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At least 811 records · Page 45

Broad SARS-CoV-2 neutralization by monoclonal and bispecific antibodies derived from a Gamma-infected individual

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has remained a medical threat due to the evolution of multiple variants that acquire resistance to vaccines and prior infection. Therefore, it is imperative to discover monoclonal antibodies (mAbs) that neutralize a broad range of SARS-CoV-2 variants. A stabilized spike glycoprotein was used to enrich antigen-specific B cells from an individual with a primary Gamma variant infection. Five mAbs selected from those B cells showed considerable neutralizing potency against multiple variants, with COVA309-35 being the most potent against the autologous virus, as well as Omicron BA.1 and BA.2, and COVA309-22 having binding and neutralization activity against Omicron BA.4/5, BQ.1.1, and XBB.1. When combining the COVA309 mAbs as cocktails or bispecific antibodies, the breadth and potency were improved. In addition, the mechanism of cross-neutralization of the COVA309 mAbs was elucidated by structural analysis. Altogether these data indicate that a Gamma-infected individual can develop broadly neutralizing antibodies.

60 APPLIED LIFE SCIENCES↗

Predicting transcription factor activity using prior biological information

Dysregulation of normal transcription factor activity is a common driver of disease. Therefore, the detection of aberrant transcription factor activity is important to understand disease pathogenesis. We have developed Priori, a method to predict transcription factor activity from RNA sequencing data. Priori has two key advantages over existing methods. First, Priori utilizes literature-supported regulatory information to identify transcription factor-target gene relationships. It then applies linear models to determine the impact of transcription factor regulation on the expression of its target genes. Second, results from a third-party benchmarking pipeline reveals that Priori detects aberrant activity from 124 single-gene perturbation experiments with higher sensitivity and specificity than 11 other methods. We applied Priori and other top-performing methods to predict transcription factor activity from two large primary patient datasets. Our work demonstrates that Priori uniquely discovered significant determinants of survival in breast cancer and identified mediators of drug response in leukemia.

59 BASIC BIOLOGICAL SCIENCES↗

Exchange bias and interface-related effects in two-dimensional van der Waals magnetic heterostructures: Open questions and perspectives

The exchange bias (EB) effect is known as a fundamentally and technologically important magnetic property of a magnetic bilayer film. It is manifested as a horizontal shift in a magnetic hysteresis loop of a film subject to cooling in the presence of a magnetic field. The EB effect in van der Waals (vdW) heterostructures offers a novel approach for tuning the magnetic properties of the newly discovered single-layer magnets, as well as adds a new impetus to magnetic vdW heterostructures. Indeed, intriguing EB effects have recently been reported in a variety of low-dimensional vdW magnetic systems ranging from a weakly interlayer-coupled vdW magnet (e.g., Fe 3 GeTe 2 ) to a bilayer composed of two different magnetic vdW materials (e.g., Fe 3 GeTe 2 /CrCl 3 , Fe 3 GeTe 2 /FePS 3 , Fe 3 GeTe 2 /MnPS 3 , Fe 3 GeTe 2 /CrSe, Fe 3 GeTe 2 /CrOCl, Fe 3 GeTe 2 /CoPc, Fe 5 GeTe 2 /FePS 3 ), to bilayers of two different vdW defective magnets (e.g., VSe 2 /MoS 2 ), or to metallic ferromagnet/vdW defective magnet interfaces (e.g., Fe/MoS 2 ). Despite their huge potential in spintronic device applications, the physical origins of the observed EB effects have remained elusive to researchers. Here, we present here a critical review of the EB effect and associated phenomena such as magnetic proximity (MP) in various vdW heterostructure systems and propose approaches to addressing some of the emerging fundamental questions.

