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DOE OSTI2026

Cooperative effect of local active stresses on the macroscopic contractility of elastic fiber networks

The collective action of actively contractile units embedded in elastic biopolymer networks plays a crucial role in regulating the network's macroscopic mechanical response. Here, in this study, we investigate how the macroscopic boundary stress in model elastic fiber networks depends on the number and nature of embedded contractile units, each exerting an isotropic force dipole, as well as on the bending stiffness of fibers. We find that the macroscopic stress increases nonlinearly with the number of dipoles due to mutual stiffening of initially soft, bending-dominated networks. Using effective medium theory, we relate this enhanced contractility to an increase in the effective average network coordination number due to constraints imposed by the force dipoles. By comparing three distinct force dipole models that differ in their local structures, we demonstrate that the specific manner in which an active unit constrains the network strongly influences the onset and nature of the stiffening transition. Our results highlight that not only the quantity but also the local geometry of force-generating units critically determines the macroscopic mechanical behavior. This framework provides a physical basis for understanding how biological systems—such as molecular motors in the cytoskeleton, or adherent cells in the extracellular matrix—can modulate network-scale nonlinear elastic properties through local tuning of active force-generating units.

Biological and medical sciences↗

DOE OSTI2020

Detecting Fractional Chern Insulators in Optical Lattices Through Quantized Displacement

The realization of interacting topological states of matter such as fractional Chern insulators (FCIs) in cold atom systems has recently come within experimental reach due to the engineering of optical lattices with synthetic gauge fields providing the required topological band structures. However, detecting their occurrence might prove difficult since transport measurements akin to those in solid state systems are challenging to perform in cold atom setups and alternatives have to be found. Here, we show that for a ν = 1/2 FCI state realized in the lowest band of a Harper-Hofstadter model of interacting bosons confined by a harmonic trapping potential, the fractionally quantized Hall conductivity σ xy can be accurately determined by the displacement of the atomic cloud under the action of a constant force which provides a suitable experimentally measurable signal for detecting the topological nature of the state. Using matrix-product state algorithms, we show that, in both cylinder and square geometries, the movement of the particle cloud in time under the application of a constant force field on top of the confining potential is proportional to σ xy for an extended range of field strengths.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Enhancing microsegregation during rapid directional solidification through ternary microalloying

The nano-cellular dendritic microstructure formed during rapid directional solidification in powder bed fusion additive manufacturing creates unique properties such as simultaneous improvement in strength and ductility. However, process control of microsegregation features remains challenging due to low sensitivity of critical solidification mechanisms to process parameters. This study leverages microalloying to achieve large changes in dendrite composition, microstructure, and interdendritic zone width during laser powder bed fusion without modifying process parameters. CALPHAD simulations predict that the addition of Zr significantly steepens the solidus line of the dilute Cu-Cr alloy system, leading to enhanced Cr rejection into the melt and greater than 95% reduction in solubility of Cr in the solidified Cu matrix. Experimental validation using time-of-flight secondary ion mass spectrometry and Kelvin probe force microscopy reveals that the ternary alloy containing 0.01 wt% Zr exhibited wider interdendritic regions compared to the binary, a significantly higher number of Cr-rich particles within interdendritic regions, near-complete ejection of oxygen impurities from the matrix, and greater nanoscale work function contrast. These features indicate more aggressive Cr segregation in the presence of Zr and a purer Cu matrix and provide a potentially robust method for engineering the nano-cellular dendritic solidification microstructure.

