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DOE OSTI2021

Pushing Cu uphill of the volcano curve: Impact of a WC support on the catalytic activity of copper toward the hydrogen evolution reaction

Here, the adsorption of atomic H and H 2 on copper mono- and submonolayers supported on hexagonal WC(0001) surfaces has been investigated using density functional theory with the Perdew–Burke–Ernzerhof exchange correlation functional and D2 van der Waals corrections. Results evidence the impact of the termination of the carbide substrate on fundamental properties of Cu adatoms, and, hence, on the stability of molecular and atomic hydrogen, defining copper's catalytic activity for hydrogen evolution reaction. Using H adsorption energy as a descriptor, catalytic activity of Cu adlayers for hydrogen evolution reaction was estimated using traditional volcano curves and a curve, obtained at low hydrogen coverage. Obtained results evidence that copper adlayers supported on the WC may present a viable low-cost alternative to noble metal-based catalysts, with improved catalytic activity compared to that of copper. This, potentially, can be a useful basis for designing and developing novel functional materials with predetermined catalytic properties.

08 HYDROGEN↗

DOE OSTI2023

Interfacial pressure improves calendar aging of lithium metal anodes

Lithium (Li) metal is a promising anode because its theoretical specific capacity is approximately ten times larger than graphite. However, Li anodes suffer from long-term capacity fade due to Li stranding (becoming electronically disconnected) and electrolyte decomposition. Applied interfacial pressure has been shown to improve Li anode cycling, likely due to reincorporating stranded or “dead” Li into the anode. Calendar aging can also lead to Li capacity loss due to electrolyte decomposition/Li corrosion and the formation of stranded Li. Some research suggests that calendar aging during cycling results in reversible capacity losses due to Li stranding and reconnection. We here investigate the effect of applied interfacial pressure on Li anode calendar aging during cycling with incorporated rest steps in a localized high-concentration electrolyte (LHCE) to understand if pressure can mitigate stranded Li formation during rest by manipulating the Li morphology. Pouch cells exhibit more stable cycling and denser Li deposits between 10 kPa and 1,000 kPa of applied pressure compared to no applied pressure. Despite drops in CE during periodic rest cycles, the average cumulative lost capacity and average coulombic efficiency (CE) of cells over 50 cycles show that cells aged with incorporated rest steps perform similarly to cells cycled without added rests. This similar average CE suggests that dead Li is largely responsible for drops in CE during rest rather than irreversible Li corrosion and that the dead Li can be reconnected in subsequent cycling. The addition of a lithiophilic ZnO coating to the Cu working electrode increases the adhesion and coverage of Li deposits at low pressures and improves CE during the first cycle.

25 ENERGY STORAGE↗

DOE OSTI2020

Partitioning of Complex Fluids at Mineral Surfaces

This report summarizes the results obtained during the LDRD project entitled "Partitioning of Complex Fluids at Mineral Interfaces." This research addressed fundamental aspects of such interfaces, which are relevant to energy-water applications in the subsurface, including fossil energy extraction and carbon sequestration. This project directly addresses the problem of selectivity of complex fluid components at mineral-fluid interfaces, where complex fluids are defined as a mixture of hydrophobic and hydrophilic components: e.g., water, aqueous ions, polar/nonpolar organic compounds. Specifically, this project investigates how adsorption selectivity varies with surface properties and fluid composition. Both experimental and molecular modeling techniques were used to better understand trends in surface wettability on mineral surfaces. The experimental techniques spanned the macroscale (contact angle measurements) to the nanoscale (cryogenic electronic microscopy and vibrational spectroscopy). We focused on an anionic surfactant and a well-characterized mineral phase representative of clay phases present in oil- and gas-producing shale deposits. Collectively, the results consistently demonstrate that the presence of surfactant in the aqueous fluid significantly affects the mineral-fluid interfacial structure. Experimental and molecular modeling results reveal details of the surfactant structure at the interface, and how this structure varies with surfactant coverage and fluid composition.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2021

What drives daily precipitation over the central Amazon? Differences observed between wet and dry seasons

