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DOE OSTI2024

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence–function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ~400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

The ion-ion correlations in organic ionic plastic crystal

Organic ionic plastic crystals (OIPCs) are emerging as promising electrolyte materials for solid-state batteries. However, despite the fast ionic diffusion, OIPCs exhibit relatively low DC conductivity in solid phases caused by strong ion-ion correlations that suppress charge transport. To understand the origin of this suppression, we performed a study of ion dynamics in the OIPC 1-Ethyl-1-methylpyrrolidinium bis (trifluoromethyl sulfonyl) imide [P 12 ][TFSI] utilizing dielectric spectroscopy, light scattering, and Nuclear Magnetic Resonance diffusometry. Comparison of the results obtained in this study with the published earlier results on an OIPC with a completely different structure (Diethyl(methyl)(isobutyl)phosphonium Hexafluorophosphate [P 1,2,2,4 ][PF 6 ]) revealed strong similarities in ion dynamics in both systems. Unlike DC conductivity, which may drop more than ten times between melted and solid phases, diffusion of anions and cations remains high and does not show strong changes at phase transition. The conductivity spectra in the broad frequency range demonstrate unusual shapes in solid phases with an additional step separating fast local ion motions from suppressed long-range charge diffusion controlling DC conductivity. We suggested that in solid phases, anions and cations can jump only between the specific ion sites defined by the crystalline structure. These constraints lead to strong cation-cation and anion-anion correlations strongly suppressing long-range charge transport.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Optimal Geometry for Focused Ion Beam-Milled Samples for Direct-Pull Micro-Tensile Testing Performed In Situ in a Scanning Electron Microscope

A thorough procedure was developed to efficiently manufacture dogbone samples using focused ion beam (FIB) milling for micro-tensile testing. A Bruker PI 89 PicoIndenter, Billerica, MA, USA, was used as a case study, although the analysis and results are applicable to other micro-mechanical testing systems capable of mounting a standard, Ø12.7 mm × Ø3.2 mm pin, scanning electron microscopy (SEM) pin stub (Ted Pella, Redding, CA, USA). Nine dogbones were made from an Fe-45Cu alloy additively manufactured using powder-fed laser-directed energy deposition (DED-LB). Testing showed that fracture was confined to the gauge section for all dogbones and that the fracture mode, ductile vs. brittle, was entirely dependent on the grain orientation relative to the loading direction. The analysis showed that the measured plastic strain to failure can vary from >11% (optimal geometry) to <1% (non-optimal geometry) in micro-tensile testing of high-tensile-strength (>1 GPa) metallic materials. Subsequently, a finite element analysis (FEA) was conducted to identify the improved dogbone geometries. A total of ten thousand dogbone geometries were tested, and their dimensions were defined by a set of four adjustable parameters (corner radius, load surface angle, load surface length, and dogbone head length). The gauge width and gauge length were fixed to 4 µm and 10 µm, respectively. Three-dimensional surface plots of the stress concentration as a function of two parameters were used to identify the optimal ranges of parameter values. The addition of maximum width and length constraints, measuring 25 µm and 30 µm, respectively, allowed us to identify an optimal geometry at load surface angles of 30° and 45°. Their respective dimensions (corner radius, load surface length, and dogbone head length) are, in µm, 12, 6, and 7 and 10, 7, and 7. Testing these two optimal geometries with a range of gauge lengths from 4 to 20 µm showed that smaller gauge lengths only slightly reduced the detrimental stress concentration outside the gauge section. However, smaller gauge lengths will notably improve the FIB surface polishing step as tapering is reduced with smaller dogbone lengths.

