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At least 973 records · Page 54

MEP pathway products allosterically promote monomerization of deoxy-D-xylulose-5-phosphate synthase to feedback-regulate their supply

Isoprenoids are a very large and diverse family of metabolites required by all living organisms. All isoprenoids derive from the double-bond isomers isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP), which are produced by the methylerythritol 4-phosphate (MEP) pathway in bacteria and plant plastids. It has been reported that IPP and DMAPP feedback-regulate the activity of deoxyxylulose 5-phosphate synthase (DXS), a dimeric enzyme that catalyzes the main flux-controlling step of the MEP pathway. Here we provide experimental insights into the underlying mechanism. Isothermal titration calorimetry and dynamic light scattering approaches showed that IPP and DMAPP can allosterically bind to DXS in vitro, causing a size shift. In silico ligand binding site analysis and docking calculations identified a potential allosteric site in the contact region between the two monomers of the active DXS dimer. Modulation of IPP and DMAPP contents in vivo followed by immunoblot analyses confirmed that high IPP/DMAPP levels resulted in monomerization and eventual aggregation of the enzyme in bacterial and plant cells. Loss of the enzymatically active dimeric conformation allows a fast and reversible reduction of DXS activity in response to a sudden increase or decrease in IPP/DMAPP supply, whereas aggregation and subsequent removal of monomers that would otherwise be available for dimerization appears to be a more drastic response in the case of persistent IPP/DMAPP overabundance (e.g., by a blockage in their conversion to downstream isoprenoids). Our results represent an important step toward understanding the regulation of the MEP pathway and rational design of biotechnological endeavors aimed at increasing isoprenoid contents in microbial and plant systems.

59 BASIC BIOLOGICAL SCIENCES↗

HAND transcription factors cooperatively specify the aorta and pulmonary trunk

Congenital heart defects (CHDs) affecting the cardiac outflow tract (OFT) constitute a significant cause of morbidity and mortality. The OFT develops from migratory cell populations which include the cardiac neural crest cells (cNCCs) and secondary heart field (SHF) derived myocardium and endocardium. The related transcription factors HAND1 and HAND2 have been implicated in human CHDs involving the OFT. Although Hand1 is expressed within the OFT, Hand1 NCC-specific conditional knockout mice (H1CKOs) are viable. Here we show that these H1CKOs present a low penetrance of OFT phenotypes, whereas SHF-specific Hand1 ablation does not reveal any cardiac phenotypes. Further, HAND1 and HAND2 appear functionally redundant within the cNCCs, as a reduction/ablation of Hand2 on an NCC-specific H1CKO background causes pronounced OFT defects. Double conditional Hand1 and Hand2 NCC knockouts exhibit persistent truncus arteriosus (PTA) with 100% penetrance. NCC lineage-tracing and Sema3c in situ mRNA expression reveal that Sema3c-expressing cells are mis-localized, resulting in a malformed septal bridge within the OFTs of H1CKO;H2CKO embryos. Interestingly, Hand1 and Hand2 also genetically interact within the SHF, as SHF H1CKOs on a heterozygous Hand2 background exhibit Ventricular Septal Defects (VSDs) with incomplete penetrance. Previously, we identified a BMP, HAND2, and GATA-dependent Hand1 OFT enhancer sufficient to drive reporter gene expression within the nascent OFT and aorta. Using these transcription inputs as a probe, we identify a novel Hand2 OFT enhancer, suggesting that a conserved BMP-GATA dependent mechanism transcriptionally regulates both HAND factors. These findings support the hypothesis that HAND factors interpret BMP signaling within the cNCCs to cooperatively coordinate OFT morphogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Balancing DNA repair to prevent ageing and cancer

DNA damage is a constant stressor to the cell. Persistent damage to the DNA over time results in an increased risk of mutation and an accumulation of mutations with age. Loss of efficient DNA damage repair can lead to accelerated ageing phenotypes or an increased cancer risk, and the trade-off between cancer susceptibility and longevity is often driven by the cell's response to DNA damage. High levels of mutations in DNA repair mutants often leads to excessive cell death and stem cell exhaustion which may promote premature ageing. Stem cells themselves have distinct characteristics that enable them to retain low mutation rates. However, when mutations do arise, stem cell clonal expansion can also contribute to age-related tissue dysfunction as well as heightened cancer risk. In this review, we will highlight increasing DNA damage and mutation accumulation as hallmarks common to both ageing and cancer. We will propose that anti-ageing interventions might be cancer preventative and discuss the mechanisms through which they may act.

