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At least 379 records · Page 21

Cell to Ecosystem: Understanding Methane and Associated Nutrient Cycling by Sediment Hosted Syntrophic Consortia and Their Viral Predators

The anaerobic oxidation of methane (AOM) is a significant worldwide microbial process in anoxic lake and ocean sediments, responsible for sequestering up to 80% of this greenhouse gas. Often considered a metabolism on the edge of thermodynamic probability, the impact of ANaerobic MEthane-oxidizing ‘ANME’ archaea on carbon and nutrient cycling in sediment ecosystems is far reaching. They not only serve as a sink for methane coupled to diverse electron acceptors, but also catalyze the transformation of many important nutrients including nitrogen, phosphate, and iron. While information about the potential mechanisms supporting metabolism in AOM is now available, remarkably little has been learned about their nutritional requirements, their dependencies on bacterial partners, and consequentially their ultimate impact on nutrient transformation and bioavailability within sedimentary ecosystems, and beyond. Further, the role of viruses within sediment ecosystems represents an essential but vastly understudied aspect of the transformation of carbon and nutrients by AOM. Viruses are now widely appreciated as central players in biogeochemical cycles across diverse ecosystems. These nanoscale predators have been shown to enhance the turnover of essential nutrients, thus stimulating microbial growth and environmental viruses themselves may constitute an important reservoir of nitrogen and phosphorous. Little is known about the role of viruses in methane-impacted sedimentary ecosystems, however prior genomic and microscopy evidence suggests that AOM consortia are susceptible to phage infection. The overarching scientific goal of this multi-disciplinary research proposal is to build on these recent discoveries and expand our understanding of interactions and fundamental activities involved in cycling of carbon and nutrients by syntrophic methanotrophic archaeal-bacterial consortia and associated viruses in anoxic sedimentary environments. Our three specific objectives are to 1) Quantify energy and nutrient exchange (e.g. N, P, Fe and vitamins) within AOM consortia and between ANME-bacterial partners; 2) Identify virus-host interactions associated with AOM and assess C and N transfer through viruses in methane-impacted sediment ecosystems; 3) Model energy and nutrient exchange in AOM consortia and viral-host interactions (i.e. viral activity), and their environmental distribution patterns. Our experimental emphasis cuts across scales that are important for understanding microbial and viral interactions and activities within their habitats, as well as community wide biogeochemical transformations. These research goals will be accomplished through the application of novel molecular techniques targeting DNA, RNA, proteins, and metabolites combined with a unique multi-modal analytical imaging pipeline. We will then model the ecophysiological capabilities of diverse sediment-hosted methanotrophic consortia to develop a more comprehensive understanding of the energetic and nutritional interactions between different AOM partner couplings that occur in sediments.

03 NATURAL GAS↗

Collimated phase measuring deflectometry II: Re-design of the optical layout for high-curvature surfaces

Collimated phase measuring deflectometry (CPMD) is an optical metrology technique developed to improve upon traditional phase measuring deflectometry (PMD). CPMD utilizes telecentric imaging and collimated structured light illumination to eliminate the height-slope ambiguity present in traditional PMD measurements. After the publication of the first CPMD paper, efforts began to optimize the optical layout of the CPMD system. The first proposed change, and the one detailed in this work, was to move the Fourier transform (FT) lens closer to the surface under test (SUT). Moving the FT lens closer to the SUT meant that for a given FT lens diameter, a larger range of surface slopes on the SUT could be measured. This change to the optical layout was not trivial and introduced at least two concerns that had to be addressed: telecentricity in the imaging path and possible ghost reflections from the re-located FT lens. Here, in this work, we examine how these concerns were addressed and present results showing that the revised optical layout is capable of measurement results at least as good as the original CPMD optical layout. We also demonstrate the increased slope measuring range of the revised optical layout.

47 OTHER INSTRUMENTATION↗

Quantitative phase imaging by gradient retardance optical microscopy

Abstract Quantitative phase imaging (QPI) has become a vital tool in bioimaging, offering precise measurements of wavefront distortion and, thus, of key cellular metabolism metrics, such as dry mass and density. However, only a few QPI applications have been demonstrated in optically thick specimens, where scattering increases background and reduces contrast. Building upon the concept of structured illumination interferometry, we introduce Gradient Retardance Optical Microscopy (GROM) for QPI of both thin and thick samples. GROM transforms any standard Differential Interference Contrast (DIC) microscope into a QPI platform by incorporating a liquid crystal retarder into the illumination path, enabling independent phase-shifting of the DIC microscope's sheared beams. GROM greatly simplifies related configurations, reduces costs, and eradicates energy losses in parallel imaging modalities, such as fluorescence. We successfully tested GROM on a diverse range of specimens, from microbes and red blood cells to optically thick (~ 300 μm) plant roots without fixation or clearing.