2D magnets↗

Assessment of the reason for the vitrification of a wall at a hillfort. The example of Broborg in Sweden

It was discovered around 250 years ago that some of the rock material in the walls of some hillforts had been subjected to such high temperature that it had vitrified. This prompted a debate as to the reason for it that is still going on today: did the vitrification come about as a result of hostile action, by accident, or for the purpose of constructing the fort? The present paper is based on the prerequisite that hillforts are different, and therefore should be evaluated individually. All identifiable factors of interest should be included, and especially those that might disprove any alternative. Thus, incentives, competence and petrographic aspects were evaluated for the hillfort Broborg (dated Migration Period, in Sweden A.D. 400 - 550), and it is concluded that the vitrification came about for the purpose of constructing the fort. This capability was lost when mortar was introduced half a millennium later.

42 ENGINEERING↗

Key Elements of Auroral Substorm Development and their Relationship to Recent Observations of Detached Sub-Auroral Phenomena Including STEVE-like Emissions

Since Akasofu introduced the concept of the substorm in 1964, numerous refinements have been added to the phenomenological model of how auroral substorms develop. Here, we review several of the most important of these including; polar cap patches, intensifications of the Polar Activated Band (PAB) at the poleward edge of the bulge, the development of new arcs poleward, the generation of auroral streamers, the evolution of streamers into auroral torches and omega bands, the association of streamers with particle injection and BBF activity in the tail, and wedgelet-like magnetic perturbations on the ground. We also review the concept of “contact breakups” which are breakups that appear to be triggered by the arrival of streamer-like forms in the equatorward regions of the oval. Finally, we remind the community that the addition of detached sub-auroral emissions was made to the phenomenological picture of substorm develop in the late 1960s along with the concept of auroral streamers. Newer observations of detached sub-auroral (STEVE-like emissions) from the Viking/UVI and POLAR/VIS imagers are presented which confirm that they are east-west aligned bands of emission that separate away from the equatorward edge of the auroral oval in response to intensifications of the poleward edge of the bulge and subsequent streamer production. We propose a new model for the formation of detached sub-auroral (STEVE-like) emissions in which a non-linear growth of a SAPS-driven instability (e.g. like the shear-flow/ballooning instability) at the plasmapause results in the disruption of the boundary separating hot plasma sheet particle from the cold plasmaspheric plasma. It is proposed that the resulting intermixing of plasma populations leads to both the observed STEVE-like emissions and also provides a source of cold plasma on open drift paths that can feed the long-lived drainage plumes that have recently been discovered.

58 GEOSCIENCES↗

Oral delivery of a functional algal-expressed TGF-β mimic halts colitis in a murine DSS model

Inflammatory bowel disease (IBD) is a set of immunological disorders which can generate chronic pain and fatigue associated with the inflammatory symptoms. The treatment of IBD remains a significant hurdle with current therapies being only partially effective or having significant side effects, suggesting that new therapies that elicit different modes of action and delivery strategies are required. TGM1 is a TGF-β mimic that was discovered from the intestinal helminth parasite Heligmosomoides polygyrus and is thought to be produced by the parasite to suppress the intestinal inflammation response to help evade host immunity, making it an ideal candidate to be developed as a novel anti-inflammatory bio-therapeutic. Here we utilized the expression system of the edible green algae Chlamydomonas reinhardtii in order to recombinantly produce active TGM1 in a form that could be ingested. C. reinhardtii robustly expressed TGM1, and the resultant recombinant protein is biologically active as measured by regulatory T cell induction. When delivered orally to mice, the algal expressed TGM1 is able to ameliorate weight loss, lymphadenopathy, and disease symptoms in a mouse model of DSS-induced colitis, demonstrating the potential of this biologic as a novel treatment of IBD.

09 BIOMASS FUELS↗

Calorimetric metal vapor adsorption energies for characterizing industrial catalyst support materials

