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At least 127 records · Page 7

Sensitivity Enhancement and Random Telegraph Noise in Magnetic Tunnel Junctions with Compensated Anisotropy

We demonstrate the manipulation of perpendicular magnetic anisotropy (PMA) in magnetic tunnel junctions (MTJs) by varying the layer stacks and temperature. PMA is tuned to compensate the shape anisotropy, giving a nonhysteretic magnetic response, a noteworthy sensitivity enhancement, and a field detectability of 1.8 nT/$\sqrt{Hz}$ at 100 kHz. Such a method is further exemplified in multiple MTJs, providing a solution to obtain desired sensitivities and operating temperatures. Additionally, the electronic noise of this MTJ is revealed as a random telegraph noise (RTN) due to a generation-recombination process. In conclusion, the observed voltage-dependent RTN could potentially be applied to true random number generators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ab initio calculations of monopole sum rules: From finite nuclei to infinite nuclear matter

We compute moments of the isoscalar monopole response of 𝑁 = 𝑍 closed-shell nuclei based on chiral nucleon-nucleon plus three-nucleon interactions. We employ the random-phase approximation (RPA) and two ab initio many-body approaches, the in-medium similarity renormalization group (IMSRG) and coupled-cluster theory (CC). In the IMSRG framework, the moments are obtained as ground-state expectation values, whereas in the CC approach, they are evaluated through excited-state calculations. We find good agreement between the IMSRG and CC results across all nuclei studied. RPA provides a reasonable approximation to the correlated methods if the interaction is soft. From the calculated moments, we extract average energies of the monopole response, compute finite-nucleus incompressibilities, and estimate the incompressibility of symmetric nuclear matter by a fit to a leptodermous expansion. Our extrapolated values are lower than those obtained in nuclear-matter calculations with the same interactions, but the values are consistent with phenomenological ranges.

Bonaiti, Francesca [Michigan State Univ., East Lan↗

The response field and the saddle points of quantum mechanical path integrals

Highlights: • Moyal quantum mechanics and Marinov’s path integral. • Classical and semiclassical limits of Marinov’s path integral. • Oscillating functional integrals. • Instantons of the Marinov’s path integral. In quantum statistical mechanics, Moyal’s equation governs the time evolution of Wigner functions and of more general Weyl symbols that represent the density matrix of arbitrary mixed states. A formal solution to Moyal’s equation is given by Marinov’s path integral. In this paper we demonstrate that this path integral can be regarded as the natural link between several conceptual, geometric, and dynamical issues in quantum mechanics. A unifying perspective is achieved by highlighting the pivotal role which the response field, one of the integration variables in Marinov’s integral, plays for pure states even. The discussion focuses on how the integral’s semiclassical approximation relates to its strictly classical limit; unlike for Feynman type path integrals, the latter is well defined in the Marinov case. The topics covered include a random force representation of Marinov’s integral based upon the concept of “Airy averaging”, a related discussion of positivity-violating Wigner functions describing tunneling processes, and the role of the response field in maintaining quantum coherence and enabling interference phenomena. The double slit experiment for electrons and the Bohm–Aharonov effect are analyzed as illustrative examples. Furthermore, a surprising relationship between the instantons of the Marinov path integral over an analytically continued (“Wick rotated”) response field, and the complex instantons of Feynman-type integrals is found. The latter play a prominent role in recent work towards a Picard–Lefschetz theory applicable to oscillatory path integrals and the resurgence program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Capturing the softening in T91 steel annealed with molten LBE through interfacial gradient plasticity