Chemistry↗

DOE OSTI2024

Chloride and Hydride Transfer as Keys to Catalytic Upcycling of Polyethylene into Liquid Alkanes

Abstract Transforming polyolefin waste into liquid alkanes through tandem cracking‐alkylation reactions catalyzed by Lewis‐acid chlorides offers an efficient route for single‐step plastic upcycling. Lewis acids in dichloromethane establish a polar environment that stabilizes carbenium ion intermediates and catalyzes hydride transfer, enabling breaking of polyethylene C−C bonds and forming C−C bonds in alkylation. Here, we show that efficient and selective deconstruction of low‐density polyethylene (LDPE) to liquid alkanes is achieved with anhydrous aluminum chloride (AlCl 3 ) and gallium chloride (GaCl 3 ). Already at 60 °C, complete LDPE conversion was achieved, while maintaining the selectivity for gasoline‐range liquid alkanes over 70 %. AlCl 3 showed an exceptional conversion rate of 5000 , surpassing other Lewis acid catalysts by two orders of magnitude. Through kinetic and mechanistic studies, we show that the rates of LDPE conversion do not correlate directly with the intrinsic strength of the Lewis acids or steric constraints that may limit the polymer to access the Lewis acid sites. Instead, the rates for the tandem processes of cracking and alkylation are primarily governed by the rates of initiation of carbenium ions and the subsequent intermolecular hydride transfer. Both jointly control the relative rates of cracking and alkylation, thereby determining the overall conversion and selectivity.

Zhang, Wei↗

DOE OSTI2024

Chloride and Hydride Transfer as Keys to Catalytic Upcycling of Polyethylene into Liquid Alkanes

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Measuring Neutron Polarisation in Deuteron Photo-disintegration with the CLAS Start Counter [Thesis]

Deuteron photo-disintegration (γd → γp) is a reaction that represents the simplest case in which nuclear and hadron physics models can be tested. Despite this, associated polarization analyses are limited in terms of angular coverage and energy ranges, especially in observables related to the recoil neutron. This is largely due to a lack in dedicated polarimetry equipment, and represents a roadblock in global progress to understand high-energy phenomena such as hexaquarks, and quark-gluon degrees of freedom. To address this problem, this PhD thesis pioneers a new methodology for the parasitic measurement of nucleon polarization using kinematic reconstruction of (spin-dependent) nucleon-nucleus scattering of reaction products, prior to their detection in large acceptance particle detector apparatus. Following this novel approach, which requires no dedicated polarimeter, a determination of the double polarization observable, $C^n_{x'}$, from deuteron photo-disintegration is presented, using Jefferson Lab’s CLAS detector. The analysis utilizes the (n,p) charge exchange reaction in CLAS’s "start counter" (plastic scintillator) to determine the final state neutron polarizations. The results present the first ever data for this observable above 0.7 GeV (photon beam energy) and significantly extend the angular range of the world data set. This new data is largely statistically consistent with the previous measurement of $C^n_{x'}$ by Bashkanov et al . in the overlapping energy range of 0.4-0.7 GeV. It is planned for the statistical accuracy of the presented result to be increased by the inclusion of additional data. The analysis herein serves as a key proof of concept for future applications, including a recommended similar analysis to be implemented with data from the more modern CLAS12 detector. This paves the way for a plethora of additional analyses using existing data sets that would provide crucial new constraints for hadron and nuclear physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Root phenotypes for improved nitrogen capture

Abstract Background Suboptimal nitrogen availability is a primary constraint for crop production in low-input agroecosystems, while nitrogen fertilization is a primary contributor to the energy, economic, and environmental costs of crop production in high-input agroecosystems. In this article we consider avenues to develop crops with improved nitrogen capture and reduced requirement for nitrogen fertilizer. Scope Intraspecific variation for an array of root phenotypes has been associated with improved nitrogen capture in cereal crops, including architectural phenotypes that colocalize root foraging with nitrogen availability in the soil; anatomical phenotypes that reduce the metabolic costs of soil exploration, improve penetration of hard soil, and exploit the rhizosphere; subcellular phenotypes that reduce the nitrogen requirement of plant tissue; molecular phenotypes exhibiting optimized nitrate uptake kinetics; and rhizosphere phenotypes that optimize associations with the rhizosphere microbiome. For each of these topics we provide examples of root phenotypes which merit attention as potential selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of soil hydrology and impedance, phenotypic plasticity, integrated phenotypes, in silico modeling, and breeding strategies using high throughput phenotyping for co-optimization of multiple phenes. Conclusions Substantial phenotypic variation exists in crop germplasm for an array of root phenotypes that improve nitrogen capture. Although this topic merits greater research attention than it currently receives, we have adequate understanding and tools to develop crops with improved nitrogen capture. Root phenotypes are underutilized yet attractive breeding targets for the development of the nitrogen efficient crops urgently needed in global agriculture.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Design and Construction of a High-Resolution Hodoscope for the GlueX Experiment with High-Statistics Analysis of the p0, ¿, and ¿1 Photoproduction Cross Sections from the RadPhi Experiment