CALPHAD↗

DOE OSTI2021

Scattering matrix pole expansions for complex wave numbers in R -matrix theory

In this followup article to Ducru et al., we establish new results on scattering matrix pole expansions for complex wave numbers in R-matrix theory. In the past, two branches of theoretical formalisms emerged to describe the scattering matrix in nuclear physics: R-matrix theory and pole expansions. The two have been quite isolated from one another. Recently, our study of Brune's alternative parametrization of R-matrix theory has shown the need to extend the scattering matrix (and the underlying R-matrix operators) to complex wave numbers. Two competing ways of doing so have emerged from a historical ambiguity in the definitions of the shift S and penetration P functions: the legacy Lane and Thomas's “force closure” approach versus analytic continuation (which is the standard in mathematical physics). The R-matrix community has not yet come to a consensus as to which to adopt for evaluations in standard nuclear data libraries, such as ENDF. Here, in this article, we argue in favor of analytic continuation of R-matrix operators. We bridge R-matrix theory with the Humblet-Rosenfeld pole expansions, and discover new properties of the Siegert-Humblet radioactive poles and widths, including their invariance properties to changes in channel radii a c . We then show that analytic continuation of R-matrix operators preserves important physical and mathematical properties of the scattering matrix—canceling spurious poles and guaranteeing generalized unitarity—while still being able to close channels below thresholds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Polyethylene Blends for Improved Oxygen Barrier: Processing-Dependent Microstructure and Gas Permeability

Here this work demonstrates a greater than expected enhancement of oxygen barrier properties in linear low-density polyethylene (LLDPE)-based materials by blending LLDPE with high-density polyethylene (HDPE). The films made by melt pressing the LLDPE/HDPE blends had a greater reduction in oxygen permeability coefficients (PO 2 ) than predicted using common permeability reduction models, i.e., the harmonic average model and zero-permeability nanofiller model. The reduction of PO 2 was attributed to the presence of spherulite crystal structures, as revealed by atomic force microscopy combined with infrared spectroscopy (AFM-IR). The LLDPE matrix exhibited significant spherulite formation even at a relatively low addition of HDPEs, which likely formed tortuous pathways for diffusing oxygen molecules. Transport results from melt-pressed films contrast with the results from films with similar compositions prepared by film blowing, which did not show barrier enhancement beyond expectation. AFM-IR revealed that the blown films lacked spherulite crystals likely due to stretching in the machine direction followed by rapid cooling. These findings demonstrate the role of processing in controlling microstructures and thus the oxygen barrier performance. This work offers the possibility of achieving easily recyclable LLDPE-based packaging materials by simple blending of polyethylenes with different crystalline content.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Surfactants are Ineffective for Reducing Imbibition of Water-Based Fracturing Fluids in Deep Gas Reservoirs

Minimizing loss of injected hydraulic fracturing fluids into shale along fracture-matrix boundaries is desired because imbibed water restricts gas production and wastes valuable water resources. This problem has motivated the addition of surfactants into water-based hydraulic fracturing fluids in order to reduce the capillary driving force for imbibition. Here, we show that reduction in interfacial tension and wettability alteration has negligible ability to reduce imbibition in deep gas reservoirs. The effectiveness of altering capillary forces acting at the wetting front also depends on the injection pressure acting at the fracture-matrix boundary. The pressure at the interface between the fracture and the shale matrix is constrained between the reservoir pore pressure and formation pressure (rock fracture pressure, also known as breakdown pressure of the rock) and increases with depth to magnitudes that greatly exceed that of capillary pressures. Furthermore, the analyses presented here show that even maximum alteration of interfacial properties that result in strongly hydrophobic interactions between the fracturing fluid and reservoir rock is incapable of significantly reducing imbibition in deep reservoirs. Instead of using surfactants, this analysis points to decreases in wellbore shut-in pressures and shut-in times as practical options for reducing imbibition losses of water-based fluids.