This study offers an alternative presentation regarding how diurnal precipitation is modulated by convective events that developed over the central Amazon during the preceding nighttime period. We use data collected during the Observations and Modelling of the Green Ocean Amazon (GoAmazon 2014/2015) field campaign that took place from 1 January 2014 to 30 November 2015 in the central Amazon. Local surface-based observations of cloud occurrence, soil temperature, surface fluxes, and planetary boundary layer characteristics are coupled with satellite data to identify the physical mechanisms that control the diurnal rainfall in central Amazon during the wet and dry seasons. This is accomplished through evaluation of the atmospheric properties during the nocturnal periods preceding raining and non-raining events. Comparisons between these non-raining and raining transitions are presented for the wet (January to April) and dry (June to September) seasons. The results suggest that wet-season diurnal precipitation is modulated by nighttime cloud coverage and local influences such as heating induced turbulence, whereas the dry-season rain events are controlled by large-scale circulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A Comparative Study of Cloud Properties Between Northern and Southern High Latitudes Based on ARM Observations and EAMv2 Simulations

Earth's high-latitude regions show a considerable amount of cloud coverage, which significantly affects global radiation budgets. Here, in this study, we examine ground- and ship-based remote sensing observations from two Atmospheric Radiation Measurement (ARM) field campaigns conducted in the high-latitude regions of Northern and Southern Hemispheres (NH and SH). A comparison of macrophysical properties for low, mid-level, high, and deep clouds shows that the cloud top heights and thickness values are higher in the Arctic for each cloud type compared with the Southern Ocean and Antarctic regions, possibly due to higher sea surface temperatures in the north Atlantic. The Arctic also shows lower ice phase occurrence frequencies compared with the SH high latitudes for low clouds. For high, mid-level and deep clouds, the cloud phase distributions as a function of temperature show small geographical variabilities. The observations are then compared with the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) to evaluate the representations of these cloud properties. Here, the results show that the model captures cloud base and top heights well and reproduces the differences in cloud macrophysical properties between the two hemispheres. But the model underestimates ice phase frequencies for all cloud types. Such model cloud phase bias is strongly correlated with positive relative humidity biases and negative aerosol number concentration biases, indicating an important role of relative humidity and aerosols in modulating cloud phase partitioning in the model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

More frequent atmospheric rivers slow the seasonal recovery of Arctic sea ice

In recent decades, Arctic sea ice coverage experienced a drastic decline in winter, when sea ice is expected to recover following the melting season. It is unclear to what extent atmospheric processes such as atmospheric rivers (ARs), intense corridors of moisture transport, contribute to this reduced recovery of sea ice. Here, in this study, using observations and climate model simulations we find a robust frequency increase in ARs in early winter over the Barents-Kara Seas and the central Arctic (ABK) between 1979 and 2021. The moisture carried by more frequent ARs has intensified surface downward longwave radiation and rainfall, caused stronger melting of thin, fragile ice cover, and slowed the seasonal recovery of sea ice, accounting for 34% of the sea ice cover decline in ABK. A series of model ensemble experiments suggests that, in addition to a uniform AR increase in response to anthropogenic warming, tropical Pacific variability also contributes to the observed Arctic AR changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Sensitivity of mesoscale modeling to urban morphological feature inputs and implications for characterizing urban sustainability

We examine the differences in meteorological output from the Weather Research and Forecasting (WRF) model run at 270 m horizontal resolution using 10 m, 100 m and 1 km resolution 3D neighborhood morphological inputs and with no morphological inputs. We find that the spatial variability in temperature, humidity, and other meteorological variables across the city can vary with the resolution and the coverage of the 3D urban morphological input, and that larger differences occur between simulations run without 3D morphological input and those run with some type of 3D morphology. We also find that the inclusion of input-building-defined roughness length calculations would improve simulation results further. We show that these inputs produce different patterns of heat wave spatial heterogeneity across the city of Washington, DC. These findings suggest that understanding neighborhood level urban sustainability under extreme heat waves, especially for vulnerable neighborhoods, requires attention to the representation of surface terrain in numerical weather models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Long-term thermal aging of parylene conformal coating under high humidity and its effects on tin whisker mitigation