47 OTHER INSTRUMENTATION↗

Delivering Robust Proton-Only Sensing of Hyperpolarized [1,2- 13 C 2 ]-Pyruvate Using Broad-Spectral-Range Nuclear Magnetic Resonance Pulse Sequences

Hyperpolarized [1- 13 C]pyruvate is the leading hyperpolarized injectable contrast agent and is currently under evaluation in clinical trials for molecular imaging of metabolic diseases, including cardiovascular disease and cancer. One aspect limiting broad scalability of the technique is that hyperpolarized 13 C MRI requires specialized 13 C hardware and software that are not generally available on clinical MRI scanners, which employ proton-only detection. Here, we present an approach that uses pulse sequences to transfer 13 C hyperpolarization to methyl protons for detection of the 13 C– 13 C pyruvate singlet, employing proton-only excitation and detection only. The new pulse sequences are robust to the B 1 and B 0 magnetic field inhomogeneities. The work focuses on singlet-to-magnetization (S2M) and rotor-synchronized (R) pulses, both relying on trains of hard pulses with broad spectral width coverage designed to effectively transform hyperpolarized 13 C 2 -singlet hyperpolarization to 1 H polarization on the CH 3 group of [1,2- 13 C 2 ]pyruvate. Finally, this approach may enable a broader adoption of hyperpolarized MRI as a molecular imaging technique.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Additive manufacturing↗

pyDiSCaMB : enabling the use of multipolar scattering factors in Phenix

Multipolar scattering models, such as the transferable aspherical atom model, account for atomic chemical interactions and provide a more accurate representation of experimental data. However, the simpler independent atom model (IAM), which assumes non-interacting atoms, is the only model available in the most widely used macromolecular refinement programs. This is primarily because IAM offers a hard-to-beat combination of computational efficiency and modelling power at typical macromolecular resolutions. By contrast, more accurate multipolar modelling has historically been limited due to its computational cost and the absence of an interface between software capable of calculating structure factors and gradients based on multipolar models and software designed for macromolecular refinement. This work introduces pyDiSCaMB , a Python software package designed to integrate between the computational crystallography toolbox ( cctbx ) and the quantum crystallography library DiSCaMB ( Densities in Structural Chemistry and Molecular Biology ), thus enabling multipolar scattering models in Phenix 's toolkit. The implementation, features and capabilities of pyDiSCaMB are presented, the runtimes for the calculation of structure factor and target gradients with respect to atomic parameters are explored, and Fourier images of electrostatic potential, electron density and deformation maps are computed as illustrative examples. The pyDiSCaMB library will make multipolar modelling widely available to the structural biology community, potentially transforming refinement and model-building for both crystallography and cryogenic electron microscopy (cryoEM).

MATTS data bank↗

Finding a needle in a haystack: quantitative HERFD-XRF imaging and HERFD-XANES characterization of trace platinum in gold solidi from the Late Roman and Byzantine Empires

High-Energy Resolution Fluorescence Detection X-Ray Fluorescence (HERFD-XRF) imaging and HERFD X-ray Absorption Near Edge Structure (XANES) spectroscopy are used to quantify and characterize trace platinum (Pt) in gold solidi from the Late Roman and Byzantine Empires. Historically, the elemental analysis of coins has been pivotal in distinguishing authentic artifacts from forgeries, elucidating minting practices, and understanding economic shifts. Notably, a new gold source with high platinum content appeared in the fourth century CE, transforming the Roman economy. Traditional methods struggled to detect platinum due to the overwhelming gold matrix. Here, this study demonstrates the effectiveness of HERFD techniques in resolving this challenge. Three gold solidi, minted between 654 and 659 CE, were analyzed alongside reference gold materials with known Pt concentrations. The HERFD-XRF imaging revealed spatial distributions of platinum, highlighting non-uniformities within the coins. Additionally, HERFD-XANES spectroscopy identified the oxidation states and chemical speciation of platinum. Results demonstrate that platinum in the solidi primarily exists as metallic Pt, with some surface oxidation. The findings align with previous measurements but reveal higher Pt concentrations and significant inhomogeneities. This research confirms the reliability of HERFD methods for quantifying trace elements and provides new insights into the raw material sources and minting techniques of ancient gold coins. The non-destructive nature of this approach allows for extensive analyses, offering valuable data for historical, economic, and archaeological studies. This innovative application of HERFD-XRF imaging and XANES in cultural heritage research underscores the potential for detailed material characterization and conservation, enhancing our understanding of ancient economies and trade patterns.