03 NATURAL GAS↗

DOE OSTI2023

Microstructural and Rheological Transitions in Bacterial Biofilms

Biofilms are aggregated bacterial communities structured within an extracellular matrix (ECM). ECM controls biofilm architecture and confers mechanical resistance against shear forces. From a physical perspective, biofilms can be described as colloidal gels, where bacterial cells are analogous to colloidal particles distributed in the polymeric ECM. However, the influence of the ECM in altering the cellular packing fraction (Φ) and the resulting viscoelastic behavior of biofilm remains unexplored. Using biofilms of Pantoea sp. (WT) and its mutant (ΔUDP), the correlation between biofilm structure and its viscoelastic response is investigated. Experiments show that the reduction of exopolysaccharide production in ΔUDP biofilms corresponds with a seven-fold increase in Φ, resulting in a colloidal glass-like structure. Consequently, the rheological signatures become altered, with the WT behaving like a weak gel, whilst the ΔUDP displayed a glass-like rheological signature. By co-culturing the two strains, biofilm Φ is modulated which allows us to explore the structural changes and capture a change in viscoelastic response from a weak to a strong gel, and to a colloidal glass-like state. The results reveal the role of exopolysaccharide in mediating a structural transition in biofilms and demonstrate a correlation between biofilm structure and viscoelastic response.

viscoelasticity↗

DOE OSTI2021

Analysis of the neutron matter equation of state and the symmetry energy up to fourth order of chiral effective field theory

We present predictions for the neutron matter equation of state, from leading to fourth order of chiral effective field theory, using recently developed, accurate chiral nucleon-nucleon potentials. For the many-body method, we employ the nonperturbative particle-particle ladder approximation, that is, we solve the G-matrix equation. Furthermore, we find the impact of subleading three-neutron forces to be mild and attractive. We also show order-by-order predictions for the symmetry energy, and discuss its density dependence in relation to empirical constraints. For the nuclear matter equation of state, in this work we adopt an empirical parametrization with good saturation properties. This is to highlight, specifically, the energy and pressure in neutron matter, particularly when comparing with empirical constraints.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Single-Step Direct Laser Writing of Multimetal Oxygen Evolution Catalysts from Liquid Precursors

We investigate a laser direct-write method to synthesize and deposit metastable, mixed transition metal oxides and evaluate their performance as oxygen evolution reaction catalysts. This laser processing method enabled the rapid synthesis of diverse heterogeneous alloy and oxide catalysts directly from cost-effective solution precursors, including catalysts with a high density of nanocrystalline metal alloy inclusions within an amorphous oxide matrix. The nanoscale heterogenous structures of the synthesized catalysts were consistent with reactive force-field Monte Carlo calculations. By evaluating the impact of varying transition metal oxide composition ratios, we created a stable Fe 0.63 Co 0.19 Ni 0.18 O x /C catalyst with a Tafel slope of 38.23 mV dec -1 and overpotential of 247 mV, a performance similar to that of IrO 2 . Synthesized Fe 0.63 Co 0.19 Ni 0.18 O x /C and Fe 0.14 Co 0.46 Ni 0.40 O x /C catalysts were experimentally compared in terms of catalytic performance and structural characteristics to determine that higher iron content and a less crystalline structure in the secondary matrix decreases the charge transfer resistance and thus is beneficial for electrocatalytic activity. Furthermore, this conclusion is supported by density-functional theory calculations showing distorted active sites in ternary metal catalysts are key for lowering overpotentials for the oxygen evolution reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Accurate models of the added mass force of a uniform random distribution of spherical particles or bubbles

The added mass force resulting from the acceleration of a body in a fluid is of fundamental and practical interest in dispersed multiphase flows. Euler–Lagrange (EL) and Euler–Euler (EE) simulations require closure terms for the added mass force in order to accurately couple the conserved variables between phases. Presently, a more thorough understanding of the added mass force in a multi-particle system is developed based on potential flow resulting in a resistance matrix formulation analogous to Stokesian dynamics. This formulation is then used to generate a dataset of added mass resistance matrices for large systems of randomly generated particles. This methodology is used to create a volume fraction corrected binary model for predicting the added mass force in large systems as well as generate statistics of the added mass force in such systems. This work provides clarification to the theory of the added mass force for particle clouds, and modelling options that may be implemented in existing EL and EE codes.

