy composition was confirmed by energy dispersive X-ray spectroscopy analysis that showed an excellent homogeneity of the alloying elements. The phase stability of the mechanically alloyed amorphous sample was further verified by employing high-temperature and high-pressure studies. The alloy samples heat-treated at 700 °C revealed crystallization of the amorphous phase. However, synchrotron-based high-pressure ambient temperature X-ray diffraction studies confirmed that the amorphous phase of the alloy remained stable up to the pressure of 30 GPa. Here, the 50 h milled sample after being annealed at 350 °C showed improvement in the soft magnetic properties of the alloy, which was due to the probable elimination of the residual stress in the amorphous phase of the alloy powders.
36 MATERIALS SCIENCE↗
High temperature tensile properties of H13 tool steel fabricated via binder jet additive manufacturing
H13 is one of the most used steels for hot work tooling applications like die casting. Binder jet additive manufacturing (BJAM) offers a cost-effective solution to fabricate tools with performance enhancing features like internal cooling channels. While full densification of BJAM H13 has been demonstrated in the literature, the room and high temperature tensile properties of the material, and the effect of post-process treatments like hot isostatic pressing (HIP), and heat treatment (HT) are unknown. Here we use HIP+HT to obtain a combination of ultimate tensile strength (UTS) and elongation to failure that is superior to H13 fabricated via laser powder bed fusion and wire arc additive manufacturing. HIP+HT BJAM H13 has a superior UTS (1836 MPa) compared with conventionally processed (1671 MPa) H13 but has lower plastic elongation. We report that as-sintered samples have an extensive network of continuous grain boundary (GB) carbides that contribute to brittle fracture. HIP+HT results in partial dissolution of GB carbides and formation of a fine martensitic microstructure resulting in superior tensile strength and elongation compared with as-sintered H13. We use thermo-kinetic calculations to rationalize the effects of HIP+HT on microstructure and properties.
36 MATERIALS SCIENCE↗
A systematic review of building energy sufficiency towards energy and climate targets
Among the sufficiency, efficiency, and renewable frameworks for reducing energy use and energy-related carbon emissions, Building Energy Sufficiency (BES) is gaining attention from policy makers and engineers. Despite the significant role of the building sector in the success of national energy and climate plans, there is a lack of research on the drivers, technologies, and effective policy instruments required to achieve BES in the building operational phase. To fill this gap, this study presents a systematic review of the definition and paradigm of BES and concludes that BES should address both occupant demand and energy or emissions requirements simultaneously. The characteristics of occupant demand in building services are divided into four dimensions: time and space, quality and quantity, control and adjustment, and flexibility. Technical options regarding the building architecture, the envelope system, and the building energy system are reviewed. Finally, policy implications and recommendations are discussed. As a result, the multiple benefits and multidisciplinary nature of BES justify further research and accelerated policy implementation in developed and developing countries.
54 ENVIRONMENTAL SCIENCES↗