Van Loon, Lisa L.↗

Integrated atomic force microscopy and x-ray irradiation for in situ characterization of radiation-induced processes

Understanding radiation-induced chemical and physical transformations at material interfaces is important across diverse fields, but experimental approaches are often limited to either ex situ observations or in situ electron microscopy or synchrotron-based methods in which cases the radiation type and dose are inextricably tied to the imaging basis itself. In this work we overcome this limitation by demonstrating integration of an X-ray source with an atomic force microscope to directly monitor radiolytically-driven interfacial chemistry at the nanoscale. We illustrate the value of in situ observations by examining effects of radiolysis on material adhesion forces in aqueous solution, as well as examining the production of alkali nitrates at the interface between an alkali halide crystal surface and air. For the examined salt-air interface, direct visualization under flexible experimental conditions greatly extends prior observations by enabling the transformation process to be followed comprehensively from source-to-sink with mass balance quantitation. Overall, our novel rad-AFM opens doors into understanding the dynamics of radiolytically-driven mass transfer and surface alteration at the nanoscale in real-time.

47 OTHER INSTRUMENTATION↗

Does manganese influence grass litter decomposition on a Hawaiian rainfall gradient?

Plant litter is a well-defined pool of organic matter (OM) in which the influence of manganese (Mn) on decomposition (both decomposition rate and the mix of compounds ultimately transferred to soil OM) has been clearly demonstrated in temperate forests. However, no similar study exists on grasslands and the effect of foliar Mn versus soil-derived Mn on litter decomposition is poorly known. We used a 5-month and 12-month field, and 10-month laboratory experiments to evaluate litter decomposition on the Kohala rainfall gradient (Island of Hawai‘i) in areas with different foliar and soil Mn abundances, and on which a single plant species (Pennisetum clandestinum) dominates primary production and the litter pool. The chemical imaging analyses of decomposed litter revealed that Mn 2+ oxidized to Mn 3+ and Mn 4+ on grass litter during decompositions—hallmarks of Mn-driven litter oxidation. However, these transformations and Mn abundance did not predict greater litter mass loss through decomposition. These observations demonstrate that the importance of Mn to an ecosystem’s C cycle does not rely solely on the metal’s abundance and availability.

54 ENVIRONMENTAL SCIENCES↗

Toward Å-fs-meV Resolution in Electron Microscopy: Systematic Simulation of the Temporal Spread of Single-Electron Packets

Though efforts to improve the temporal resolution of transmission electron microscopes (TEMs) have waxed and waned for decades, with relatively recent advances routinely reaching sub-picosecond scales, fundamental and practical challenges have hindered the advance of combined Å-fs-meV resolutions, particularly for core-loss spectroscopy and real-space imaging. This is due in no small part to the complexity of the approach required to access timescales upon which electrons, atoms, molecules, and materials first begin to respond and transform – attoseconds to picoseconds. Here we present part of a larger effort devoted to systematically mapping the instrument parameter space of a TEM modified to reach ultrafast timescales. With General Particle Tracer, we studied the statistical temporal distributions of single-electron packets as a function of various fs pulsed-laser parameters and electron-gun configurations and fields for the exact architecture and dimensions of a Thermo Fisher Tecnai Femto ultrafast electron microscope. We focused on easily-adjustable parameters, such as laser pulse duration, laser spot size, photon energy, Wehnelt aperture diameter, and photocathode size. In addition to establishing trends and dispersion behaviors, we identify regimes within which packet duration can be 100s of fs and approach the 300-fs laser limit employed here. Overall, the results provide a detailed picture of the temporal behavior of single-electron packets in the Tecnai Femto gun region, forming the initial contribution of a larger effort.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ring artifact reduction via multiscale nonlocal collaborative filtering of spatially correlated noise

X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Synchrotron Imaging of Pore Formation in Li Metal Solid-State Batteries Aided by Machine Learning