In order to study the effect of annealing with molten lead–bismuth eutectic alloy (mLBE) on the mechanical properties of T91 steel, micropillar compression tests were analyzed through the consideration of mechanical interface energy terms within gradient plasticity. The stress–strain curves of the micropillars showed significant stochastic effects, characterized by a different elastic and plastic behavior response for each pillar. Among the various pillars, some exhibited a similar trilinear behavior. Scanning electron microscopy (SEM) images of these specimens demonstrated localized slip deformation and slip planes after compression, while transmission electron microscopy (TEM) images showed the presence of a severe slip zone along the random grain boundaries (RGBs), indicating that the GBs played a dominant role in the deformation/slip. By employing interfacial gradient plasticity that can explicitly account for the presence of GBs, the trilinear response was captured, allowing for the determination of the mechanical interface parameter. As anticipated the pillars which underwent severe slip at the GBs had a lower value for the mechanical interface parameter. Finally, annealing with mLBE can, therefore, in some cases result in softening in the overall stress–strain, as it lowers the mechanical interface energy of GBs.

36 MATERIALS SCIENCE↗

Memory row recording for mitigating crosstalk in dynamic random access memory

A method includes adding a set of one or more victim rows to a first probabilistic filter and to a second probabilistic filter, in response to a memory access request, identifying a candidate victim row adjacent to a memory address specified by a memory access request, identifying the candidate victim row as a victim row in the set of victim rows based on performing a lookup of the candidate victim row in a selected filter, where the selected filter includes one of the first probabilistic filter and the second probabilistic filter, in response to identifying the candidate row as the victim row, enabling a row hammering countermeasure, clearing the first probabilistic filter in each of a first set of time periods, and clearing the second probabilistic filter in each of a second set of time periods interleaved with the first set of time periods.

SeyedzadehDelcheh, SeyedMohammad↗

A functional global sensitivity measure and efficient reliability sensitivity analysis with respect to statistical parameters

Sensitivity analysis and reliability assessment are two important aspects of structural and system safety. Epistemic uncertainty with respect to probabilistic model of input parameters due to lack of knowledge is present in many scarce-data applications and complicates the characterization of uncertainty in model response. In this article, we present two importance measures to evaluate the impact of distribution parameters on the probability distribution function (PDF) of the output and the failure probability. The epistemic uncertainty associated with the distribution parameters is modeled as random variables. Additionally, a modified extended polynomial chaos expansion (MEPCE) approach is introduced in which aleatory and epistemic random variables are modeled and propagated simultaneously while allowing the separate assessment for any single epistemic variable. A MEPCE-based kernel density estimation (KDE) construction provides a composite map from each epistemic variable to the response PDF. The functional global sensitivity index of the PDF with respect to the distribution parameters is thus derived, as a function of output, which is both more informative and more efficient than standard scalar sensitivity measures. Reliability sensitivity indices can be readily evaluated by integrating the global sensitivity index function over the failure zone. Three illustrative examples are used to demonstrate the proposed methodology.

42 ENGINEERING↗

Moisture availability mediates the relationship between terrestrial gross primary production and solar-induced chlorophyll fluorescence: Insights from global-scale variations

Effective use of solar-induced chlorophyll fluorescence (SIF) to estimate and monitor gross primary production (GPP) in terrestrial ecosystems requires a comprehensive understanding and quantification of the relationship between SIF and GPP. To date, this understanding is incomplete and somewhat controversial in the literature. Here we derived the GPP/SIF ratio from multiple data sources as a diagnostic metric to explore its global-scale patterns of spatial variation and potential climatic dependence. We found that the growing season GPP/SIF ratio varied substantially across global land surfaces, with the highest ratios consistently found in boreal regions. Spatial variation in GPP/SIF was strongly modulated by climate variables. The most striking pattern was a consistent decrease in GPP/SIF from cold-and-wet climates to hot-and-dry climates. We propose that the reduction in GPP/SIF with decreasing moisture availability may be related to stomatal responses to aridity. Furthermore, we show that GPP/SIF can be empirically modeled from climate variables using a machine learning (random forest) framework, which can improve the modeling of ecosystem production and quantify its uncertainty in global terrestrial biosphere models. Finally, our results point to the need for targeted field and experimental studies to better understand the patterns observed and to improve the modeling of the relationship between SIF and GPP over broad scales.

