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DOE OSTI2021

In-situ magnetic alignment model for additive manufacturing of anisotropic bonded magnets

In this work, we report a mathematical framework which predicts the degree of alignment (DoA) in an in-situ aligned additively manufactured 3D printed bonded magnets. A multiphysics model is developed which couples the harmonious interactions of magnetic particles in a viscous flowing polymer under the presence of an external magnetic field. The hydrodynamic fluid-particle interaction is paired with the magnetophoretic force to predict the particle trajectory and distribution during extrusion through a 3D printer nozzle. Succeeding the force balance, a magnetohydrodynamic torque equilibrium analysis is performed to predict the net-orientation of the magnetic particles as a function of the applied field strength, viscous forces, and particle-to-particle interactions (P2P). Experimental validation of the DoA predictions is performed using 65 vol% Nd-Fe-B+Sm-Fe-N in Nylon12 (DoA exp = 0.620 and DoA theory = 0.686) and 15 vol% Sm-Co in PLA (DoA exp = 0.830 and DoA theory = 0.863). A parametric analysis is performed to analyze the effect of operating and design parameters like alignment field strength, magnetic loading fraction, extrusion load, and particle size. The model predicts a competing behavior between particle-fluid and particle-particle interactions under the presence of an applied field. Lastly, the model provides a framework to efficiently predict the DoA in tandem with a functionalized-magnetic 3D printer and allows the user to adjust the operating parameters according to the desired DoA.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Conformational Domain Wall Switch

Domain walls in ferroelectric materials have tantalizing potential in disruptive memory and reconfigurable nanoelectronics technologies. Here, a ferroelectric domain wall switch with three distinct addressable resistance states is demonstrated. The device operation hinges on fully controllable and reversible conformational changes of the domain wall. As validated by atomistic simulations consistent with the experiments, using electric field, the shape—and hence the charge state—of the domain wall and ultimately its conduction are altered. Sequential nanoscale transitions of the walls are visualized directly using stroboscopic-piezoresponse force microscopy and Kelvin probe microscopy. In this work, anisotropic head-to-head domain wall injection, stabilized by the majority carrier type of the ferroelectric, BiFeO 3 , is identified as the key factor that enables conformational control.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Interlaboratory Reproducibility of Contour Method Data in a High Strength Aluminum Alloy

The contour method for residual stress measurement has seen significant development, but an experimental reproducibility study utilizing physical samples has not been published. A double-blind reproducibly study is reported, having scope beginning with EDM cutting and ending with residual stress calculation. A reinforced I-beam sample geometry is identified for its unique residual stress profile when extracted from residual stress bearing quenched aluminum bar (7050-T74). Contour measurements are prescribed on a midplane of symmetry with dimensions 24.0 mm by 50.0 mm. Fourteen identically prepared samples are fabricated from a single long bar with well characterized and uniform residual stress. Five samples throughout the bar are identified for planning measurements to validate sample uniformity and overall suitability of the residual stress field. The planning measurements employ a range of techniques: contour method, neutron diffraction, and hole-drilling. Eight samples are distributed to an international group of participants to execute their standard measurement practice. A double-blind process is followed to provide anonymity. Results are provided by eight participants: six being self-similar and two being quite different, the latter set aside as outliers. An average residual stress field is established from non-outlying results and the spatial distribution of reproducibility standard deviation is determined. The average stress field ranges from -60 to 70 MPa and the reproducibility standard deviation averages 8.1 MPa on the measurement plane. The average reproducibility standard deviation is about 3 × larger for points within 1.0 mm of plane boundaries (17.6 MPa) than for the remaining points (6.1 MPa). Reproducibility standard deviation (among different labs) for contour method residual stress measurement is found to be very similar to repeatability standard deviation (in a single lab) reported in prior work. The reproducibility observed here, for the entire measurement process, is also similar to that found in a prior reproducibility study limited to contour method data analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Understanding poromechanical response of a biogenic coalbed methane reservoir

Abstract Biogenic coalbed methane (BCBM) reservoirs aim to produce methane from in situ coal deposits following microbial conversion of coal. Success of BCBM reservoirs requires economic methane production within an acceptable timeframe. The work reported here quantifies the findings of previously published qualitative work, where it was found that bioconversion induces strains in the pore, matrix and bulk scales. Using imaging and dynamic strain monitoring techniques, the bioconversion induced strain is quantified here. To understand the effect of these strains from a reservoir geomechanics perspective, a corresponding poromechanical model is developed. Furthermore, findings of imaging experiments are validated using core-flooding flow experiments. Finally, expected field-scale behavior of the permeability response of a BCBM operation is modeled and analyzed. The results of the study indicated that, for Illinois coals, bioconversion induced strains result in a decrease in fracture porosity, resulting in a detrimental permeability drop in excess of 60% during bioconversion, which festers itself exponentially throughout its producing life. Results indicate that reservoirs with high initial permeability that will support higher Darcian flowrates, would be better suited for coal bioconversion, thereby providing a site-selection criteria for BCBM operations.

