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At least 415 records · Page 23

Complex plant-derived organic aerosol as ice-nucleating particles – more than the sums of their parts?

Quantifying the impact of complex organic particles on the formation of ice crystals in clouds remains challenging, mostly due to the vast number of different sources ranging from sea spray to agricultural areas. In particular, there are many open questions regarding the ice nucleation properties of organic particles released from terrestrial sources such as decaying plant material. In this work, we present results from laboratory studies investigating the immersion freezing properties of individual organic compounds commonly found in plant tissue and complex organic aerosol particles from vegetated environments, without specifically investigating the contribution from biological particles, which may contribute to the overall ice nucleation efficiency observed at high temperatures. To characterize the ice nucleation properties of plant-related aerosol samples for temperatures between 242 and 267 K, we used the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud chamber and the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT), which is a droplet freezing assay. Individual plant components (polysaccharides, lignin, soy and rice protein) were mostly less ice active, or similarly ice active, compared to microcrystalline cellulose, which has been suggested by recent studies to be a proxy for quantifying the primary cloud ice formation caused by particles originating from vegetation. In contrast, samples from ambient sources with a complex organic matter composition (agricultural soils and leaf litter) were either similarly ice active or up to 2 orders of magnitude more ice active than cellulose. Of all individual organic plant components, only carnauba wax (i.e., lipids) showed a similarly high ice nucleation activity as that of the samples from vegetated environments over a temperature range between 245 and 252 K. Hence, based on our experimental results, we suggest considering cellulose as being representative for the average ice nucleation activity of plant-derived particles, whereas lignin and plant proteins tend to provide a lower limit. In contrast, complex biogenic particles may exhibit ice nucleation activities which are up to 2 orders of magnitude higher than observed for cellulose, making ambient plant-derived particles a potentially important contributor to the population of ice-nucleating particles in the troposphere, even though major uncertainties regarding their transport to cloud altitude remain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cooperative microbial interactions drive spatial segregation in porous environments

The role of microbial interactions and the underlying mechanisms that shape complex biofilm communities are poorly understood. Here we employ a microfluidic chip to represent porous subsurface environments and show that cooperative microbial interactions between free-living and biofilm-forming bacteria trigger active spatial segregation to promote their respective dominance in segregated microhabitats. During initial colonization, free-living and biofilm-forming microbes are segregated from the mixed planktonic inoculum to occupy the ambient fluid and grain surface. Contrary to spatial exclusion through competition, the active spatial segregation is induced by cooperative interactions which improves the fitness of both biofilm and planktonic populations. We further show that free-living Arthrobacter induces the surface colonization by scavenging the biofilm inhibitor, D-amino acids and receives benefits from the public goods secreted by the biofilm-forming strains. Collectively, our results reveal how cooperative microbial interactions may contribute to microbial coexistence in segregated microhabitats and drive subsurface biofilm community succession.

59 BASIC BIOLOGICAL SCIENCES↗

Black carbon enriches short-range-order ferrihydrite in Amazonian Dark Earth: Interplay mechanism and environmental implications

Our study underpins the mechanism of organo-mineral interaction between black carbon (BC, biochar) and associated minerals in the historical BC-rich Amazonian Dark Earth (ADE) by using synchrotron-based microscopic (TXM), microspectroscopic (μFTIR) and spectroscopic (XAS and μ-diffraction) approaches. The BC-rich ADE contained over 100% more poorly crystalline minerals than the adjacent tropical soil. Linear combination fitting of k-spacing in the X-ray Absorption Spectra (XAS) revealed that ferrihydrite contributed to 81.1% of the Fe-minerals in BC. A small but distinct peak was observed at 5.7 Å –1 in the extended X-ray absorption fine structure k oscillation of BC, revealing the presence of Fe—C (including Fe-O-C) covalent bonds. No Fe—C path was yielded by the XAS fitting when an obvious peak downshift of the first (Fe—Fe 1 ) shell was observed, suggesting that the availability of inner-sphere Fe—C complexation was limited to the BC surface and interphase region. In this study, the main minerals for organo-mineral complexation were short-range-order (SRO) ferrihydrite on BC instead of corner-sharing FeO 6 octahedra. Compared to ADE, the coordination number of the first (Fe—Fe 1 ) and second (Fe—Fe 2 ) shell was higher in BC, revealing a higher degree of order in coordination between the neighboring Fe mineral crystals. Black C limited the progressive aging of amorphous Fe phases and greatly enriched SRO ferrihydrite in the redox-fluctuating and high-leaching environment. The transformation of SRO ferrihydrite into the more crystalline Fe oxides was controlled by the local pH environment. A strong signal from the complexed phenolic group (aryl-OH, 1241 cm –1 ) and a distinct band of inner-sphere complexation (Fe-aryl C, 1380–1384 cm –1 ) were identified in the FTIR spectra. The enrichment of poorly crystalline minerals can have positive feedback on the long-term stabilization of BC. The scale-up application of biochar to agricultural and ecological systems may have a long-lasting impact on the enrichment and transformation of the SRO minerals in the soil.