42 ENGINEERING↗

DOE OSTI2025

Designing Physicochemically‐Ordered Interphases for High‐Performance Composites

To enhance the mechanical properties of carbon fiber‐reinforced polymer composites, a physicochemical scaffold is designed incorporating microscopically architected chemically reactive nanofibers that act as a multiscale bridge between the carbon fibers and the matrix. Thermally activated nanofibers leverage their morphologically driven mechanochemical properties to form covalent bonds with adjacent polymer molecules, creating a co‐continuous network that dramatically enhances fiber‐matrix load transfer. By meticulously controlling the nanofiber architecture through variable surface area, functional group availability, and polymer chain alignment effects, the extent of covalent bonding between nanofibers and the matrix is manipulated ultimately resulting in improved carbon fiber‐matrix adhesion. Further, the concept was validated using polyacrylonitrile nanofibers within an acrylonitrile butadiene styrene matrix in a discontinuous carbon fiber‐reinforced composite system. Nanomechanical studies using atomic force microscopy and low‐field nuclear magnetic resonance spectroscopy confirmed immobilized, chemically transferred, and ordered nanostructures at the interphase. The resulting composites demonstrated ≈56% and ≈175% improvements in tensile strength and toughness, respectively, compared to composites without nanofiber. Comprehensive thermal, rheological, and X‐ray scattering analyses, along side all‐atomic molecular dynamics simulations, revealed the fundamental mechanisms behind these improvements in mechanical behavior. The versatility and efficacy of the approach have the potential to address longstanding interphase challenges in the composite industry.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Elucidating nanoscale mechanical properties of diabetic human adipose tissue using atomic force microscopy

Abstract Obesity-related type 2 diabetes (DM) is a major public health concern. Adipose tissue metabolic dysfunction, including fibrosis, plays a central role in DM pathogenesis. Obesity is associated with changes in adipose tissue extracellular matrix (ECM), but the impact of these changes on adipose tissue mechanics and their role in metabolic disease is poorly defined. This study utilized atomic force microscopy (AFM) to quantify difference in elasticity between human DM and non-diabetic (NDM) visceral adipose tissue. The mean elastic modulus of DM adipose tissue was twice that of NDM adipose tissue (11.50 kPa vs. 4.48 kPa) to a 95% confidence level, with significant variability in elasticity of DM compared to NDM adipose tissue. Histologic and chemical measures of fibrosis revealed increased hydroxyproline content in DM adipose tissue, but no difference in Sirius Red staining between DM and NDM tissues. These findings support the hypothesis that fibrosis, evidenced by increased elastic modulus, is enhanced in DM adipose tissue, and suggest that measures of tissue mechanics may better resolve disease-specific differences in adipose tissue fibrosis compared with histologic measures. These data demonstrate the power of AFM nanoindentation to probe tissue mechanics, and delineate the impact of metabolic disease on the mechanical properties of adipose tissue.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Embedded symmetric positive semi-definite machine-learned elements for reduced-order modeling in finite-element simulations with application to threaded fasteners

Here, we present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an “outer” coarse-scale domain that we resolve using a finite element method (FEM) and an “inner” fine-scale domain. We then develop a machine-learned (ML) model for the impact of the inner domain on the outer domain. In essence, for solid mechanics, our machine-learned surrogate performs static condensation of the inner domain degrees of freedom. This is achieved by learning the map from displacements on the inner-outer domain interface boundary to forces contributed by the inner domain to the outer domain on the same interface boundary. We consider two such mappings, one that directly maps from displacements to forces without constraints, and one that maps from displacements to forces by virtue of learning a symmetric positive semi-definite (SPSD) stiffness matrix. We demonstrate, in a simplified setting, that learning an SPSD stiffness matrix results in a coarse-scale problem that is well-posed with a unique solution. We present numerical experiments on several exemplars, ranging from finite deformations of a cube to finite deformations with contact of a fastener-bushing geometry. We demonstrate that enforcing an SPSD stiffness matrix drastically improves the robustness and accuracy of FEM–ML coupled simulations, and that the resulting methods can accurately characterize out-of-sample loading configurations with significant speedups over the standard FEM simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Skeletal reaction models for methane combustion

A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). Here, the sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Parallel-in-Time Simulation of Lindblad's Equation

