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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Soliton Generation in Negative Thermal Expansion Materials

Strain solitons have been observed statically in several 2D materials and dynamically in substrate materials using ultrafast laser pulses. The latter case relies on lattice relaxation in response to ultrafast heating in a light-absorbing transducer material, a process which is sensitive to the thermal expansion coefficient. Here we consider an unusual case where the sign of the thermal expansion coefficient is negative, a scenario which is experimentally feasible in light of rapid and recent advances in the discovery of negative thermal expansion materials. We present numerical solutions to a nonlinear differential equation which has been repeatedly demonstrated to quantitatively model experimental data and discuss the salient results using realistic parameters for material linear and nonlinear elasticity. The solitons that emerge from the initial value problem with negative and positive thermal expansion are qualitatively different in several ways. The new case of negative thermal expansion gives rise to a nearly-periodic soliton train with chirped profile and free of an isolated shock front. We suggest this unanticipated result may be realized experimentally and assess the potential for certain applications of this generic effect.

36 MATERIALS SCIENCE↗
DOE OSTI2022

University of Missouri Research Reactor (MURR) Design Demonstration Element End Fitting Structural Rigidity Analysis

The primary objective of this work is to assess the extent to which the stiffness (measured by means of maximum displacement) of the end fittings in the DDE contributes to the stiffness of the entire element, and how it compares to the equivalent stiffness of the end fittings in the LEU element. Structural analysis of both the LEU element and the DDE were performed using COMSOL 5.3a finite element software. Supporting combs are used on the leading and trailing edges of fuel plates for both the LEU element and the DDE. Therefore, simulations with and without combs are performed as two bounding boundary conditions on the leading edge of the fuel plates. Three types of loads are analyzed in this work: the hydraulic load due to the channel flow disparity-induced pressure differential, the thermal load due to the thermal expansion of the fuel plates, and a point load equal in magnitude to the LEU element’s weight.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Tuning Thermal and Mechanical Properties of Polydimethylsiloxane with Carbon Fibers

In order to meet the needs of constantly advancing technologies, fabricating materials with improved properties and predictable behavior has become vital. To that end, we have prepared polydimethylsiloxane (PDMS) polymer samples filled with carbon nanofibers (CFs) at 0, 0.5, 1.0, 2.0, and 4.0 CF loadings (w/w) to investigate and optimize the amount of filler needed for fabrication with improved mechanical properties. Samples were prepared using easy, cost-efficient mechanical mixing to combine the PDMS and CF filler and were then characterized by chemical (FTIR), mechanical (hardness and tension), and physical (swelling, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and coefficient of thermal expansion) analyses to determine the material properties. We found that hardness and thermal stability increased predictably, while the ultimate strength and toughness both decreased. Repeated tension caused the CF-filled PDMS samples to lose significant toughness with increasing CF loadings. The hardness and thermal degradation temperature with 4 wt.% CF loading in PDMS increased more than 40% and 25 °C, respectively, compared with the pristine PDMS sample. Additionally, dilatometer measurements showed a 20% decrease in the coefficient of thermal expansion (CTE) with a small amount of CF filler in PDMS. In this study, we were able to show the mechanical and thermal properties of PDMS can be tuned with good confidence using CFs.

degradation temperature↗
DOE OSTI2024

Bayesian reduced-order deep learning surrogate model for dynamic systems described by partial differential equations

We propose a reduced-order deep-learning surrogate model for dynamic systems described by time-dependent partial differential equations. This method employs space–time Karhunen–Loève expansions (KLEs) of the state variables and space-dependent KLEs of space-varying parameters to identify the reduced (latent) dimensions. Subsequently, a deep neural network (DNN) is used to map the parameter latent space to the state variable latent space. An approximate Bayesian method is developed for uncertainty quantification (UQ) in the proposed KL-DNN surrogate model. The KL-DNN method is tested for the linear advection–diffusion and nonlinear diffusion equations, and the Bayesian approach for UQ is compared with the deep ensembling (DE) approach, commonly used for quantifying uncertainty in DNN models. It was found that the approximate Bayesian method provides a more informative distribution of the PDE solutions in terms of the coverage of the reference PDE solutions (the percentage of nodes where the reference solution is within the confidence interval predicted by the UQ methods) and log predictive probability. The DE method is found to underestimate uncertainty and introduce bias. For the nonlinear diffusion equation, we compare the KL-DNN method with the Fourier Neural Operator (FNO) method and find that KL-DNN is 10% more accurate and needs less training time than the FNO method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Vacuum magnetic fields with exact quasisymmetry near a flux surface. Part 1. Solutions near an axisymmetric surface