54 ENVIRONMENTAL SCIENCES↗

Harnessing Intermolecular Interactions to Promote Long-Lived Photoinduced Charge Separation from Copper Phenanthroline Chromophores

In this study, facilitating photoinduced electron transfer (PET) while minimizing rapid charge-recombination processes to produce a long-lived charge-separated (CS) state represents a primary challenge associated with achieving efficient solar fuel production. Natural photosynthetic systems employ intermolecular interactions to arrange the electron-transfer relay in reaction centers and promote a directional flow of electrons. This work explores a similar tactic through the synthesis and ground- and excited-state characterization of two Cu(I)bis(phenanthroline) chromophores with homoleptic and heteroleptic coordination geometries and which are functionalized with negatively charged sulfonate groups. The addition of sulfonate groups enables solubility in pure water, and it also induces assembly with the dicationic electron acceptor methyl viologen (MV 2+ ) via bimolecular, dynamic electrostatic interactions. The effect of the sulfonate groups on the ground- and excited-state properties was evaluated by comparison with the unsulfonated analogues in 1:1 acetonitrile/water. The excited-state lifetimes for all sulfonated complexes are similar to what we expect from previous literature, with the exception of the sulfonated heteroleptic complex whose metal-to-ligand charge-transfer (MLCT) lifetime in water has two components that are fit to 10 and 77 ns. For the sulfonated complexes, we detected reduced MV +$\bullet$ in both solvent environments following MLCT excitation, but control measurements in 1:1 acetonitrile/water with the unsulfonated analogues showed no PET to MV 2+ , indicating that electrostatically driven supramolecular assemblies of the sulfonated complexes with MV 2+ facilitate the observed PET. Additionally, the strength of the intermolecular interactions driving the formation of these assemblies changes drastically with the solvent environment. In 1:1 acetonitrile/water, PET occurred from both sulfonated complexes with quantum yields (Φ ET ) of 2-3% but increased to a remarkable 98% for the sulfonated heteroleptic complex with a 3 μs CS-state lifetime in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystal generation using the fully differentiable pipeline and latent space optimization

We present a materials generation framework that couples a symmetry-conditioned variational autoencoder with a differentiable SO(3) power spectrum objective to steer candidates toward a specified local environment under the crystallographic constraints. In particular, we implement a fully differentiable pipeline that performs batch-wise optimization on both direct and latent crystallographic representations. Using the GPU acceleration, the implementation achieves about fivefold speed compared to our previous CPU workflow, while yielding comparable outcomes. In addition, we introduce the optimization strategy that alternatively performs optimization on the direct and latent crystal representations. This dual-level relaxation approach can effectively escape local minima defined by different objective gradients, thus increasing the success rate of generating complex structures satisfying the target local environments. This framework can be extended to systems consisting of multi-components and multi-environments, providing a scalable route to generate material structures with the target local environment.

conditional VAE↗

Machine learning pipeline to predict defect behavior in metallic alloy systems

The interaction between defect and solute atoms is critical to the thermodynamic and kinetic behavior of metallic alloys under exposure to high-energy radiation, causing irradiation damage in materials. Radiation can generate non-equilibrium concentrations of point defects such as vacancies and interstitials. The excess point defects not only accelerate diffusional processes such as precipitation that cause radiation embrittlement, but also change the pathway of phase transformations, including nucleation processes. Understanding these defect behaviors is complicated by the challenge and complexity of addressing each possible local and discrete distribution of environments and chemical interactions around targeted defects-solute or solute-solute complexes. To resolve the challenge, machine learning regression techniques have emerged as powerful tools that can train and construct an energy model to accurately describe the chemical interactions of solutes and defects. In Fiscal Year 2022, the work focused on the workflow development and demonstration using machine learning regression, density functional theory, cluster expansion, and Monte Carlo simulation to predict the effects of ternary solute elements (e.g., aluminum and molybdenum) and point defects on the Cr-rich $\alpha^{\prime}$ precipitation in multicomponent FeCr model alloys. The computational outcomes include the prediction of the ternary phase diagram, vacancy formation energy for different compositions, and the effect of vacancies on the nucleation of Cr-rich clusters. The simulations predict a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from $\alpha^{\prime}$ precipitates. Additionally, the simulations show the formation of Cr-vacancy clusters as the initial nuclei for stable nucleation and growth of $\alpha^{\prime}$ particles. The results demonstrate important outcomes and applications of using machine learning pipeline to study model or commercial alloys with multicomponent solute species and point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Interplay of vibration- and environment-assisted energy transfer