Many important catalysts and electro-catalysts for energy and environmental technologies involve late transition metal atoms and nanoparticles dispersed across the surface of high-surface-area support materials, for example, oxide nanoparticles. The surface reactivity and long-term stability against deactivation of these materials depends strongly on the strength of bonding of the metal atom and nanoparticles to the support surface. Here, we introduce a novel calorimetry method that implements a LiTaO 3 crystal for heat detection and extends metal adsorption calorimetry to surfaces of nanomaterials that are deposited from liquid solutions, as is typical when preparing industrial catalyst supports. This allows one to measure the strength of metal atom bonding and the adhesion energy of metal nanoparticles to clean surfaces of technologically relevant catalyst supports. We demonstrate that here by measuring the heat of Ag vapor adsorption onto the clean surfaces of high-surface-area TiO 2 anatase powdered support materials (i.e., 5-nm-diameter nanoparticles). These heats of adsorption show a pulse-to-pulse standard deviation of only 9.3 kJ/mol (3.3%) for pulses containing only 1% of a monolayer of Ag vapor, with potential for a 5-fold reduction in noise if used with another metal evaporator. The calorimeter was also proven to work well measuring heats of Ag adsorption on calcium niobate(001) nanosheets deposited as thin films from liquid solution. Here, this calorimeter opens up the possibility of using metal adsorption calorimetry to screen catalyst support materials for the strengths with which they bind metal atoms and metal nanoparticles, offering new opportunities to discover better support materials or for basic scientific study of structure / function relationships with respect to metal / support bond energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure sensitivity of ammonia electro-oxidation on transition metal surfaces: A first-principles study

Ammonia electro-oxidation is a promising catalytic reaction for application in alkaline fuel cells. In this paper we study the trends in this reaction on the (1 0 0) facet of eight fcc transition metals: Au, Ag, Cu, Pt, Pd, Ni, Ir, and Rh. We calculate from first-principles (DFT-GGA-PW91) the energetics for two mechanisms: (i) the N + N mechanism and (ii) the Gerischer-Mauerer mechanism. The onset potentials for both mechanisms are provided for both (1 0 0) and (1 1 1) facets. We also calculate the activation energies for the N-N bond-making non-Faradaic events on Cu, Pt, Pd, Ni, Ir, and Rh. We discover that N* – which is considered a poison for Pt(1 1 1) – is a reactive intermediate on Pt(1 0 0), allowing for a facile dimerization to N2 on Pt(1 0 0) at high potentials. We draw similar analyses for the structure sensitivity on the other metals, and we conclude with some general principles to guide catalyst design for this reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ligand-coordination effects on the selective hydrogenation of acetylene in single-site Pd-ligand supported catalysts

The selective hydrogenation of acetylene to ethylene is a critical step in the synthesis of polyethylenes. Achieving high conversion to ethylene without over-hydrogenation to ethane is a challenge that requires control of the transition metal site, which we achieve through a ligand-coordinated supported catalyst (LCSC) strategy. Using Pd catalysts coordinated to 1,10-phenanthroline-5,6-dione (PDO) ligands on CeO2 supports, we have discovered that the reaction selectivity depends strongly on the ligand:metal ratio with higher selectivity when more ligand is present in the catalyst. Catalyst structure was examined by extended X-ray absorption fine structure spectroscopy, transmission electron microscopy, and CO adsorption, which indicate single-atom character of the Pd. The ligand:metal ratio is determined by Xray photoelectron spectroscopy measurements and correlated with hydrogenation reactions under steady-state flow conditions to examine trends in hydrogenation activity and selectivity. Those trends can be better understood by density functional theory calculations that indicate hydrogen binding on the ligand to guide reaction selectivity toward the desired ethylene hydrogenation product. Here these results demonstrate the importance of considering the dynamic character of LCSCs and inform the design of future single-site heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational descriptor for electrochemical currents of carbon dioxide reduction on Cu facets

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO 2 R) reduction that produce valuable hydrocarbons and oxygenates. In this work, leveraging density functional theory calculations for the CO adsorption energy ΔE CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE CO and the experimentally measured CO 2 R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining ab initio thermodynamics of early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically controlling step. Beyond the general CO adsorption energy that only shows a linear trend with CO 2 R activity, we show that the reaction free energy of CO* → CHO* is the descriptor for the overall CO 2 R activity for Cu facets, as it displays a volcano relationship with the experimental current. Importantly, we show that high step and kink density of the Cu terminations not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. In addition, we explain that the high activity of (741) is due to its relatively low hydrogen evolution reaction activity compared with the other Cu surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