Usage of pure tin (Sn) or Sn-rich alloy in electronics industry is growing, which makes them more susceptible to the spontaneous growth of tin whiskers. The risk of having these whiskers can be dramatically mitigated by applying a conformal coating provided that it not only possesses excellent mechanical and adhesion properties but also maintains these properties throughout their service. Parylene C is commonly used as a conformal coating because of its favorable mechanical and physical properties, as well as superior conformal coverage. The purpose of this paper is to investigate the degradation of parylene C coating during the thermal aging in high humidity environment (85°C/85% relative humidity for up to 5000hrs) and its effect on the tin whisker mitigation capacity. It was observed that during aging at high temperature and high humidity (HTHH) environment, the oxidation occurs at early times, followed by bond scission, resulting in the loss of strength of the coating. Thinner parylene coating (12.5-μm-thick) had better coating adhesion on the silane-treated tin surface, so provided the better protection for tin whisker penetration than the thicker counterpart (25-μm-thick). After 2500hrs of aging, due to the degradation of the silane agent at the tin/parylene interface, the adhesion of the parylene coating was significantly weakened on the tin surface, which resulted in extensive corrosion of the tin solderpads. The loss of adhesion of the coating, along with the corrosion of the tin surface facilitated the tin whisker nucleation at the interface while the loss of mechanical strength and the brittleness made the coating easily penetrated by the growing whiskers. Tin whiskers with a smaller diameter were buckled and grew along the delaminated region while those with a larger diameter penetrated and continued to grow through the coating. Hence, the effectiveness of the parylene coatings on tin whisker mitigation is significantly reduced under long exposure to such high temperature and high humidity.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Overlooked cooling effects of albedo in terrestrial ecosystems

Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by Intergovernmental Panel on Climate Change (IPCC) assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced RF and the consequent global warming impact (GWI Δα ). We then highlight the shortcomings of available current databases and methodologies for calculating GWI Δα at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from earth system models (ESMs) suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI Δα is substantial, exceeding the RF Δα values of IPCC reports. Inclusion of GWI Δα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI Δα component into future ESMs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Correlating structure, self-assembly chemistry and conductivity of trithiocyanuric acid on Au(111)

The majority of candidates for simple model molecular-electronic components consist of a conductive π-conjugated hydrocarbon linker attached to at least two anchoring groups, such as thiols or isocyanides. It has been found that select molecules self-assemble on gold surfaces, creating one-dimensional conductive structures that act as “molecular wires”. Furthermore, these oligomers can form molecular bridges between gold nanoparticles, leading to the creation of simple molecular-electronic devices. This raises the question whether other π-conjugated molecular linkers could exhibit similar behavior that might offer a broader range of candidates for fabricating electronic devices. Trithiocyanuric acid (1,3,5-triazine-2,4,6-trithiol, TTCA) provides a possible candidate. TTCA (C3N3(SH)3) can exist as a trithiol or as a trithione in which hydrogens transfer to the sulfurs so that they are present with three C=N groups within the ring. TTCA exists naturally in the trithione form but converts into a trithiol when adsorbed onto an Ag(111) where it is vertically oriented. The structure of TTCA adsorbed on Au(111) is studied here using reflection-absorption infrared spectroscopy (RAIRS) where it is found to remain as the trithione isomer, but changes orientation as the coverage increases. Scanning-tunneling microscopy (STM) reveals that TTCA oligomerizes on Au(111) to form chains and triangular structures. The influence on molecular conductivity due to the differences in the adsorbate's isomeric structure was investigated using devices comprising either silver or gold nanoparticles deposited in the gap between gold nanoelectrodes. Both devices were found to conduct when dosed with TTCA, but the devices fabricated using silver were about 13 time more conductive than those made from gold nanoparticles, consistent with the π-conjugated structure formed on silver but not on gold. This implies that oligomers form both on silver and on gold and potentially increases the range of molecule-metal combinations that might be used to fabricate molecular-electronic devices.