60 APPLIED LIFE SCIENCES↗

Toward data assimilation of ship-induced aerosol–cloud interactions

Satellite imagery can detect temporary cloud trails or ship tracks formed from aerosols emitted from large ships traversing our oceans, a phenomenon that global climate models cannot directly reproduce. Ship tracks are observable examples of marine cloud brightening, a potential solar climate intervention that shows promise in helping combat climate change. In this paper, we demonstrate a simulation-based approach in learning the behavior of ship tracks based upon a novel stochastic emulation mechanism. Our method uses wind fields to determine the movement of aerosol–cloud tracks and uses a stochastic partial differential equation (SPDE) to model their persistence behavior. This SPDE incorporates both a drift and diffusion term which describes the movement of aerosol particles via wind and their diffusivity through the atmosphere, respectively. We first present our proposed approach with examples using simulated wind fields and ship paths. We then successfully demonstrate our tool by applying the approximate Bayesian computation method-sequential Monte Carlo for data assimilation.

54 ENVIRONMENTAL SCIENCES↗

Scale interactions and anisotropy in Rayleigh–Taylor turbulence

We study energy scale transfer in Rayleigh–Taylor (RT) flows by coarse graining in physical space without Fourier transforms, allowing scale analysis along the vertical direction. Two processes are responsible for kinetic energy flux across scales: baropycnal work Λ, due to large-scale pressure gradients acting on small scales of density and velocity; and deformation work Π, due to multiscale velocity. Our coarse-graining analysis shows how these fluxes exhibit self-similar evolution that is quadratic-in-time, similar to the RT mixing layer. We find that Λ is a conduit for potential energy, transferring energy non-locally from the largest scales to smaller scales in the inertial range where Π takes over. In three dimensions, Π continues a persistent cascade to smaller scales, whereas in two dimensions Π rechannels the energy back to larger scales despite the lack of vorticity conservation in two-dimensional (2-D) variable density flows. This gives rise to a positive feedback loop in 2-D RT (absent in three dimensions) in which mixing layer growth and the associated potential energy release are enhanced relative to 3-D RT, explaining the oft-observed larger α values in 2-D simulations. Despite higher bulk kinetic energy levels in two dimensions, small inertial scales are weaker than in three dimensions. Moreover, the net upscale cascade in two dimensions tends to isotropize the large-scale flow, in stark contrast to three dimensions. Furthermore, our findings indicate the absence of net upscale energy transfer in three-dimensional RT as is often claimed; growth of large-scale bubbles and spikes is not due to ‘mergers’ but solely due to baropycnal work Λ.

42 ENGINEERING↗

Small-scale properties from exascale computations of turbulence on a $\mathbf{32\,768^3}$ periodic cube

To study the physics of small-scale properties of homogeneous isotropic turbulence at increasingly high Reynolds numbers, direct numerical simulation results have been obtained for forced isotropic turbulence at Taylor-scale Reynolds number R λ = 2500 on a 32 768 3 three-dimensional periodic domain using a GPU pseudo-spectral code on a 1.1 exaflop GPU supercomputer (Frontier). These simulations employ the multi-resolution independent simulation (MRIS) technique (Yeung & Ravikumar 2020, Phys. Rev. Fluids, vol. 5, 110517) where ensemble averaging is performed over multiple short segments initiated from velocity fields at modest resolution, and subsequently taken to higher resolution in both space and time. Reynolds numbers are increased by reducing the viscosity with the large-scale forcing parameters unchanged. Although MRIS segments at the highest resolution for each Reynolds number last for only a few Kolmogorov time scales, small-scale physics in the dissipation range is well captured – for instance, in the probability density functions and higher moments of the dissipation rate and enstrophy density, which appear to show monotonic trends persisting well beyond the Reynolds number range in prior works in the literature. Attainment of range of length and time scales consistent with classical scaling also reinforces the potential utility of the present high-resolution data for studies of short-time-scale turbulence physics at high Reynolds numbers where full-length simulations spanning many large-eddy time scales are still not accessible. A single snapshot of the 32 768 3 data is publicly available for further analyses via the Johns Hopkins Turbulence Database.