While several results have pointed to the existence of exactly quasisymmetric fields on a surface (Garren & Boozer, Phys. Fluids B, vol. 3, 1991, pp. 2805–2821; 2822–2834; Plunk & Helander, J. Plasma Phys. , vol. 84, 2018, 905840205), we have obtained the first such solutions using a vacuum surface expansion formalism. We obtain a single nonlinear parabolic partial differential equation for a function $\eta$ such the field strength satisfies $B = B(\eta )$ . Closed-form solutions are obtained in cylindrical, slab and isodynamic geometries. Numerical solutions of the full nonlinear equations in general axisymmetric toroidal geometry are obtained, resulting in a class of quasihelical local vacuum equilibria near an axisymmetric surface. The analytic models provide additional insight into general features of the nonlinear solutions, such as localization of the surface perturbations on the inboard side. The local solutions thus obtained can be continued globally only for special initial surfaces.

Physics↗
DOE OSTI2024

Loops of loops expansion in the amplituhedron

We study a novel geometric expansion for scattering amplitudes in the planar sector of $\mathcal{N}$ = 4 super Yang-Mills theory, in the context of the Amplituhedron which reproduces the all-loop integrand as a canonical differential form on the positive geometry. In a paper by Arkani-Hamed, Henn and one of the authors, it was shown that this result can be recast in terms of negative geometries with a certain hierarchy of loops (closed cycles) in the space of loop momenta, represented by lines in momentum twistor space. One can then calculate an all-loop order result in the approximation where only tree graphs in the space of all loops are considered. Furthermore, using differential equation methods, it is possible to calculate and resum integrated expressions and obtain strong coupling results. In this paper, we provide a more general framework for the ‘loops of loops’ expansion and outline a powerful method for the determination of differential forms for higher-order geometries. We solve the problem completely for graphs with one internal cycle, but the method can be used more generally for other geometries.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Ab initio nucleon-nucleus elastic scattering with chiral effective field theory uncertainties

Effective interactions for nucleon-nucleus elastic scattering from first principles require the use of the same nucleon-nucleon interaction in the structure and reaction calculations and a consistent treatment of the relevant operators at each order. Systematic investigations of the effect of truncation uncertainties of chiral nucleon-nucleon ( N N ) forces have been carried out for scattering observables in the two- and three-nucleons system as well as for bound-state properties of light nuclei. Here we extend this type of study to proton and neutron elastic scattering for 16 O and 12 C. Using the frameworks of the spectator expansion of multiple scattering theory as well as the no-core shell model, we employ one specific chiral interaction from the LENPIC collaboration and consistently calculate the leading-order effective nucleon-nucleus interaction up to the third chiral order, from which we extract elastic scattering observables. Then we apply pointwise as well as correlated uncertainty quantification for the estimation of the chiral truncation error. We calculate and analyze proton elastic scattering observables for 16 O and 12 C as well as neutron elastic scattering observables for 12 C between 65 and 185 MeV projectile kinetic energy. We find in all cases qualitatively similar results for the chiral truncation uncertainties as in few-body systems and assess them using similar diagnostic tools. The order-by-order convergence of the scattering observables for 16 O and 12 C is very reasonable around 100 MeV, while for higher energies the chiral expansion parameter becomes too large for convergence. Comparing proton and neutron differential cross sections reveals that their description is comparable up to around 100 MeV. Here, we also find a nearly perfect correlation between the differential cross section for neutron scattering and the N N Wolfenstein amplitudes for small momentum transfers. The diagnostic tools for studying order-by-order convergence in observables in few-body systems can be employed for observables in nucleon-nucleus scattering with only minor modifications provided the momentum scale in the problems is not too large. We also find that the chiral N N interaction on which our study is based gives a very good description of differential cross sections for 16 O and 12 C as low as 65-MeV projectile energy, particularly in the forward direction. In addition, the very forward direction of the neutron differential cross section mirrors the behavior of the N N interaction amazingly well.