Abstract We study the interplay between two environmental influences on excited state energy transfer in photosynthetic light harvesting complexes, namely, vibrationally assisted energy transfer (VAET) and environment-assisted quantum transport (ENAQT), considering a dimeric chromophore donor–acceptor model as a prototype for larger systems. We demonstrate how the basic features of the excitonic energy transfer are influenced by these two environments, both separately and together, with the environment being fully quantum in the case of VAET and treated in the Haken–Strobl–Reineker classical limit in the case of ENAQT. Our results reveal that in the weak noise regime, the presence of a classical noise source is detrimental to the energy transfer that is resonantly assisted by the exciton-vibration interactions intrinsic to VAET. In the strong noise regime we reproduce all the features of ENAQT, including the turnover into a Zeno regime where energy transfer is suppressed, and VAET is insignificant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ammonia Synthesis by a Supported Iron-Lithium Hydride Precatalyst: Silicon Nitride Support Enabled Synthesis and Nitrogen Reservoir Dynamics

Amorphous silicon nitride (Si 3 N 4 ) is an unconventional support for the chemisorption of organometallic complexes and offers potential improvements in active site stability and reactivity through enhanced metal-nitrogen covalency and orbital overlap in bonding interactions with the nitride framework. Here, we show that silicon nitride-supported iron mesityl complexes display divergent reactivity compared to their silica-supported homologues, resisting metallic particle formation under reducing pretreatment conditions (exposure to excess organolithium reagents) and maintaining active iron/lithium speciation under ammonia synthesis conditions that is absent on the oxide support. When the organometallic iron complex on silicon nitride is exposed to excess n-butyllithium, iron remains isolated, catalyzing the conversion of butyllithium to lithium hydride, resulting in a divalent iron site in a polyhydride environment. In contrast, the silica-supported complex is converted to reduced iron clusters without forming persistent isolated hydrides. These structural differences lead to markedly different catalytic behaviors under ammonia synthesis conditions. The Li/Fe/Si 3 N 4 catalyst is highly active (7.5 mol NH 3 /mol Fe/h at 300 °C, 10 bar, or 46 mol NH 3 /mol Fe/h at 400 °C, 10 bar), while both the silica-supported analog and the nonlithiated Si 3 N 4 -supported species are inactive. Notably, this activity is enhanced relative to previously reported iron-lithium hydride composite catalysts (0.43–4.1 mol NH 3 /mol Fe/h at 300 °C, 10 bar) and relative to the industrial benchmark promoted iron catalyst KM1 (3.0 mol NH 3 /mol Fe/h at 400 °C, 10 bar). The catalyst activation and LiH/LiNH x nitrogen reservoir dynamics for Li/Fe/Si 3 N 4 are studied by X-ray Absorption, Mössbauer, and in situ DRIFT spectroscopies and isotopic exchange kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface chemistry of neutron irradiated tungsten in a high-temperature multi-material environment

Deuterium retention was measured on neutron irradiated tungsten samples where one side of the samples had a visually clean metallic luster and the opposite side appeared to have a reacted surface film. Deuterium plasma exposure and subsequent thermal desorption from the reacted surface side produced spectra with larger total deuterium desorption at lower temperatures than from the clean surface side. For neutron irradiation, these W disk samples were installed in an irradiation capsule in such a way that one side of W sample was in contact with the surface of another W sample, and the opposite side was in contact with a SiC temperature monitor. The composition of the reacted surface was investigated using X-ray photoelectron spectroscopy and showed that SiC had interdiffused into the W samples. Neutron enhanced diffusion likely contributed to this as SiC and W are stable at temperatures exceeding the irradiation temperature. Results highlight the need to consider the surface chemistry of samples in drawing conclusions on hydrogen isotope retention of W materials and also illustrate the complexity of multi-material nuclear environments expected in fusion devices.