intermittency↗

Comparison of the stellar populations of bulges and discs using the MaNGA survey

We use the MaNGA integral field spectroscopic survey of low-redshift galaxies to compare the stellar populations of the bulge and disc components, identified from their Sérsic profiles, for various samples of galaxies. Bulge-dominated regions tend to be more metal-rich and have slightly older stellar ages than their associated disc-dominated regions. The metallicity difference is consistent with the deeper gravitational potential in bulges relative to discs, which allows bulges to retain more of the metals produced by stars. The age difference is due to star formation persisting longer in discs relative to bulges. Relative to galaxies with lower stellar masses, galaxies with higher stellar masses tend to have bulge-dominated regions that are more metal-rich and older (in light-weighted measurements) than their disc-dominated regions. This suggests high-mass galaxies quench from the inside out, while lower-mass galaxies quench across the whole galaxy simultaneously. Early-type galaxies tend to have bulge-dominated regions the same age as their disc-dominated regions, while late-type galaxies tend to have disc-dominated regions significantly younger than their bulge-dominated regions. Central galaxies tend to have a greater metallicity difference between their bulge-dominated regions and disc-dominated regions than satellite galaxies at similar stellar mass. This difference may be explained by central galaxies being subject to mergers or extended gas accretion bringing new, lower-metallicity gas to the disc, thereby reducing the average metallicity and age of the stars; quenching of satellite discs may also play a role.

79 ASTRONOMY AND ASTROPHYSICS↗

Fluctuation dynamo in a weakly collisional plasma

The turbulent amplification of cosmic magnetic fields depends upon the material properties of the host plasma. In many hot, dilute astrophysical systems, such as the intracluster medium (ICM) of galaxy clusters, the rarity of particle–particle collisions allows departures from local thermodynamic equilibrium. These departures – pressure anisotropies – exert anisotropic viscous stresses on the plasma motions that inhibit their ability to stretch magnetic-field lines. We present an extensive numerical study of the fluctuation dynamo in a weakly collisional plasma using magnetohydrodynamic (MHD) equations endowed with a field-parallel viscous (Braginskii) stress. When the stress is limited to values consistent with a pressure anisotropy regulated by firehose and mirror instabilities, the Braginskii-MHD dynamo largely resembles its MHD counterpart, particularly when the magnetic field is dynamically weak. If instead the parallel viscous stress is left unabated – a situation relevant to recent kinetic simulations of the fluctuation dynamo and, we argue, to the early stages of the dynamo in a magnetized ICM – the dynamo changes its character, amplifying the magnetic field while exhibiting many characteristics reminiscent of the saturated state of the large-Prandtl-number ( ${Pm}\gtrsim {1}$ ) MHD dynamo. We construct an analytic model for the Braginskii-MHD dynamo in this regime, which successfully matches simulated dynamo growth rates and magnetic-energy spectra. A prediction of this model, confirmed by our numerical simulations, is that a Braginskii-MHD plasma without pressure-anisotropy limiters will not support a dynamo if the ratio of perpendicular and parallel viscosities is too small. This ratio reflects the relative allowed rates of field-line stretching and mixing, the latter of which promotes resistive dissipation of the magnetic field. Finally, in all cases that do exhibit a viable dynamo, the generated magnetic field is organized into folds that persist into the saturated state and bias the chaotic flow to acquire a scale-dependent spectral anisotropy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Interpretation of high-harmonic fast-wave propagation in the scrape-off layer of NSTX-U as a geometrically bounded-waveguide mode

This paper revisits the onset of high-harmonic fast-wave (HHFW) propagation in the scrape-off layer (SOL) plasma of the NSTX/NSTX-U spherical tokamak, motivated by past HHFW heating and current drive experiments and modelling. Previously, the fast-wave propagation in the SOL was correlated with the opening (suppression) of the fast-wave right-hand cutoff layer in front of the antenna. In this work, the SOL propagation is interpreted as a geometric waveguide mode guided by the SOL geometry, whose radial width can be comparable to the wave’s perpendicular wavelength in the HHFW regime. A two-dimensional circular model is first employed using full-wave solvers to characterise the poloidal eigenmode structures and to clarify their relationship to annulus resonance. By progressively adding a tokamak-like magnetic-field configuration, starting from a uniform axial field, the effects of magnetic-field gradients and pitch on the SOL waveguide mode are characterised. The poloidal mode numbers supported by the SOL plasma agree well with analytic estimates, indicating that an anisotropic plasma in a bounded geometry selectively supports and amplifies the resonant poloidal mode number. Additionally, two-dimensional axisymmetric NSTX-U simulations demonstrate that the SOL eigenmode features identified in the circular model persist in the experimentally relevant configurations. A control approach based on lengthening the wave perpendicular wavelength relative to the SOL width, including a higher magnetic (B)-field operation, is discussed. The analysis here shows the key role of a bounded geometry in interpreting HHFW eigenmode coupling and propagation in the NSTX-U SOL plasma.

plasma heating↗

Adsorption of Ar into zeolite Al-MFI (NH 4 )

The crystal structure of anhydrous Al-MFI (NH 4 ) containing adsorbed Ar has been determined and refined using synchrotron X-ray powder diffraction data taken at 90 K, and optimized using density functional theory techniques. Six highly occupied Ar sites almost completely fill the pore volume of the zeolite. Changing the gas flow from Ar to He at 90 K decreases the Ar occupancies of all six sites, but two decrease more than the others. Warming the sample from 90 to 295 K in Ar flow results in further decreases in site occupancies, but five of the original six sites persist.