High-rate capable, reversible lithium metal anodes are necessary for next generation energy storage systems. In situ tomography of Li/LLZO/Li cells is carried out to track morphological transformations in Li metal electrodes. Machine learning enables tracking the lithium metal morphology during galvanostatic cycling. Nonuniform lithium electrode kinetics are observed at both electrodes during cycling. Hot spots in lithium metal are correlated with microstructural anisotropy in LLZO. Mesoscale modeling reveals that regions with lower effective properties (transport and mechanical) are nuclei for failure. Advanced visualization combined with electrochemistry represents an important pathway toward resolving non-equilibrium effects that limit rate capabilities of solid-state batteries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multiscale X-ray phase contrast imaging of human cartilage for investigating osteoarthritis formation

The evolution of cartilage degeneration is still not fully understood, partly due to its thinness, low radio-opacity and therefore lack of adequately resolving imaging techniques. X-ray phase-contrast imaging (X-PCI) offers increased sensitivity with respect to standard radiography and CT allowing an enhanced visibility of adjoining, low density structures with an almost histological image resolution. This study examined the feasibility of X-PCI for high-resolution (sub-) micrometer analysis of different stages in tissue degeneration of human cartilage samples and compare it to histology and transmission electron microscopy. Ten 10%-formalin preserved healthy and moderately degenerated osteochondral samples, post-mortem extracted from human knee joints, were examined using four different X-PCI tomographic set-ups using synchrotron radiation the European Synchrotron Radiation Facility (France) and the Swiss Light Source (Switzerland). Volumetric datasets were acquired with voxel sizes between 0.7 × 0.7 × 0.7 and 0.1 × 0.1 × 0.1 µm 3 . Data were reconstructed by a filtered back-projection algorithm, post-processed by ImageJ, the WEKA machine learning pixel classification tool and VGStudio max. For correlation, osteochondral samples were processed for histology and transmission electron microscopy. X-PCI provides a three-dimensional visualization of healthy and moderately degenerated cartilage samples down to a (sub-)cellular level with good correlation to histologic and transmission electron microscopy images. X-PCI is able to resolve the three layers and the architectural organization of cartilage including changes in chondrocyte cell morphology, chondrocyte subgroup distribution and (re-)organization as well as its subtle matrix structures. X-PCI captures comprehensive cartilage tissue transformation in its environment and might serve as a tissue-preserving, staining-free and volumetric virtual histology tool for examining and chronicling cartilage behavior in basic research/laboratory experiments of cartilage disease evolution.

3D analysis↗

Origin, parameters, and underlying deformation mechanisms of propagating deformation bands in irradiated 316L stainless steel

Lüders-type propagating deformation bands were observed in specimens of irradiated 316L stainless steel samples removed from Spallation Neutron Source target vessels after service. Mechanical testing with digital image correlation (DIC) and in-situ tensile testing with scanning electron microscopy electron backscatter diffraction showed that the observed Lüders-type behavior was not related to the known transformation-induced plasticity or twinning-induced plasticity behavior. Instead, the phenomenon occurs at small local strain values before a significant amount of martensite or deformation twins appear in the microstructure. Microstructural analysis and in-situ mechanical test results suggest Lüders-type band formation and propagation were related to the appearance and evolution of defect-free channels—analogous to slip bands. A modified Swift equation with a Ludwigson-like component was offered to rationalize the phenomenon and model the strain-softening processes at small strain values. Finally, the results indicate complex microstructural processes and deformation mechanisms were active at small strain values and underline the benefits of advanced mechanical test approaches such as DIC.

36 MATERIALS SCIENCE↗

Cell dynamics simulations of coupled charge and magnetic phase transformation in correlated oxides

In this work, we present a comprehensive numerical study on the kinetics of phase transition that is characterized by two nonconserved scalar order parameters coupled by a special linear-quadratic interaction. This particular Ginzburg-Landau theory has been proposed to describe the coupled charge and magnetic transition in nickelates and the collinear stripe phase in cuprates. The inhomogeneous state of such systems at low temperatures consists of magnetic domains separated by quasimetallic domain walls where the charge order is reduced. By performing large-scale cell dynamics simulations, we find a two-stage phase-ordering process in which a short period of independent evolution of the two order parameters is followed by a correlated coarsening process. The long-time growth and coarsening of magnetic domains is shown to follow the Allen-Cahn power law. We further show that the nucleation-and-growth dynamics during phase transformation to the ordered states is well described by the Kolmogorov-Johnson-Mehl-Avrami theory in two dimensions. On the other hand, the presence of quasimetallic magnetic domain walls in the ordered states gives rise to a very different kinetics for transformation to the high-temperature paramagnetic phase. In this scenario, the phase transformation is initiated by the decay of magnetic domain walls into two insulator-metal boundaries, which subsequently move away from each other. Implications of our findings to recent nano-imaging experiments on nickelates are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