36 MATERIALS SCIENCE↗

Biodiversity and Global Health: Intersection of Health, Security, and the Environment

One of the biggest consequences of large-scale environmental change is the loss of biodiversity. Recent studies predict a loss of 1 million species in the near future. Biodiversity loss and land use change through anthropogenic disturbance are known to affect disease exposure, disease severity, and disease impacts. It is becoming increasingly clear that biodiversity loss will lead to an increase in infectious diseases in certain regions. Changes in biodiversity may contain important signatures for prediction of infectious diseases and outbreaks. Here, we argue that areas of high or rapid biodiversity loss will be critical to monitor under the umbrella of global health security. Global Health Security consists of the actions and activities required to reduce the impact of public health events in populations living in different geographic regions and across international borders. Like infectious diseases, climate change and other causes of environmental changes do not respect international borders and are becoming more widespread in all parts of the world. Here, the relationships among biodiversity, climate and environmental changes, and pathogen prevalence are dynamic, context dependent, and complex. Accounting for this complexity requires the inclusion of the environment sector, presently missing, when evaluating the potential of global health security actions for mitigating disease risks.

59 BASIC BIOLOGICAL SCIENCES↗

Virus-Like Particles (VLPs) as a Platform for Hierarchical Compartmentalization

Hierarchically self-assembled structures are common in biology, but it is often challenging to design and fabricate synthetic analogs. The archetypal cell is defined by hierarchically organized multicompartmentalized structures with boundaries that delineate the interior from exterior environments and is an inspiration for complex functional materials. Here, we have demonstrated an approach to the design and construction of a nested protein cage system that can additionally incorporate the packing of other functional macromolecules and exhibit some of the features of a minimal synthetic cell-like material. We have demonstrated a strategy for controlled co-packaging of subcompartments, ferritin (Fn) cages, together with active cellobiose-hydrolyzing β-glycosidase enzyme macromolecules, CelB, inside the sequestered volume of the bacteriophage P22 capsid. Using controlled in vitro assembly, we were able to modulate the stoichiometry of Fn cages and CelB encapsulated inside the P22 to control the degree of compartmentalization. The co-encapsulated enzyme CelB showed catalytic activity even when packaged at high total macromolecular concentrations comparable to an intracellular environment. Here, this approach could be used as a model to create synthetic protein-based protocells that can confine smaller functionalized proto-organelles and additional macromolecules to support a range of biochemical reactions.

59 BASIC BIOLOGICAL SCIENCES↗

Accurate Free Energies for Complex Condensed-Phase Reactions Using an Artificial Neural Network Corrected DFTB/MM Methodology

Semiempirical methods like density functional tight-binding (DFTB) allow extensive phase space sampling, making it possible to generate free energy surfaces of complex reactions in condensed-phase environments. Such a high efficiency often comes at the cost of reduced accuracy, which may be improved by developing a specific reaction parametrization (SRP) for the particular molecular system. Thiol–disulfide exchange is a nucleophilic substitution reaction that occurs in a large class of proteins. Its proper description requires a high-level ab initio method, while DFT-GAA and hybrid functionals were shown to be inadequate, and so is DFTB due to its DFT-GGA descent. We develop an SRP for thiol–disulfide exchange based on an artificial neural network (ANN) implementation in the DFTB+ software and compare its performance to that of a standard SRP approach applied to DFTB. Furthermore, as an application, we use both new DFTB-SRP as components of a QM/MM scheme to investigate thiol–disulfide exchange in two molecular complexes: a solvated model system and a blood protein. Demonstrating the strengths of the methodology, highly accurate free energy surfaces are generated at a low cost, as the augmentation of DFTB with an ANN only adds a small computational overhead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic interactions at the mineral–organic matter interface

Minerals are widely assumed to protect organic matter (OM) from degradation in the environment, promoting the persistence of carbon in soil and sediments. In this Review, we describe the mechanisms and processes operating at the mineral–organic interface as they relate to OM transformation dynamics. A broad set of interactions occur, with minerals adsorbing organic compounds to their surfaces and/or acting as catalysts for organic reactions. Minerals can serve as redox partners for OM through direct electron transfer or by generating reactive oxygen species, which then oxidize OM. Finally, the compartmentalization of soil and sediment by minerals creates unique microsites that host diverse microbial communities. Acknowledgement of this multiplicity of interactions suggests that the general assumption that the mineral matrix provides a protective function for OM is overly simplistic. Future work must recognize adsorption as a condition for further reactions instead of as a final destination for organic adsorbates, and should consider the spatial and functional complexity that is characteristic of the environments where mineral–OM interactions are observed.