6 ≤ A ≤ 19↗
DOE OSTI2025

$\mathrm{SageNet}$: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation

Accurate modeling of the inflationary gravitational waves (GWs) requires time-consuming, iterative numerical integrations of differential equations to take into account their backreaction on the expansion history. To improve computational efficiency while preserving accuracy, we present the Stiff-amplified Gravitational-wave Emulator Network (SageNet), a deep learning framework designed to replace conventional numerical solvers (code available at https://github.com/YifangLuo/SageNet). SageNet employs a long short-term memory architecture to emulate the present-day energy density spectrum of the inflationary GWs with possible stiff amplification, Ω GW (f). Trained on a data set of 25,689 numerically generated solutions, SageNet allows accurate reconstructions of Ω GW (f) and generalizes well to a wide range of cosmological parameters; 90.9% of the test emulations with randomly distributed parameters exhibit errors of under 4%. In addition, SageNet demonstrates its ability to learn and reproduce the artificial, adaptive sampling patterns in numerical calculations, which implement denser sampling of frequencies around changes in spectral indices in Ω GW (f). The dual capability of learning both physical and artificial features of the numerical GW spectra establishes SageNet as a robust alternative to exact numerical methods. Finally, our benchmark tests show that SageNet reduces the computation time from tens of seconds to milliseconds, achieving a speedup of ∼10 4 times over standard CPU-based numerical solvers with the potential for further acceleration on GPU hardware. These capabilities make SageNet a powerful tool for accelerating Bayesian inference procedures for extended cosmological models. In a broad sense, the SageNet framework offers a fast, accurate, and generalizable solution to modeling cosmological observables whose theoretical predictions demand costly differential equation solvers.

Astronomy data modeling↗
DOE OSTI2022

The stratification of rigidity

We show that a master integrand basis exists for all planar, two-loop amplitudes in massless four-dimensional theories which is fully stratified by rigidity — with each integrand being either pure and strictly polylogarithmic or (pure and) strictly elliptic-polylogarithmic, with each of the later involving a single elliptic curve. Such integrands can be said to have definite rigidity.

1/N Expansion↗
DOE OSTI2026

Global population structures and demographic history of Suillus luteus, a pine co‐introduced ectomycorrhizal fungus associated with exotic forestry and invasion

Human colonization since the 19th century has resulted in the global spread of pines beyond their original northern boreal distribution. Although the introduction history of pines is documented through historical records, little is known about the introduction history of their ectomycorrhizal (ECM) fungi, which are critical symbionts for the survival and invasion of pines. Using Suillus luteus as an example, whole genomes of 208 individuals collected across native and introduced ranges were sequenced to reveal the introduction history of pine co-introduced ECM fungi. Population genomics analyses showed that all introductions originated from Europe. With the exception of North America, introduced populations were genetically differentiated from the European population, with varying magnitudes of population expansion in different introduced regions. Genetic variation within the native European population followed isolation by distance, but not in the introduced range, highlighting the disparity in the spatial-genetic patterns of native vs exotic habitats. The spread of S. luteus is mediated by human activities accompanying pine introductions, with its demographic history linked to forestry practices. The spatial, temporal, and demographic patterns observed in S. luteus offer insight into the population genetics of a widely introduced ECM fungus and are likely applicable to other pine co-introduced ECM fungi.