Differential cross sections for forward-angle photoproduction of p0, ¿, and ¿ 1 pseudoscalar mesons were measured using data from the RadPhi experiment conducted in Hall B at Jef ferson Lab. RadPhi utilized a tagged bremsstrahlung photon beam incident on a stationary 9Be target, with a detector system configured to trigger on a recoil proton in coincidence with multiple neutral showers in the calorimeter. Events were reconstructed and subjected to kinematic constraints, with background suppressed via sideband subtraction guided by Monte Carlo modeling of background contributions. Cross sections were extracted over the photon energy range 4.4– 5.4 GeV and binned in invariant momentum transfer t, providing measurements from one of the first high-statistics experiments of forward ¿ and ¿1 pro duction from a nuclear target at these energies. Acceptance corrections were applied using a detailed GEANT-based simulation of the detector geometry and response. The resulting cross sections are consistent with 2020 CLAS results, when scaled by the number of protons in beryllium, and show broad agreement with other data and theoretical models. In parallel, a high-resolution photon tagger detector, the Tagger Microscope (TAGM), was designed, constructed, and commissioned for the GlueX experiment in Hall D at Jefferson Lab. The TAGM was developed to provide high-rate tagging capability in the coherent bremsstrahlung peak by detecting post-bremsstrahlung electrons across a one GeV range along the focal plane of the tagging spectrometer. The detector consists of a 5ˆ102 array of 2ˆ2 mm2 square BCF-20 plastic scintillating fibers thermally fused to BCF-98 light guide fibers optically coupled to silicon photomultipliers. These fibers are mounted in a precision machined framework enabling fine positional adjustments to maintain precise alignment with post-bremsstrahlung electron trajectories, while ensuring mechanical rigidity, thermal stability, optical isolation, minimal inactive area, and radiation shielding for electronics. The construction effort involved extensive testing of fiber quality, light transmission, thermal fusing, radiation hardness, and defect analysis using SEM and EDX techniques. Following its installation and commissioning, the TAGM became a critical component of the GlueX beamline, enabling high-rate tagging essential for studies of hybrid mesons and gluonic ex citations.

McIntyre, James [Univ. of Connecticut, Storrs, CT ↗

DOE OSTI2023

Path-Integrated X-Ray Images for Multi-Surface Digital Image Correlation (PI-DIC)