54 ENVIRONMENTAL SCIENCES↗

Managing Software Provenance to Enhance Reproducibility in Computational Research

Scientific processes rely on software as an important tool for data acquisition, analysis, and discovery. Over the years, sustainable software development practices have made progress in being considered as an integral component of research. However, management of computation-based scientific studies is often left to individual researchers who design their computational experiments based on personal preferences and the nature of the study. Here, we believe that the quality, efficiency, and reproducibility of computation-based scientific research can be improved by explicitly creating an execution environment that allows researchers to provide a clear record of traceability. This is particularly relevant to complex computational studies in high-performance computing (HPC) environments. In this article, we review the documentation required to maintain a comprehensive record of HPC computational experiments for reproducibility. We also provide an overview of tools and practices that we have developed to perform such studies around Flash-X, a multiphysics scientific software.

97 MATHEMATICS AND COMPUTING↗

Exploring the Use of Large Immersive Display Systems in the Nuclear Industry

Large immersive display systems play a critical role in the nuclear industry by enabling advanced training, design reviews, scientific visualization, and safety simulations. These systems, such as CAVE and powerwalls, allow engineers and operators to interact with virtual nuclear environments in real-time, providing a deeper understanding of complex systems. Their ability to simulate real-world scenarios for testing and optimization in a safe, controlled environment ensures that operators and engineers can refine process, enhance safety protocols, and troubleshoot complex challenges. This article outlines key lessons learned from deploying these systems, practical insights into their applications, and considerations for future improvements, aiming to guide their broader adoption and effective use in the nuclear industry.

99 - GENERAL AND MISCELLANEOUS↗

Radiosonde Observations of Environments Supporting Deep Moist Convection Initiation during RELAMPAGO-CACTI

The Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) and Cloud, Aerosol, and Complex Terrain Interactions (CACTI) projects deployed a high-spatiotemporal-resolution radiosonde network to examine environments supporting deep convection in the complex terrain of central Argentina. This study aims to characterize atmospheric profiles most representative of the near-cloud environment (in time and space) to identify the mesoscale ingredients affecting storm initiation and growth. Spatiotemporal autocorrelation analysis of the soundings reveals that there is considerable environmental heterogeneity, with boundary layer thermodynamic and kinematic fields becoming statistically uncorrelated on scales of 1–2 h and 30 km. Using this as guidance, we examine a variety of environmental parameters derived from soundings collected within close proximity (30 km in space and 30 min in time) of 44 events over 9 days where the atmosphere either: 1) supported the initiation of sustained precipitating convection, 2) yielded weak and short-lived precipitating convection, or 3) produced no precipitating convection in disagreement with numerical forecasts from convection-allowing models (i.e., Null events). There are large statistical differences between the Null event environments and those supporting any convective precipitation. Null event profiles contained larger convective available potential energy, but had low free-tropospheric relative humidity, higher freezing levels, and evidence of limited horizontal convergence near the terrain at low levels that likely suppressed deep convective growth. Here, we also present evidence from the radiosonde and satellite measurements that flow–terrain interactions may yield gravity wave activity that affects CI outcome.

54 ENVIRONMENTAL SCIENCES↗

Pyrrophens: Pyrrole-Based Hexadentate Ligands Tailor-Made for Uranyl (UO 2 2+ ) Coordination and Molecular Recognition

Derivatives of a novel pyrrole-containing Schiff base ligand system (called “pyrrophen”) are presented which feature substituted phenylene linkers (R 1 = R 2 = H (H 2 L 1 ); R 1 = R 2 = CH 3 (H 2 L 2 )) and a binding pocket modeled after macrocyclic species. These ligands bind neutral CH 3 OH in the solid state through pyrrolic hydrogen-bonding. Here, the interaction of the uranyl cation (UO 2 2+ ) and H 2 L 1–2 yields planar hexagonal bipyramdial uranyl complexes, while the Cu 2+ and Zn 2+ complexes were found to self-assemble as dinuclear helicate complexes (M 2 L 2 ) with H 2 L 1 under identical conditions. The favorable binding of UO 2 2+ over Zn 2+ provides insight into the molecular recognition of uranyl over other metal species. Structural features of these complexes are examined with special attention to features of the UO 2 2+ coordination environment which distinguish them from other related salophen and porphyrinoid complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of Turbulence and Dispersion in Multiscale Atmospheric Simulations over Complex Urban Terrain during the Joint Urban 2003 Field Campaign

Abstract This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment. Significance Statement Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.

42 ENGINEERING↗