In this work, we introduce a data-driven approach to building reduced dynamical models through manifold learning; the reduced latent space is discovered using Diffusion Maps (a manifold learning technique) on time series data. A second round of Diffusion Maps on those latent coordinates allows the approximation of the reduced dynamical models. This second round enables mapping the latent space coordinates back to the full ambient space (what is called lifting); it also enables the approximation of full state functions of interest in terms of the reduced coordinates. In our work, we develop and test three different reduced numerical simulation methodologies, either through pre-tabulation in the latent space and integration on the fly or by going back and forth between the ambient space and the latent space. The data-driven latent space simulation results, based on the three different approaches, are validated through (a) the latent space observation of the full simulation through the Nyström Extension formula, or through (b) lifting the reduced trajectory back to the full ambient space, via Latent Harmonics. Latent space modeling often involves additional regularization to favor certain properties of the space over others, and the mapping back to the ambient space is then constructed mostly independently from these properties; here, we use the same data-driven approach to construct the latent space and then map back to the ambient space.

97 MATHEMATICS AND COMPUTING↗

gLaSDI: Parametric physics-informed greedy latent space dynamics identification

A parametric adaptive physics-informed greedy Latent Space Dynamics Identification (gLaSDI) method is proposed for accurate, efficient, and robust data-driven reduced-order modeling of high-dimensional nonlinear dynamical systems. In the proposed gLaSDI framework, an autoencoder discovers intrinsic nonlinear latent representations of high-dimensional data, while dynamics identification (DI) models capture local latent-space dynamics. Here, an interactive training algorithm is adopted for the autoencoder and local DI models, which enables identification of simple latent-space dynamics and enhances accuracy and efficiency of data-driven reduced-order modeling. To maximize and accelerate the exploration of the parameter space for the optimal model performance, an adaptive greedy sampling algorithm integrated with a physics-informed residual-based error indicator and random-subset evaluation is introduced to search for the optimal training samples on the fly. Further, to exploit local latent-space dynamics captured by the local DI models for an improved modeling accuracy with a minimum number of local DI models in the parameter space, a -nearest neighbor convex interpolation scheme is employed. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including Burgers equations, nonlinear heat conduction, and radial advection. The proposed adaptive greedy sampling outperforms the conventional predefined uniform sampling in terms of accuracy. Compared with the high-fidelity models, gLaSDI achieves 17 to 2,658× speed-up with 1 to 5% relative errors.

97 MATHEMATICS AND COMPUTING↗

Data-driven Whitney forms for structure-preserving control volume analysis

Control volume analysis models physics via the exchange of generalized fluxes between subdomains. Here, we introduce a scientific machine learning framework adopting a partition of unity architecture to identify physically-relevant control volumes, with generalized fluxes between subdomains encoded via Whitney forms. The approach provides a differentiable parameterization of geometry which may be trained in an end-to-end fashion to extract reduced models from full field data while exactly preserving physics. The architecture admits a data-driven finite element exterior calculus allowing discovery of mixed finite element spaces with closed form quadrature rules. An equivalence between Whitney forms and graph networks reveals that the geometric problem of control volume learning is equivalent to an unsupervised graph discovery problem. The framework is developed for manifolds in arbitrary dimension, with examples provided for H(div) problems in $\mathbb{R}$ establishing convergence and structure preservation properties. Finally, we consider a lithium-ion battery problem where we discover a reduced finite element space encoding transport pathways from high-fidelity microstructure resolved simulations. The approach reduces the 5.89M finite element simulation to 136 elements while reproducing pressure to under 0.1% error and preserving conservation.

97 MATHEMATICS AND COMPUTING↗

Dyn$\mathrm{AMO}$: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws

Here we introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost and solution accuracy in numerical methods for partial differential equations. However, traditional adaptive mesh refinement approaches for time-dependent problems typically rely only on instantaneous error indicators to guide adaptivity. As a result, standard strategies often require frequent remeshing to maintain accuracy. In the DynAMO approach, multi-agent reinforcement learning is used to discover new local refinement policies that can anticipate and respond to future solution states by producing meshes that deliver more accurate solutions for longer time intervals. By applying DynAMO to discontinuous Galerkin methods for the linear advection and compressible Euler equations in two dimensions, we demonstrate that this new mesh refinement paradigm can outperform conventional threshold-based strategies while also generalizing to different mesh sizes, remeshing and simulation times, and initial conditions.