59 BASIC BIOLOGICAL SCIENCES↗

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗

Trivalent mosaic or consensus HIV immunogens prime humoral and broader cellular immune responses in adults

Mosaic and consensus HIV-1 immunogens provide two distinct approaches to elicit greater breadth of coverage against globally circulating HIV-1 and have shown improved immunologic breadth in nonhuman primate models. This double-blind randomized trial enrolled 105 healthy HIV-uninfected adults who received 3 doses of either a trivalent global mosaic, a group M consensus (CON-S), or a natural clade B (Nat-B) gp160 env DNA vaccine followed by 2 doses of a heterologous modified vaccinia Ankara–vectored HIV-1 vaccine or placebo. We performed prespecified blinded immunogenicity analyses at day 70 and day 238 after the first immunization. T cell responses to vaccine antigens and 5 heterologous Env variants were fully mapped. Env-specific CD4 + T cell responses were induced in 71% of the mosaic vaccine recipients versus 48% of the CON-S recipients and 48% of the natural Env recipients. The mean number of T cell epitopes recognized was 2.5 (95% CI, 1.2–4.2) for mosaic recipients, 1.6 (95% CI, 0.82–2.6) for CON-S recipients, and 1.1 (95% CI, 0.62–1.71) for Nat-B recipients. Mean breadth was significantly greater in the mosaic group than in the Nat-B group using overall (P = 0.014), prime-matched (P = 0.002), heterologous (P = 0.046), and boost-matched (P = 0.009) measures. Overall T cell breadth was largely due to Env-specific CD4 + T cell responses. Priming with a mosaic antigen significantly increased the number of epitopes recognized by Env-specific T cells and enabled more, albeit still limited, cross-recognition of heterologous variants. Mosaic and consensus immunogens are promising approaches to address global diversity of HIV-1.

60 APPLIED LIFE SCIENCES↗

Structure Tuning, Strong Second Harmonic Generation Response, and High Optical Stability of the Polar Semiconductors Na 1- x K x AsQ 2

We report the mixed cation compounds Na 1-x K x AsSe 2 (x = 0.8, 0.65, 0.5) and Na 0.1 K 0.9 AsS 2 crystallize in the polar noncentrosymmetric space group Cc. The AAsQ(2) (A = alkali metals, Q = S, Se) family features one-dimensional (1D) 1 / ∞ [AQ 2 - ] chains comprising corner-sharing pyramidal AQ 3 units in which the packing of these chains is dependent on the alkali metals. The parallel 1 / ∞ [AQ(2) - ] chains interact via short As ∙∙∙Se contacts, which increase in length when the fraction of K atoms is increased. The increase in the As ∙∙∙Se interchain distance increases the band gap from 1.75 eV in γ-NaAsSe 2 to 2.01 eV in Na 0.35 K 0.65 AsSe 2 , 2.07 eV in Na 0.2 K 0.8 AsSe 2 , and 2.18 eV in Na 0.1 K 0.9 AsS 2 . The Na 1-x K x AsSe 2 (x = 0.8, 0.65) compounds melt congruently at approximately 316 °C. Wavelength-dependent second harmonic generation (SHG) measurements on powder samples of Na 1-x K x AsSe 2 (x = 0.8, 0.65, 0.5) and Na 0.1 K 0.9 AsS 2 suggest that Na 0.2 K 0.8 AsSe 2 and Na 0.1 K 0.9 AsS 2 have the highest SHG response and exhibit significantly higher laser-induced damage thresholds (LIDTs). Theoretical SHG calculations on Na 0.5 K 0.5 AsSe 2 confirm its SHG response with the highest value of d 33 = 22.5 pm/V χ 333 (2) = 45.0 pm/V). The effective nonlinearity for a randomly oriented powder is calculated to be d eff = 18.9 pm/V χ eff (2) = 37.8 pm/V), which is consistent with the experimentally obtained value of d eff = 16.5 pm/V χ eff (2) = 33.0 pm/V). Three-photon absorption is the dominant mechanism for the optical breakdown of the compounds under intense excitation at 1580 nm, with Na 0.2 K 0.8 AsSe 2 exhibiting the highest stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data?

Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0, may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material and neutron diagnosed subcritical experiments. Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Computational Model for Microballistic Perforation of Multilayer Graphene

The peridynamic theory of solid mechanics is applied to the continuum modeling of the impact of small, high-velocity silica spheres on multilayer graphene targets. The model treats the laminate as a brittle elastic membrane. The material model includes separate failure criteria for the initial rupture of the membrane and for propagating cracks. Material variability is incorporated by assigning random variations in elastic properties within Voronoi cells. The computational model is shown to reproduce the primary aspects of the response observed in experiments, including the growth of a family of radial cracks from the point of impact.

36 MATERIALS SCIENCE↗

Temporal regulation of cold transcriptional response in switchgrass

Switchgrass low-land ecotypes have significantly higher biomass but lower cold tolerance compared to up-land ecotypes. Understanding the molecular mechanisms underlying cold response, including the ones at transcriptional level, can contribute to improving tolerance of high-yield switchgrass under chilling and freezing environmental conditions. Here, by analyzing an existing switchgrass transcriptome dataset, the temporal cis- regulatory basis of switchgrass transcriptional response to cold is dissected computationally. We found that the number of cold-responsive genes and enriched Gene Ontology terms increased as duration of cold treatment increased from 30 min to 24 hours, suggesting an amplified response/cascading effect in cold-responsive gene expression. To identify genomic sequences likely important for regulating cold response, machine learning models predictive of cold response were established using k -mer sequences enriched in the genic and flanking regions of cold-responsive genes but not non-responsive genes. These k -mers, referred to as putative cis -regulatory elements (pCREs) are likely regulatory sequences of cold response in switchgrass. There are in total 655 pCREs where 54 are important in all cold treatment time points. Consistent with this, eight of 35 known cold-responsive CREs were similar to top-ranked pCREs in the models and only these eight were important for predicting temporal cold response. More importantly, most of the top-ranked pCREs were novel sequences in cold regulation. Our findings suggest additional sequence elements important for cold-responsive regulation previously not known that warrant further studies.

60 APPLIED LIFE SCIENCES↗

Is Mini Beam Ready for Human Trials? Results of Randomized Study of Treating De-Novo Brain Tumors in Canines Using Linear Accelerator Generated Mini Beams

The main challenge in treating malignant brain neoplasms lies in eradicating the tumor while minimizing treatmentrelated damage. Conventional radiation treatments are associated with considerable side effects. Synchrotron generated micro-beam radiation (SMBRT) has shown to preserve brain architecture while killing tumor cells, however physical characteristics and limited facility access restrict its use. We have created a new clinical device which produces mini beams on a linear accelerator, to provide a new type of treatment called mini-beam radiation therapy (MBRT). The objective of this study is to compare the treatment outcomes of linear accelerator based MBRT versus standard radiation treatment (SRT), to evaluate the tumor response and the treatment-related changes in the normal brain with respect to each treatment type. Pet dogs with de-novo brain tumors were accrued for treatment. Dogs were randomized between standard fractionated stereotactic (9 Gy in 3 fractions) radiation treatment vs. a single fraction of MBRT (26 Gy mean dose). Dogs were monitored after treatment for clinical assessment and imaging. When the dogs were euthanized, a veterinary pathologist assessed the radiation changes and tumor response. We accrued 16 dogs, 8 dogs in each treatment arm. In the MBRT arm, 71% dogs achieved complete pathological remission. The radiation-related changes were all confined to the target region. Structural damage was not observed in the beam path outside of the target region. In contrast, none of the dogs in control group achieved remission and the treatment related damage was more extensive. Therapeutic superiority was observed with MBRT, including both tumor control and the normal structural preservation. The MBRT findings are suggestive of an immune related mechanism which is absent in standard treatment. These findings together with the widespread availability of clinical linear accelerators make MBRT a promising research topic to explore further treatment and clinical trial opportunities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Randomly Layered Superstructure of In 2 O 3 Truncated Nano-Octahedra and Its High-Pressure Behavior