Ke, Yi‐Hong↗
DOE OSTI2025

High-temperature stability and thermal expansion behavior of equi-atomic refractory multi-principal element alloys based on MoNbTi system for Gen IV reactor applications

The present study investigates the thermal stability and thermal expansion behavior of seven equi-atomic refractory multi-principal element alloys (MPEAs) based on the MoNbTi ternary system composed of low neutron absorption cross section elements. Through an integrated approach utilizing in-situ high-temperature X-ray diffraction (HT-XRD) in conjunction with differential scanning calorimetry (DSC), dilatometry and ageing heat treatment, the thermal stability of the MPEAs was comprehensively analyzed. In-situ HT-XRD experiment confirmed the stability of the room temperature phases up to 1000 °C with no peaks observed corresponding to additional phases in the HT-XRD patterns at 500, 800 and 1100 °C. DSC thermograms showed the absence of peaks up to 1000 °C, while peaks and valleys corresponding to exothermic and endothermic events were observed above 1000 °C. Coefficient of thermal expansion (CTE) derived from second order polynomial fitting of linear thermal expansion data from the dilatometry experiment showed linear increment up to 1000 °C for all the alloys except those containing Zr. The Cr containing alloys exhibited notably higher CTE values, particularly the Al containing alloy exhibited the highest value. Ageing heat treatment at 800 and 1000 °C for 96 h and subsequent microstructural analysis revealed significant precipitation of secondary phases in MoNbTiZr, MoNbTiZrV and MoNbTiCrAl. In conclusion, a substantial increase in hardness was observed in MoNbTiZr and MoNbTiCrAl due to secondary phase precipitation, while the other alloys maintained hardness values comparable to their as-cast and homogenized states.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. Furthermore, this study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Chromosome-scale Genome Assembly of the Most Abundant Ectomycorrhizal Fungus Cenococcum Geophilum Reveals Massive TE Expansion and RIP Defense Mechanism

Transposable elements (TEs) play crucial roles in genome evolution and ecological adaptation in fungi, yet their dynamics in ectomycorrhizal species remain poorly understood. Cenococcum geophilum, the most widespread ectomycorrhizal fungus in boreal and temperate forests with its large, repeat-rich genome, represents an ideal system to investigate TE-mediated adaptation to the physical environment and symbiotic lifestyle. However, previous studies have been limited by fragmented genome assemblies that prevented the resolution of repeat-rich regions. We assembled a telomere-to-telomere reference genome of C. geophilum strain 1.58 using PacBio HiFi and Hi-C datasets, resulting in a 178.54 Mbp genome with seven contiguous chromosomes. We identified 14,145 genes and over 78% of the genome consists of transposable elements (TEs). Of these, 94% are affected by repeat-induced point mutations (RIP), a genome defense mechanism that acts during the sexual reproduction phase, indicating cryptic or ancient sexual reproduction in this putatively asexual fungus. Long terminal repeat retrotransposons, LINEs, and DNA transposons dominate, with three TE families (Ty3, Ty1, and Tad1) contributing over 60% of the genome size, indicating recent transposition bursts. Screening of 15 additional C. geophilum strains revealed recent and lineage-specific TE expansions, implying that several TEs escaped the RIP machinery and retained potential activity. Supporting TE activity in the context of symbiosis, we found 56 TEs differentially transcribed between ectomycorrhizal and free-living mycelium tissues. An even higher number (n = 66) of TEs were differentially expressed between stress resistance morphology (i.e. sclerotia) and free-living mycelium. This supports that TEs are differentially regulated as a response to symbiotic and stress-related conditions. Our results demonstrate that the C. geophilum genome expansion was driven by a few lineage-specific TE families in recent history, with high RIP activity attesting to sexual reproduction. We also provide insights how TEs could respond to lifestyle transitions and traits associated with desiccation resistance.

Cenococcum geophilum↗
DOE OSTI2025

Karhunen–Loève deep learning method for surrogate modeling and approximate Bayesian parameter estimation