Pandey, Rohit (ORCID:0009000415483436)↗

DOE OSTI2025

Informed unsupervised machine learning analysis of dislocation microstructure from high-resolution differential aperture X-ray structural microscopy data

This study leverages high-resolution differential-aperture X-ray structural microscopy (DAXM) to probe the local dislocation structure in deformed 304L-stainless steel at small strain, by measuring the lattice rotation and deviatoric elastic strain with a sub-micron resolution. For a single grain in a polycrystalline specimen, the measured lattice rotation field over the measured volume exhibited a multimodal distribution while the deviatoric elastic strain showed a single-mode distribution. An unsupervised Cauchy mixture machine learning model was developed to resolve the multimodal distribution of the lattice rotation. By mapping the lattice rotation data associated with each Cauchy peak in the model back onto the measured volume, we identify contiguous regions of the crystal rotated near the average values corresponding to the peaks of the overall rotation distribution. These regions represent the grain subdivision in the microstructure. Finally, the dislocation density tensor was also computed and its norm was laid over the rotation field to detect the subgrain boundaries. This step provided a validation of the Cauchy mixture model for the analysis of the lattice rotation distribution. The current study highlights the integration of advanced X-ray microscopy techniques with data-driven analysis methods to uncover detailed microstructure scales in deformed crystals.

Machine learning; Lattice rotation; High-energy X-↗

DOE OSTI2022

A better understanding of the mechanics of borehole breakout utilizing a finite strain gradient-enhanced micropolar continuum model

Borehole breakout denotes the failure in rock mass subjected to drilling, caused by stress concentrations exceeding the material strength. Depending on the material properties, the preexisting in situ stress state, and the borehole dimensions, different types of borehole breakout, such as spiral-shaped breakout or v-shaped breakout, are distinguished in the literature. In the present work, we address the influence of the material properties on the predicted borehole breakout mode in a comprehensive finite element study. To this end, herein we employ a gradient-enhanced micropolar damage-plasticity model based on the Mohr–Coulomb strength criterion, formulated in the finite strain regime, which is calibrated based on experimental results from plane strain compression tests on Red Wildmoor sandstone. In the numerical study, the influence of the in situ stress state, the material friction angle, plastic dilation, post peak residual strength, and the inherent material length scale parameters are investigated. Thereby, we demonstrate that depending on the material parameters, substantially different failure modes, characterized by strongly localized shear bands or diffuse failure zones, are predicted. It is shown that in particular the brittleness of the material in the post peak regime has a major influence on the predicted breakout type. Moreover, a statistical validation of the results is obtained by considering different random field distributions of the initial material strength.

58 GEOSCIENCES↗

DOE OSTI2021

State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities to monitor the system dynamic performance in real-time at fast time scales. The use of such technologies has unlocked new opportunities to introduce new data driven algorithms for improving the stability assessment and control of the system. Motivated by these challenges, a group of experts have worked together to highlight and establish a baseline set of these common concerns, which can be used as motivation to propose innovative analytics and data-driven solutions. In this document, the results of a survey on 10 transmission system operators around the world are presented and it aims to understand the current practices of the participating companies, in terms of data acquisition, handling, storage, modelling and analytics. The overall objective of this document is to capture the actual needs from the interviewed utilities, thereby laying the groundwork for setting valid assumptions for the development of advanced algorithms in this field.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

An overview of the first principles studies of doped RE-TM5 systems for the development of hard magnetic properties