Materials Science↗

Astrovirology: how viruses enhance our understanding of life in the Universe

Abstract Viruses are the most numerically abundant biological entities on Earth. As ubiquitous replicators of molecular information and agents of community change, viruses have potent effects on the life on Earth, and may play a critical role in human spaceflight, for life-detection missions to other planetary bodies and planetary protection. However, major knowledge gaps constrain our understanding of the Earth's virosphere: (1) the role viruses play in biogeochemical cycles, (2) the origin(s) of viruses and (3) the involvement of viruses in the evolution, distribution and persistence of life. As viruses are the only replicators that span all known types of nucleic acids, an expanded experimental and theoretical toolbox built for Earth's viruses will be pivotal for detecting and understanding life on Earth and beyond. Only by filling in these knowledge and technical gaps we will obtain an inclusive assessment of how to distinguish and detect life on other planetary surfaces. Meanwhile, space exploration requires life-support systems for the needs of humans, plants and their microbial inhabitants. Viral effects on microbes and plants are essential for Earth's biosphere and human health, but virus–host interactions in spaceflight are poorly understood. Viral relationships with their hosts respond to environmental changes in complex ways which are difficult to predict by extrapolating from Earth-based proxies. These relationships should be studied in space to fully understand how spaceflight will modulate viral impacts on human health and life-support systems, including microbiomes. In this review, we address key questions that must be examined to incorporate viruses into Earth system models, life-support systems and life detection. Tackling these questions will benefit our efforts to develop planetary protection protocols and further our understanding of viruses in astrobiology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

Nontraditional Approaches To Enable High-Energy and Long-Life Lithium–Sulfur Batteries

In this study, lithium-sulfur (Li-S) batteries are promising for automotive applications due to their high theoretical energy density (2600 Wh/kg). In addition, the natural abundance of sulfur could mitigate the global raw material supply chain challenge of commercial lithium-ion batteries that use critical elements, such as nickel and cobalt. However, due to persistent polysulfide shuttling and uncontrolled lithium dendrite growth, Li-S batteries using nonencapsulated sulfur cathodes and conventional ether-based electrolytes suffer from rapid cell degradation upon cycling. Despite significant improvements in recent decades, there is still a big gap between lab research and commercialization of the technology. To date, the reported cell energy densities and cycling life of practical Li-S pouch cells remain largely unsatisfactory. Traditional approaches to improving Li-S performance are primarily focused on confining polysulfides using electronically conductive hosts. However, these micro- and mesoporous hosts suffer from limited pore volume to accommodate high sulfur loading and the associated volume change during cycling. Moreover, they fail to balance adsorption-conversion of polysulfides during charge-discharge, leading to the formation of massive dead sulfur. Such hosts are themselves electrochemically inactive, which decreases the practical energy density. In contrast, a series of nontraditional approaches, paired with advances in multiscale mechanistic understanding, have recently demonstrated exciting performance outcomes not only in conventional coin cells but also in practical pouch cells. In this Account, we first introduce our novel cathode design strategies to overcome polysulfide shuttling and sluggish redox kinetics in thick S cathodes via selenium-sulfur chemistry and cathode host engineering. Next, we gain a mechanistic understanding of Li-S batteries in various types of electrolytes via a series of spectroscopic, nuclear magnetic resonance, and electrochemical methods. Meanwhile, a novel cathode solid electrolyte interphase encapsulation strategy via nonviscous highly fluorinated ether-based electrolyte is introduced. The established selection rule by investigating how solvating power retards the shuttle effect and induces robust cathode/solid-electrolyte interphase formation is also included. We then discuss how the synergistic interactions between rational cathode structures and electrolytes can be exploited to tailor the reaction pathways and kinetics of S cathodes under high mass loading and lean electrolyte conditions. In addition, a novel interlayer design to simultaneously overcome degradation processes (polysulfide shuttling and lithium dendrite formation) and accelerate redox reaction kinetics is presented. Finally, this Account concludes with an overview of the challenges and strategies to develop Li-S pouch cells with high practical energy density, long cycle life, and fast-charging capability.