97 MATHEMATICS AND COMPUTING↗

Vertical gradient freeze growth of detector grade CdZnTeSe single crystals

Here, we report the growth of detector grade Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 (CZTS) single crystals, a recently discovered quaternary semiconductor for room temperature radiation detection, by a vertical gradient freeze (VGF) method. VGF is a comparatively low-temperature growth method and avoids relative motion between the heater and the ampoule containing the precursor materials which minimizes any thermal drift or temperature fluctuations. As a result, CZTS single crystals with superior charge transport properties has been obtained. Growth of detector-grade CZTS single crystals using VGF method has not been reported yet. X-ray spectroscopy based elemental analysis showed that the grown crystals demonstrated the desired stoichiometry required for high resolution radiation detection. Planar detectors fabricated by deposition of gold contacts (~0.07 cm 2 ) demonstrated high bulk resistivity ~10 10 Ω-cm and a very low leakage current density of 2.8 × 10 –8 A/cm 2 at a bias of 100 V when measured at room temperature. The detectors showed excellent radiation response with 100 % charge collection efficiency when exposed to 5486 keV alpha particles. The electron mobility-lifetime (μτ) product was measured to be 3 × 10 –3 cm 2 /V using a single polarity Hecht analysis which is at par with the recently reported values measured in CZTS grown using conventional Bridgman or travelling heater method. The electron mobility has been calculated to be 964 cm 2 V –1 s –1 using a time-of-flight (TOF) method, a substantial improvement over that obtained from conventionally grown CZTS single crystals.

36 MATERIALS SCIENCE↗

Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding

The paper considers testing and signal identification for covariance matrices from two populations of marginally sub-Gaussian distributed. A multi-level thresholding procedure is proposed for testing the equality of two high-dimensional covariance matrices, which is designed to detect sparse and faint differences between the covariances. A novel -statistic composition is developed to establish the asymptotic distribution of the thresholding statistics in conjunction with the matrix blocking and the coupling techniques. It is shown that the proposed test is more powerful than the existing tests in detecting sparse and weak signals in covariances. Multiple testing procedures are constructed to discover different covariances and the sub-groups of variables with different covariance structures between the two populations. The proposed procedures are based on the multi-level thresholding test, which are able to control the false discovery proportion () with high power. Simulation experiments and a case study on the returns of the S&P 500 stocks before and after the COVID-19 pandemic are conducted to demonstrate and compare the utilities of the proposed methods.

97 MATHEMATICS AND COMPUTING↗

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗

Microstructure analysis and machinability of additively manufactured A205 aluminum with heat treatments

A205 aluminum is one of the few high-strength aluminum alloys discovered for additive manufacturing (AM). The microstructure and heat treatment effects of AM A205 vary from those of its cast form, indicating possible differences in machinability during post-processing. Here, the objective of this research is to determine these variations of AM A205 and their effects on machinability using the cast condition as the baseline. As built and two heat-treated conditions (solution treatment and age hardening) were applied and compared in terms of their microstructures, micro-hardness, and machinability including vibration, specific cutting energy, chip morphology, and surface finish. The effects of print orientations on machinability were tested as well and found to be insignificant. AM as built had a higher hardness and slightly better machinability than its cast as built cast counterpart due to a smaller grain size (1 µm vs. 15 µm), eutectic θ-Al 2 Cu lattice and a fine, homogeneous TiB 2 distribution. The solution treatment dissolved this θ-Al 2 Cu lattice and increased the grain size (3 µm) which decreased the hardness, increased the ductility seen in the chips, and reduced the overall machinability. The presence of θ’-Al 2 Cu precipitates improved the machinability of aged AM A205. In addition, it was found that A205 exhibited both ductile and brittle behavior depending on the cutting speed, thus producing different machinability. The speed dependency is related to the material condition and heat treatment.

36 MATERIALS SCIENCE↗