In this study, we compiled all the first principles calculations performed on RE-TM 5 (RE: rare earth, TM: transition metal) system to address the following question: Has everything been tried to improve the hard magnetic properties of this special intermetallic compound, and are there any venues that are worth pursuing? As it is the case with the first principles studies in any field, they are driven mainly by experimental work: (i) to validate their results, and (ii) to extend our understanding of the underlying physical phenomena so that the theory in hand can be used as a predictive tool to shed light on certain what-if scenarios. Our analysis indicates that three major compounds are investigated more than others: (1) YCo 5 , because it can potentially be an intermediate-performance hard magnet, and the presence of yttrium with no localized 4f electrons simplifies calculations significantly, (2) SmCo 5 , because it has the largest magnetic anisotropy energy among all RE hard magnets as well as very impressive high temperature performance, (3) CeCo 5 , because Ce is the most abundant rare earth element with a curious 4f electron behavior that gives rise to pronounced deviations in its structural and magnetic properties across the lanthanides series. This is followed by a brief analysis of several ab initio approaches that were developed to treat these rather complicated systems both at 0 K and at finite temperatures. Towards the end, we elucidate the role of exchange-correlation approximations such as local density approximations (LDA) and generalized gradient approximation (GGA) formulation in determining the MAE and M s by analyzing their corresponding density of states (DOS), and providing our results on a rather overlooked hard-magnetic material: LaCo 5 .

36 MATERIALS SCIENCE↗

DOE OSTI2024

Pore‐Scale Modeling of Reactive Transport with Coupled Mineral Dissolution and Precipitation

Abstract We present a new pore‐scale model for multicomponent advective‐diffusive transport with coupled mineral dissolution and precipitation. Both dissolution and precipitation are captured simultaneously by introducing a phase transformation vector field representing the direction and magnitude of the overall phase change. An effective viscosity model is adopted in simulating fluid flow during mineral dissolution‐precipitation that can accurately capture the velocity field without introducing any empirical parameters. The proposed approach is validated against analytical solutions and interface tracking simulations in simplified structures. After validation, the proposed approach is employed in modeling realistic rocks where mineral dissolution and precipitation are dominant at different locations. We have identified three regimes for mineral dissolution‐precipitation coupling: (a) compact dissolution‐precipitation where dissolution is dominant near the inlet and precipitation is dominant near the outlet, (b) wormhole dissolution with clustered precipitation where dissolution generates wormholes in the main flow paths and precipitation clogs the secondary flow paths, and (c) dissolution dominant where all solid grains are gradually dissolved. In the three regimes, the proposed approach provides reliable porosity‐permeability relationships that cannot be described well by traditional macroscale models. We find that the permeability can increase while the overall porosity decreases when the main flow paths are expanded by dissolution and adjacent pore spaces are clogged by precipitation.

58 GEOSCIENCES↗

DOE OSTI2018

Modeling of canonical and C2'- O -thiophenylmethyl modified hexamers of RNA. Insights into the nature of structural changes and thermal stability

Modifying the ribose ring or the nucleobase within oligonucleotides of RNA is a strategy that has regained attention due to its potential to provide chemical stability, increase affinity towards a target, or introduce groups with bioorthogonal reactivity, among other applications. However introducing groups via synthetic routes can be a daunting process and may result in unexpected physical properties and structural variations. In addition, characterizing the effects of a modification within an oligonucleotide can be time consuming and expensive, e.g., NMR, crystallography. Thus the development of models that are accurate, reasonably priced and carried out over short periods of time is essential to the development of this field. In this paper we report on the development and validation of computational models that explain the nature of the structural and stability changes induced by the presence of a C2'-O-methylthiophene group at various positions within duplexes conformed by two 6-mers of modified RNA as well as random coils containing the same modification(s). Through analysis of the obtained models it was concluded that the presence of the methylthiophene moiety on two strands of RNA induces a conformational change around the torsion angle (κ°) that leads to lower values in the pseudorotational angle (δ°), thus resulting in an A-form α-helix with shorter distances between phosphates than those in canonical RNA. These results provide a reasonable explanation for the experimental observations, which display the thermal stabilization of the duplexes, and are guiding efforts from our groups to control the structure and function of RNA, i.e., via functionalization of the RNA structure for attaining thermal stability while retaining the structural properties of an A-form duplex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Dissecting ion-specific dielectric spectra of sodium-halide solutions into solvation water and ionic contributions