X-ray imaging offers unique possibilities for Digital Image Correlation (DIC), opening the door for full-field deformation measurements of a test article in complex environments where optical DIC suffers severe biases or is impossible. While X-ray DIC has been performed in the past with standard DIC codes designed for optical images, the path-integrated nature of X-ray images places constraints on the experimental setup, predominantly that only a single surface of interest moves/deforms. These requirements are difficult to realize for many practical situations and limit the amount of information that can be garnered in a single test. Other X-ray based diagnostics such as Digital Volume Correlation (DVC) and Projection DVC (P-DVC) overcome these obstacles, but DVC is limited to quasi-static tests, and both DVC and P-DVC necessitate high-resolution computed tomography (CT) scan(s) and often require a potentially invasive pattern throughout the volume of the specimen. Here this work presents a novel approach to measure time-resolved displacements and strains on multiple surfaces from a single series of 2D, path-integrated (PI) X-ray images, called PI-DIC. The principle of optical flow or conservation of intensity—the foundation of DIC—was reframed for path-integrated images, for an exemplar setup comprised of two plates moving and deforming independently. Synthetic images were generated for rigid translations, rigid rotations, and uniform stretches, where each plate underwent a unique motion/deformation. Experimental specimens were fabricated (either an aluminum plate with tantalum features or a plastic plate with steel features) and the two specimens were independently translated. PI-DIC was successfully demonstrated with the synthetic images and validated with the experimental images. Prescribed displacements were recovered for each plate from the single set of path-integrated, deformed images. Errors were approximately 0.02 px for the synthetic images with 1.5% image noise, and 0.05 px for the experimental images. These results provide the foundation for PI-DIC to measure motion and deformation of multiple, independent surfaces with subpixel accuracy from a single series of path-integrated X-ray images.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Linking constituent phase properties to ductility and edge stretchability of two DP 980 steels

Two DP 980 steels were characterized with multiple methods to determine its microstructure characteristics, tensile properties and edge stretchability. The first (DP980-B) is a commercial grade DP980 steel produced by AK Steel, while the second (DP980-T) is a modification of the first one by a tempering process. Both contain two individual phases: ferrite and martensite with body centered cubic (BCC) and tetragonal (BCT) crystal structure respectively. ASTM standard tensile tests were performed for both materials, revealing that DP980-B has higher work hardening and larger total elongation than DP980-T. Standard hole piercing and subsequent hole expansion and extrusion tests were also performed. The critical hole expansion ratio (HER) of hole pierced sheet at different nominal clearances, on the other hand, show an opposite trend: the HER of DP980-T almost doubles that of DP980-B. This indicates the tensile ductility and edge stretchability are determined by different mechanisms due to different deformation modes. The ductility of sheet metal during uniaxial tension is determined by deformation instability, i.e. necking, due to less constraint at the region of deformation and fracture will occur quickly after necking. The contribution of post-necking deformation to the total elongation is insignificant for the high strength grades such as DP980 steels. The ductility during hole-expansion, however, is mainly determined by material fracture behavior that is dependent on phase property disparity and material intrinsic fracture parameters. With the individual phase properties for both DP steels determined by in situ tensile tests under high energy X-ray diffraction, the results show that DP980-T steel has lower property disparities between the two phases than DP980-B steel, due to the tempering process. This explains why the DP980-T steel has higher HER than DP980-B steel: lower phase disparity will lead to less local deformation during loading. The higher work hardening rate for DP980-B steel contributes to its higher uniform elongation compared with DP980-T steel based on the maximum load condition of deformation instability. An integrated finite element simulation framework for studying hole expansion is also presented here, based on the calculated individual phase properties from the combined high energy x-ray diffraction (HEXRD) and elastic plastic self-consistent modeling. The simulation results correlate well with the experimental results on the HER difference between the two materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Effect of Specimen Thickness on Fracture Toughness and Plane Stress to Plane Strain Transition in Medium-Density Polyethylene

This study investigates the effect of specimen thickness on fracture toughness and the transition from plane stress to plane strain conditions in Medium-Density Polyethylene (MDPE) using Single Edge Notched Bend (SENB) specimens. Three thickness groups (7.5 mm, 9.0 mm, and 12.1 mm) were tested following ASTM D5045 protocol. Conditional stress intensity factors (KQ) increased from 2.2 MPavm to 2.8 MPavm with increasing thickness, demonstrating significant size dependency. Confocal microscopy revealed a 34% reduction in maximum crack tip opening displacement (CTOD) from 0.478 mm to 0.314 mm as thickness increased, with plastic zone lateral extent decreasing by 32%. This quantitative evidence validates Irwin's theoretical prediction of plastic zone size transition from plane stress r_y˜ (1/2p) (K_I/s_y )^2 to plane strain conditions r_y˜ (1/6p) (K_I/s_y )^2.Scanning electron microscopy confirmed progressive suppression of shear lips and evolution from ductile tearing with extensive polymer chain drawing in thin specimens to localized crazing in thick specimens. Despite all specimens satisfying the ASTM D5045 criterion (B = 2.5(KQ/s_y )^2 ) ,residual shear lips persisted even in the thickest specimens, demonstrating that nominal size requirements alone are insufficient for achieving complete plane strain conditions in highly ductile polymers. The findings emphasize the necessity of integrated analytical and morphological assessment for valid fracture toughness characterization, with critical implications for life assessment and integrity prediction in thick-section polymer components such as natural gas distribution pipelines.