This study outlines the synthesis and characterization of a unique superlattice composed of vertex-truncated indium oxide (In 2 O 3 ) nano-octahedra, along with an exploration of its response to high-pressure conditions. Here, using a bright-field transmission electron microscope (BF-TEM), we determined an average circumradius of 15.2 nm for these octahedral building blocks. The resilience and response of the superlattice to pressure variations, peaking at 18.01 GPa, were examined by employing synchrotron-based Wide-Angle X-ray Scattering (WAXS) and Small-Angle X-ray Scattering (SAXS) techniques. The WAXS data revealed no phase transitions, reinforcing the stability of the 2D superlattice comprised of random layers in alignment with a 2D p31m symmetry. Notably, the SAXS data unveiled a pressure-induced, irreversible octahedron translation and ligand interaction occurring within the random layer. Through our examination of these pressure-sensitive behaviors, we identified a distinctive translation model inherent to octahedra and observed modulation in the superlattice cell parameter induced by pressure. This research signifies a noteworthy progression in deciphering the intricate behaviors of 2D superlattices under high-pressure conditions.

36 MATERIALS SCIENCE↗

Peridynamic Model for Microballistic Perforation of Multilayer Graphene

The peridynamic theory of solid mechanics is applied to the continuum modeling of the impact of small, high-velocity silica spheres on multilayer graphene targets. The model treats the laminate as a brittle elastic membrane. The material model includes separate failure criteria for the initial rupture of the membrane and for propagating cracks. Material variability is incorporated by assigning random variations in elastic properties within Voronoi cells. Here, the computational model is shown to reproduce the primary aspects of the response observed in experiments, including the growth of a family of radial cracks from the point of impact.

42 ENGINEERING↗

Randomized control trial of moderate dose vitamin D alters microbiota stability and metabolite networks in healthy adults

ABSTRACT Evidence indicates that both vitamin D and the gut microbiome are involved in the process of colon carcinogenesis. However, it is unclear what effects supplemental vitamin D 3 has on the gut microbiome and its metabolites in healthy adults. We conducted a double-blind, randomized, placebo-controlled trial to identify the acute and long-term microbiota structural and metabolite changes that occur in response to a moderate dose (4,000 IU) of vitamin D 3 for 12 weeks in healthy adults. Our results demonstrated a significant increase in serum 25-hydroxy-vitamin D (25(OH)D) in the treatment group compared to placebo ( P < 0.0001). Vitamin D 3 significantly increased compositional similarity ( P < 0.0001) in the treatment group, and enriched members of the Bifidobacteriaceae family. We also identified a significant inverse relationship between the percent change in serum 25(OH)D and microbial stability in the treatment group ( R = −0.52, P < 0.019). Furthermore, vitamin D 3 supplementation resulted in notable metabolic shifts, in addition to resulting in a drastic rewiring of key gut microbial-metabolic associations. In conclusion, we show that a moderate dose of vitamin D 3 among healthy adults has unique acute and persistent effects on the fecal microbiota, and suggest novel mechanisms by which vitamin D may affect the host-microbiota relationship. IMPORTANCE Preventative measures to reduce the rise in early-onset colorectal cancer are of critical need. Both vitamin D, dietary and serum levels, and the gut microbiome are implicated in the etiology of colorectal cancer. By understanding the intimate relationship between vitamin D, the gut microbiome, and its metabolites, we may be able to identify key mechanisms that can be targeted for intervention, including inflammation and metabolic dysfunction. Furthermore, the similarity of vitamin D to cholesterol, which is metabolized by the gut microbiome, gives precedence to its ability to produce metabolites that can be further studied and leveraged for controlling colorectal cancer incidence and mortality.

Wyatt, Madhur↗

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