Using extensive equilibrium molecular dynamics simulations we determine the dielectric spectra of aqueous solutions of NaF, NaCl, NaBr, and NaI. The ion-specific and concentration-dependent shifts of the static dielectric constants and the dielectric relaxation times match experimental results very well, which serves as a validation of the classical and non-polarizable ionic force fields used. The purely ionic contribution to the dielectric response is negligible, but determines the conductivity of the salt solutions. The ion-water cross correlation contribution is negative and reduces the total dielectric response by about 5%-10% for 1 M solutions. The dominating water dielectric response is decomposed into different water solvation shells and ion-pair configurations, by this the spectral blue shift and the dielectric decrement of salt solutions with increasing salt concentration is demonstrated to be primarily caused by first-solvation shell water. With rising salt concentration the simulated spectra show more pronounced deviations from a single-Debye form and can be well described by a Cole-Cole fit, in quantitative agreement with experiments. Our spectral decomposition into ionic and different water solvation shell contributions does not render the individual contributions more Debye-like, this suggests the non-Debye-like character of the dielectric spectra of salt solutions not to be due to the superposition of different elementary relaxation processes with different relaxation times. Rather, the non-Debye-like character is likely to be an inherent spectral signature of solvation water around ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

A flexible setup for angle-resolved X-ray fluorescence spectrometry with laboratory sources

X-ray fluorescence (XRF) analysis is one of the standard tools for the analysis of stratified materials and is widely applied for the investigation of electronics and coatings. The composition and thickness of the layers can be determined quantitatively and non-destructively. Recent work showed that these capabilities can be extended towards retrieving stratigraphic information like concentration depth profiles using angle-resolved XRF (ARXRF). This paper introduces an experimental sample chamber which was developed as a multi-purpose tool enabling different measurement geometries suited for transmission measurements, conventional XRF, ARXRF, etc. The chamber was specifically designed for attaching all kinds of laboratory X-ray sources for the soft and hard X-ray ranges as well as various detection systems. In detail, a setup for ARXRF using an X-ray tube with a polycapillary X-ray lens as source is presented. For such a type of setup, both the spectral and lateral characterizations of the radiation field are crucial for quantitative ARXRF measurements. The characterization is validated with the help of a stratified validation sample.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Hexagonal boron nitride and water interaction parameters

The study of hexagonal boron nitride (hBN) in microfluidic and nanofluidic applications at the atomic level requires accurate force field parameters to describe the water-hBN interaction. In this work, we begin with benchmark quality first principles quantum Monte Carlo calculations on the interaction energy between water and hBN, which are used to validate random phase approximation (RPA) calculations. We then proceed with RPA to derive force field parameters, which are used to simulate water contact angle on bulk hBN, attaining a value within the experimental uncertainties. This paper demonstrates that end-to-end multiscale modeling, starting at detailed many-body quantum mechanics and ending with macroscopic properties, with the approximations controlled along the way, is feasible for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Position dependent optical coupling between single quantum dots and photonic crystal nanocavities

We demonstrate precise and quick detection of the positions of quantum dots (QDs) embedded in two-dimensional photonic crystal nanocavities. We apply this technique to investigate the QD position dependence of the optical coupling between the QD and the nanocavity. We use a scanning electron microscope (SEM) operating at a low acceleration voltage to detect surface bumps induced by the QDs buried underneath. This enables QD detection with a sub-10 nm precision. We then experimentally measure the vacuum Rabi spectra to extract the optical coupling strengths (gs) between single QDs and cavities, and compare them to the values estimated by a combination of the SEM-measured QD positions and electromagnetic cavity field simulations. We found a highly linear relationship between the local cavity field intensities and the QD-cavity gs, suggesting the validity of the point dipole approximation used in the estimation of the gs. The estimation using SEM has a small standard deviation of ±6.2%, which potentially enables the high accuracy prediction of g prior to optical measurements. Our technique will play a key role for deeply understanding the interaction between QDs and photonic nanostructures and for advancing QD-based cavity quantum electrodynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Integral Nuclear Data and Benchmarking Needs for Fusion Energy Systems

Fusion energy systems are currently being designed and optimized using radiation transport codes. To deal with the unique environment inside a fusion-based system, many of these designs incorporate novel materials able to withstand the high radiation fields, ensure adequate cooling and thermal protection, and produce tritium. Validation plays a vital role in building trust in the predictive power of these models and computational methods. Validation of a code consists of modeling documented real-world experiments and comparing the code-predicted response to the measured response. Adequate validation requires measured responses from real-world experiments, also known as integral data, that mimic the system being designed, including materials, impinging radiation, and temperature, among other variables. The most trusted integral data are experimental responses that have been through a rigorous benchmarking process that develops a recommended computational model and evaluates all experimental uncertainties. Finally, there are a few research groups around the world that have been producing integral data for fusion applications, but a substantial investment is needed to address the unique validation needs of the fusion community.

Fusion↗