Medium-Density Polyethylene↗

DOE OSTI2020

Topologically derived dislocation theory for twist and stretch moiré superlattices in bilayer graphene

In this work, we develop a continuum dislocation description of twist and stretch moiré superlattices in two-dimensional material bilayers. The continuum formulation is based on the topological constraints introduced by the periodic dislocation network associated with the moiré structure. The approach is based on solving analytically for the structural distortion and displacement fields that satisfy the topological constraints and that minimize the total energy. The total energy is described by both the strain energy of each individual distorted layer and a Peierls-Nabarro-like interfacial contribution arising from stacking disregistry. The dislocation core emerges naturally within the formalism as a result of the competition between the two contributions. The approach presented here captures the structure and energetics of twist and stretch moiré superlattices of dislocations with arbitrary direction and character, without assuming an analytical solution a priori and while accounting naturally for dislocation-dislocation image interactions. In comparisons to atomistic simulations using classical potentials, the maximum structure deviation is 6%, while the maximum line energy deviation is 0.019 eV/Å. Several applications of our model are shown, including predicting the variation of structure with twist angle and describing dislocation line tension and junction energies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science Applications

Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods is that the resulting model requires significantly less data to train. By incorporating physical rules into the machine learning formulation itself, the predictions are expected to be physically plausible. Gaussian process (GP) is perhaps one of the most common methods in machine learning for small datasets. In this paper, we investigate the possibility of constraining a GP formulation with monotonicity on three different material datasets, where one experimental and two computational datasets are used. The monotonic GP is compared against the regular GP, where a significant reduction in the posterior variance is observed. The monotonic GP is strictly monotonic in the interpolation regime, but in the extrapolation regime, the monotonic effect starts fading away as one goes beyond the training dataset. Imposing monotonicity on the GP comes at a small accuracy cost, compared to the regular GP. The monotonic GP is perhaps most useful in applications where data are scarce and noisy, and monotonicity is supported by strong physical evidence.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Modular machine learning-based elastoplasticity: Generalization in the context of limited data

The development of highly accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions and from the viewpoint of data availability, verification, and validation. Recently, data-driven modeling approaches have been proposed that aim to establish stress-evolution laws that avoid user-chosen functional forms by relying on machine learning representations and algorithms. However, these approaches not only require a significant amount of data but also need data that probes the full stress space with a variety of complex loading paths. Furthermore, they rarely enforce all necessary thermodynamic principles as hard constraints. Hence, they are in particular not suitable for low-data or limited-data regimes, where the first arises from the cost of obtaining the data and the latter from the experimental limitations of obtaining labeled data, which is commonly the case in engineering applications. In this work, we discuss a hybrid framework that can work on a variable amount of data by relying on the modularity of the elastoplasticity formulation where each component of the model can be chosen to be either a classical phenomenological or a data-driven model depending on the amount of available information and the complexity of the response. The method is tested on synthetic uniaxial data coming from simulations as well as cyclic experimental data for structural materials. The discovered material models are found to not only interpolate well but also allow for accurate extrapolation in a thermodynamically consistent manner far outside the domain of the training data. This ability to extrapolate from limited data was the main reason for the early and continued success of phenomenological models and the main shortcoming in machine learning-enabled constitutive modeling approaches. Training aspects and details of the implementation of these models into Finite Element simulations are discussed and analyzed.

42 ENGINEERING↗