Constructing fast quantum logic gates is critical to building a scalable quantum computer. We consider a qudit, a quantum version of a bit that can take an arbitrary number of states, coupled with a cavity. In this project, we wish to force the qudit to reach the 0-state, for any possible initial state. The coupled system changes in time according to Lindblad’s equation, an ordinary differential equation on the density matrix of the quantum system. Lindblad’s equation contains some parameters that we can control, so-called control functions. We seek control functions which force the qudit to the 0-state within 2 microseconds, which is much faster than what is currently done in practice. The search method is gradient descent, a numerical optimization method that uses gradient information to iteratively improve the control parameters. My contribution to this project is an attempt to speed up the computation of the gradient. It currently takes about 40 seconds to compute the gradient which involves solving a set of ODEs sequentially. Current supercomputers have thousands of cores, but sequential computations can only make use of 1 core at a time. We wish to divide up the work better, so that we can use many more cores at once. To this end, we have implemented the Multigrid Reduction in Time (MGRIT) algorithm. We perform a systematic parameter search on how to best apply this algorithm. Results indicate a 25 percent speed up for solving Lindblad’s equation and determining how close the final state is the 0-state.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Process Intensification for Nanostructure Aluminum Extrusions

A new technology called Shear Assisted Processing and Extrusion (ShAPE™), pioneered at the Pacific Northwest National Laboratory (PNNL), has the potential to revolutionize the US extrusion industry. Maturation of the ShAPE™ process would create a new cross cutting US manufacturing technology that advances three key the objectives within AMO; namely, nanomaterials processing, process intensification, and materials for extreme and harsh environments. PNNL and SCM Metals Products, Inc. (SCM), a division of Kymera International, will collaborate to mature the ShAPE™ extrusion process beyond TRL 3 to increase the likelihood of its adoption by industry. PNNL’s custom (one-of-a-kind in the world) ShAPE™ machine will be used to extrude round rods of high strength aluminum alloy feedstock powder provided by SCM. As proof-of-concept, PNNL has previously extruded 5 mm diameter rods with SCM aluminum alloy powder AL-12.4TM. This project aims to scale up the process to a diameter of 25 mm while retaining the excellent mechanical properties achieved for the 5 mm diameter rods. The degree of process intensification with ShAPE™ will also be estimated. The primary objectives of this project are as follows. 1) Fabricate 25 mm diameter nanostructured extrusions in bulk, directly from AL-12.4TM aluminum alloy powder without the need for canning, degassing, compaction, and other intermediate steps typical of powder metallurgy extrusion. 2) Achieve a microstructure with an ultrafine grained (UFG <1 µm) aluminum matrix having refined and homogenously distributed nanoscale second phases. 3) Show that the ram force can be significantly reduced compared to conventional powder metallurgy extrusion of the same material and estimate the extent of process intensification that may be possible with ShAPE™. 4) Demonstrate improved high-temperature mechanical properties compared to conventional extrusion of the same material. The following tasks will be undertaken to achieve these objectives. PNNL will develop the die set and process parameters necessary to fabricate Al-12.4TM extrusions with a 25 mm diameter. Microstructural analysis will be performed by PNNL while mechanical testing will be conducted by SCM. With information learned from the process development and characterization, PNNL will perform an estimate of the degree of process intensification that may be possible with ShAPE™.

42 ENGINEERING↗

DOE OSTI2021

Ab Initio Neutrinoless Double-Beta Decay Matrix Elements for Ca 48 , Ge 76 , and Se 82

We calculate basis-space converged neutrinoless ββ-decay nuclear matrix elements for the lightest candidates: 48 Ca, 76 Ge, and 82 Se. Starting from initial two- and three-nucleon forces, we apply the ab initio in-medium similarity renormalization group to construct valence-space Hamiltonians and consistently transformed ββ-decay operators. Here, we find that the tensor component is non-negligible in 76 Ge and 82 Se, and the resulting nuclear matrix elements are overall 25%–45% smaller than those obtained from the phenomenological shell model. While a final matrix element with uncertainties still requires substantial developments, this work nevertheless opens a path toward a true first-principles calculation of neutrinoless ββ decay in all nuclei relevant for ongoing large-scale searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