Molecular electronics↗

DOE OSTI2024

Formation of the oxyl’s potential energy surface by the spectral kinetics of a vibrational mode

One of the most reactive intermediates for oxidative reactions is the oxyl radical, an electron-deficient oxygen atom. The discovery of a new vibration upon photoexcitation of the oxygen evolution catalysis detected the oxyl radical at the SrTiO3 surface. The vibration was assigned to a motion of the sub-surface oxygen underneath the titanium oxyl (Ti–O●−) created upon hole transfer to (or electron extraction from) a hydroxylated surface site. Evidence for such an interfacial mode is derived from its spectral shape, which exhibited a Fano resonance—a coupling of a sharp normal mode to continuum excitations. Here, this Fano resonance is utilized to derive precise formation kinetics of the oxyl radical and its associated potential energy surface (PES). From the Fano lineshape, the formation kinetics are obtained from the anti-resonance (the kinetics of the coupling factor), the resonance (the kinetics of the coupled continuum excitations), and the frequency integrated spectrum (the kinetics of the normal mode’s cross-section). All three perspectives yield logistic function growth with a half-rise of 2.3 ± 0.3 ps and a time constant of 0.48 ± 0.09 ps. A non-equilibrium transient associated with photoexcitation is separated from the rise of the equilibrated PES. The logistic function characterizes the oxyl coverage at the very initial stages (t ∼ 0) to have an exponential growth rate that quickly decreases toward zero as a limiting coverage is reached. Such time-dependent reaction kinetics identify a dynamic activation barrier associated with the formation of a PES and quantify it for oxyl radical coverage.

Chemistry↗

DOE OSTI2024

Diverse and unconventional methanogens, methanotrophs, and methylotrophs in metagenome-assembled genomes from subsurface sediments of the Slate River floodplain, Crested Butte, CO, USA

We use metagenome-assembled genomes (MAGs) to understand single-carbon (C1) compound-cycling—particularly methane-cycling—microorganisms in montane riparian floodplain sediments. We generated 1,233 MAGs (>50% completeness and <10% contamination) from 50- to 150-cm depth below the sediment surface capturing the transition between oxic, unsaturated sediments and anoxic, saturated sediments in the Slate River (SR) floodplain (Crested Butte, CO, USA). We recovered genomes of putative methanogens, methanotrophs, and methylotrophs (n = 57). Methanogens, found only in deep, anoxic depths at SR, originate from three different clades (Methanoregulaceae, Methanotrichaceae, and Methanomassiliicoccales), each with a different methanogenesis pathway; putative methanotrophic MAGs originate from within the Archaea (Candidatus Methanoperedens) in anoxic depths and uncultured bacteria (Ca. Binatia) in oxic depths. Genomes for canonical aerobic methanotrophs were not recovered. Ca. Methanoperedens were exceptionally abundant (~1,400× coverage, >50% abundance in the MAG library) in one sample that also contained aceticlastic methanogens, indicating a potential C1/methane-cycling hotspot. Ca. Methylomirabilis MAGs from SR encode pathways for methylotrophy but do not harbor methane monooxygenase or nitrogen reduction genes. Comparative genomic analysis supports that one clade within the Ca. Methylomirabilis genus is not methanotrophic. The genetic potential for methylotrophy was widespread, with over 10% and 19% of SR MAGs encoding a methanol dehydrogenase or substrate-specific methyltransferase, respectively. MAGs from uncultured Thermoplasmata archaea in the Ca. Gimiplasmatales (UBA10834) contain pathways that may allow for anaerobic methylotrophic acetogenesis. Overall, MAGs from SR floodplain sediments reveal a potential for methane production and consumption in the system and a robust potential for methylotrophy.

58 GEOSCIENCES↗

DOE OSTI2022

A Multiscale Deep Learning Model for Soil Moisture Integrating Satellite and In Situ Data

Deep learning (DL) models trained on hydrologic observations can perform extraordinarily well, but they can inherit deficiencies of the training data, such as limited coverage of in situ data or low resolution/accuracy of satellite data. In this work, we propose a novel multiscale DL scheme learning simultaneously from satellite and in situ data to predict 9 km daily soil moisture (5 cm depth). Based on spatial cross-validation over sites in the conterminous United States, the multiscale scheme obtained a median correlation of 0.901 and root-mean-square error of 0.034 m 3 /m 3 . It outperformed the Soil Moisture Active Passive satellite mission's 9 km product, DL models trained on in situ data alone, and land surface models. Our 9 km product showed better accuracy than previous 1 km satellite downscaling products, highlighting limited impacts of improving resolution. Not only is our product useful for planning against floods, droughts, and pests, our scheme is generically applicable to geoscientific domains with data on multiple scales, breaking the confines of individual data sets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗

DOE OSTI2023

Thin film charged particle detectors

Silicon tracking detectors have grown to cover larger surface areas up to hundreds of square meters, and are even taking over other sub-detectors, such as calorimeters. However, further improvements in tracking detector performance are more likely to arise from the ability to make a low mass detector comprised of a high ratio of active sensor to inactive materials, where dead materials include electrical services, cooling, mechanical supports, etc. In addition, the cost and time to build these detectors is currently large. Therefore, advancements in the fundamental technology of tracking detectors may need to look at a more transformative approach that enables extremely large area coverage with minimal dead material and is easier and faster to build. The advancement of thin film fabrication techniques has the potential to revolutionize the next-to-next generation of particle detector experiments. Some thin film deposition techniques have already been developed and widely used in the industry to make LED screens for TVs and monitors. If large area thin film detectors on the order of several square meters can be fabricated with similar performance as current silicon technologies, they could be used in future particle physics experiments. This paper aims to review the key fundamental performance criteria of existing silicon detectors and past research to use thin films and other semi-conductor materials as particle detectors in order to explore the important considerations and challenges to pursue thin film detectors.

Solid state detectors↗

DOE OSTI2021

Determining Spatial Scales of Soil Moisture—Cloud Coupling Pathways Using Semi-Idealized Simulations

The spatial scales of land-atmosphere interactions over heterogeneous, realistic soil moisture patterns are critical to improve our understanding of land-atmosphere interactions. However, these scales are poorly quantified. We use high-resolution numerical experiments to quantify the spatial scales for a selected day during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign in Oklahoma. A semi-idealized approach (removing background winds and surface topography while retaining the real-world data for other boundary conditions) enables examination of the local influence from the surface. Simulations that apply uniform surface, variable land cover with uniform soil moisture, and variable land cover with variable soil moisture are then compared. Land cover variations, especially water and urban surfaces, create two variance peaks in the surface sensible heat flux in the scales >10 km (meso-β) and <6 km (meso-γ). Both peaks are enhanced by the observation-based soil moisture distribution that has most of its variance in the meso-β scale. Atmospheric response in the meso-β scale is hydrostatic with weak vertical motion. The land cover variations induce secondary circulations in the scales of 2.5–6 km. The additional soil moisture variability intensifies extreme circulations over dry soil patches and sharp sensible heat flux gradients, slightly extending the characteristic scales to 2.5–9 km. While their areal coverage is small, soil moisture variations on such “hotspots” lead to substantially larger convective cloud structure and domain-mean rainfall, calling for a consideration of their non-linear effect in large-scale models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Isolation and characterization of IgG3 glycan-targeting antibodies with exceptional cross-reactivity for diverse viral families

Broadly reactive antibodies that target sequence-diverse antigens are of interest for vaccine design and monoclonal antibody therapeutic development because they can protect against multiple strains of a virus and provide a barrier to evolution of escape mutants. Using LIBRA-seq (linking B cell receptor to antigen specificity through sequencing) data for the B cell repertoire of an individual chronically infected with human immunodeficiency virus type 1 (HIV-1), we identified a lineage of IgG3 antibodies predicted to bind to HIV-1 Envelope (Env) and influenza A Hemagglutinin (HA). Two lineage members, antibodies 2526 and 546, were confirmed to bind to a large panel of diverse antigens, including several strains of HIV-1 Env, influenza HA, coronavirus (CoV) spike, hepatitis C virus (HCV) E protein, Nipah virus (NiV) F protein, and Langya virus (LayV) F protein. We found that both antibodies bind to complex glycans on the antigenic surfaces. Antibody 2526 targets the stem region of influenza HA and the N-terminal domain (NTD) region of SARS-CoV-2 spike. A crystal structure of 2526 Fab bound to mannose revealed the presence of a glycan-binding pocket on the light chain. Antibody 2526 cross-reacted with antigens from multiple pathogens and displayed no signs of autoreactivity. These features distinguish antibody 2526 from previously described glycan-reactive antibodies. Further study of this antibody class may aid in the selection and engineering of broadly reactive antibody therapeutics and can inform the development of effective vaccines with exceptional breadth of pathogen coverage.

Microbiology↗