We evaluate the performance of the Karhunen-Loève Deep Neural Network (KL-DNN) framework for surrogate modeling and approximate Bayesian parameter estimation in partial differential equation models. In the surrogate model, the Karhunen-Loève (KL) expansions are used for the dimensionality reduction of the number of unknown parameters and variables, and a deep neural network is employed to relate the reduced space of parameters to that of the state variables. The KL-DNN surrogate model is used to formulate a maximum-a-posteriori-like least-squares problem, which is randomized to draw samples of the posterior distribution of the parameters. We test the proposed framework for a hypothetical unconfined aquifer via comparison with the forward MODFLOW and inverse PEST++ iterative ensemble smoother (IES) solutions as well as the state-of-the-art Fourier neural operator (FNO) and deep operator networks (DeepONets) operator learning surrogate models. Our results show that the KL-DNN surrogate model outperforms FNO and DeepONet for forward predictions. For solving inverse problems, the randomized algorithm provides the same or more accurate Bayesian predictions of the parameters than IES as evidenced by the higher log-predictive probability of both the estimated parameter field and the forecast hydraulic head. The posterior mean obtained from the randomized algorithm is closer to the reference parameter field than that obtained with FNO as the maximum a posteriori estimate.

Approximate Bayesian inference↗
DOE OSTI2024

Modeling In-Reactor Temperature Gradients in Lithium Aluminate Ceramic Pellets

In reactor thermal performance of lithium aluminate ceramic pellets are calculated to determine operating temperatures if internal components shift during irradiation. A 2D conduction model was setup to model this scenario with additional physics, including thermal expansion of components to reactor temperatures, creep down of the cladding due to differential pressure between the inside of the rod and reactor coolant system, and net radiation exchange between components. The non-linear coupling of the governing equations presented convergence challenges due to the very different effects from a small temperature change on the radiation vs radial and circumferential conduction equations. Initial temperature guesses for the multidimensional solution were provided from conservative 1D models simulating bounding scenarios. Convergence was greatly improved by taking small steps towards the root solutions and averaging with initial guesses. The final method robustly converged all 132 points at an axial plane after a few dozen iterations. The temperature results show that the additional physics have a secondary effect as the dominant heat transfer mechanism is radial conduction across the gas gap followed by circumferential conduction around components. Circumferential conduction in the lithium aluminate pellets is enhanced by the relatively high thermal conductivity of this ceramic.

Carstens, Nathan A.↗
DOE OSTI2020

High-Temperature Thermodynamics of Cerium Silicates, A-Ce 2 Si 2 O 7 , and Ce 4.67 (SiO 4 ) 3 O

Lanthanide disilicates and oxyapatites have potential roles in high temperature applications as thermal (TBC) and environmental barrier coatings (EBC), or possible alteration phases in geological nuclear waste repositories. However, those Ce 3+ -bearing silicates have only been limitedly studied. In this work, we performed detailed structural and thermodynamic investigations on A-Ce 2 Si 2 O 7 (tetragonal, P4 1 ) and Ce 4.67 (SiO 4 ) 3 O (hexagonal, P6 3 /m). The high temperature structural behaviors and coefficients of thermal expansion were determined by in situ high temperature synchrotron X-ray diffraction (HT-XRD) implemented with Rietveld analysis and thermogravimetric analysis coupled with differential scanning calorimetry (TGA-DSC). A-Ce 2 Si 2 O 7 was found to be stable in N 2 and air up to ~1483 K with anisotropic thermal expansion along the a and c axes (α a = 12.3 × 10 -6 K -1 and α c = 12.4 × 10 -6 K -1 ). Ce 4.67 (SiO 4 ) 3 O had a slow partial oxidation between 533 K and 873 K to a new nonstoichiometric phase Ce 3+ 1.67- xCe4 + x Ce 3+ 3 (SiO 4 ) 3 O 1+0.5x , followed by a thermal decomposition to CeO 2 and SiO 2 at ~1000 K in air. By using high temperature oxide melt solution calorimetry at 973 K with lead borate as the solvent, the standard enthalpy of formation was determined for A-Ce 2 Si 2 O 7 (-3825.1 ± 6.0 kJ/mol) and Ce 4.67 (SiO 4 ) 3 O (-7391.3 ± 9.5 kJ/mol). Finally, these thermodynamic parameters were compared with those of CeO 2 , CeSiO 4 , and other silicate oxyapatites for examining their chemical stability in high temperature environments relevant for aeronautical applications, mineral formation, and nuclear fuel cycle.

36 MATERIALS SCIENCE↗
DOE OSTI2020

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↗