25 ENERGY STORAGE↗

Evaluating Retention Index Score Assumptions to Refine GC–MS Metabolite Identification

As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography–mass spectrometry (GC–MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores. Here, in this study, we examined whether uninvestigated assumptions of the RI score are valid and propose ways to improve them. Query RIs were matched to library RI with a generous window of ±35 to avoid unintentional removal of valid compound identifications. Each match was manually verified as a true positive (TP), true negative, or unknown. Metabolites with at least 30 TP identifications were included in downstream analyses, resulting in a total of 87 metabolites from samples of varying complexity and type (e.g., amino acid mixtures, human urine, fungal species, and so on.). Our results showed that the RI score assumptions of normality, consistent variance across metabolites, and a mean error centered at 0 are often violated. We demonstrated through a cross-validation analysis that modifying these underlying assumptions according to empirical metabolite-specific distributions improved the TP and negative rankings. Further, we statistically determined the minimum number of samples required to estimate distributional parameters for scoring metrics. Overall, this work proposes a robust statistical pipeline to reduce the time bottleneck of metabolite identification by improving RI scores and thus minimize the effort to complete manual verification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Assessment of Mammalian Lipidome Complexity Using Multimodal 21 T FTICR Mass Spectrometry Imaging

Herein, we assess the complementarity and complexity of data that can be detected within mammalian lipidome mass spectrometry imaging (MSI) via matrix-assisted laser desorption ionization (MALDI) and nanospray desorption electrospray ionization (nano-DESI). We do so by employing 21 T Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) with absorption mode FT processing in both cases, allowing unmatched mass resolving power per unit time (≥613k at m/z 760, 1.536 s transients). While our results demonstrated that molecular coverage and dynamic range capabilities were greater in MALDI analysis, nano-DESI provided superior mass error, and all annotations for both modes had sub-ppm error. Taken together, these experiments highlight the coverage of 1676 lipids and serve as a functional guide for expected lipidome complexity within nano-DESI-MSI and MALDI-MSI. To further assess the lipidome complexity, mass splits (i.e., the difference in mass between neighboring peaks) within single pixels were collated across all pixels from each respective MSI experiment. The spatial localization of these mass splits was powerful in informing whether the observed mass splits were biological or artificial (e.g., matrix related). Mass splits down to 2.4 mDa were observed (i.e., sodium adduct ambiguity) in each experiment, and both modalities highlighted comparable degrees of lipidome complexity. Further, we highlight the persistence of certain mass splits (e.g., 8.9 mDa; double bond ambiguity) independent of ionization biases. Here, we also evaluate the need for ultrahigh mass resolving power for mass splits ≤4.6 mDa (potassium adduct ambiguity) at m/z > 1000, which may only be resolved by advanced FTICR-MS instrumentation.

21T-FTICR-MS↗

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. Here we present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ~5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗

Dynamic Barriers to Crystallization of Calcium Barium Carbonates

Metastable carbonates play important roles in geochemistry, biomineralization and serve as model systems for nonclassical theories of nucleation and growth. Balcite (Ca 0.5 Ba 0.5 CO 3 ) is a remarkable carbonate phase that is isostructural with a high-temperature modification of calcite (CaCO 3 ), yet can be synthesized at ambient conditions. Here, we investigate crystallization pathways in the Ba-Ca-CO 3 -H 2 O system, with a focus on the transformation of amorphous calcium barium carbonate (ACBC) to balcite and subsequent decomposition into the equilibrium calcite (CaCO3) and witherite (BaCO 3 ) phases. Density functional theory calculations show that balcite is an unstable solid solution (Ca 1-x BaxCO 3 , R 3¯ m) in the range 0.17 < x < 0.5, but is accessible through the amorphous ACBC precursor for x ≲ 0.5, and predict its decomposition into calcite and witherite. We confirm this pathway experimentally but found demixing to proceed slowly and remain incomplete even after 9 months. Nucleation kinetics of balcite from ACBC was assessed using a microfluidic assay, where increasing barium content led to a surprising increase in the balcite nucleation rate, despite decreasing thermodynamic driving force. We attribute crystallization rates that dramatically accelerate with time to changes in interfacial structure and composition during coarsening of the amorphous precipitate. By carefully quantifying the thermodynamic and kinetic contributions in the multistep crystallization of a metastable carbonate, we produce insights that allow us to better interpret the formation and persistence of metastable minerals in natural and synthetic environments.

36 MATERIALS SCIENCE↗