Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “process interactions”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

Modeling diffusion and depletion in high-aspect-ratio atomic layer deposition processes: Process parameters and manufacturing impacts

Atomic layer deposition (ALD) is a powerful technique for modifying the surface chemistry and properties of substrates with complex and nonplanar topologies. However, achieving uniform and conformal deposition on ultrahigh-aspect-ratio substrates remains challenging, typically requiring large quantities of precursors and long exposure times. Furthermore, process optimization is often performed empirically and involves substantial trial and error. In this work, we perform a combined experimental and computational study of ALD Al 2 O 3 infiltration into silica aerogel monoliths (aspect ratio >10 5 ). A reaction-diffusion model is used to explore the effects of key processing parameters, namely, exposure time per dose, precursor source temperature, number of aerogels in the reactor, and reactor volume. The model is based on quasi-static mode ALD, where the dosed precursor is held in the chamber for a fixed period of time before purging. We analyze the trade-offs between process throughput and precursor utilization for each of these parameters. Furthermore, we investigate the co-optimization and interactions between multiple process parameters, demonstrating the potential for further improvements. Furthermore, this physics-based model can be used to identify a set of process parameters for high-aspect-ratio ALD that meet specific manufacturing objective functions, including throughput, cost, and sustainability.

Aerogel↗

Engineering a new tripartite split-ccGFP system from Corynactis californica for detecting protein–protein interactions

Protein-protein interactions (PPIs) are critical to a range of biological processes and, consequently, aberrant interactions are implicated in many disorders. The study of the complex networks of PPIs promises to elucidate undiscovered roles in cellular processes and the mechanisms of disease. To accomplish this, tools to effectively sense PPIs are necessary. Effective PPI sensors must rapidly detect interactions in real-time with high sensitivity without perturbing the proteins of interest (POIs) under study. Split fluorescent proteins have previously been used to successfully monitor PPIs, in part due to the small size of the tags. Here, we developed an optimized tripartite split GFP system based on Corynactis californica GFP (ccGFP) to detect PPIs in vitro. In this sensor system, ccGFP fragments ccGFP10 and ccGFP11 are tagged to two POIs. PPIs can then be detected via fluorescence by complementation to the third fragment, ccGFP1-9, which reconstitutes functional ccGFP. The optimized ccGFP system shows improved detection kinetics and pH and temperature stability compared to a previous system. We then validated the sensor by monitoring PPIs in two model systems: attractive/repulsive coiled-coils and rapamycin-inducible FRB/FKBP heterodimerization. Finally, we developed an anti-tripartite ccGFP single-chain variable fragment (scFv), which could enable versatile detection of identified protein-protein complexes.

59 BASIC BIOLOGICAL SCIENCES↗

Lepto-axiogenesis

We propose a baryogenenesis mechanism that uses a rotating condensate of a Peccei-Quinn (PQ) symmetry breaking field and the dimension-five operator that gives Majorana neutrino masses. The rotation induces charge asymmetries for the Higgs boson and for lepton chirality through sphaleron processes and Yukawa interactions. The dimension-five interaction transfers these asymmetries to the lepton asymmetry, which in turn is transferred into the baryon asymmetry through the electroweak sphaleron process. QCD axion dark matter can be simultaneously produced by dynamics of the same PQ field via kinetic misalignment or parametric resonance, favoring an axion decay constant ƒ a ≲ 10 10 GeV, or by conventional misalignment and contributions from strings and domain walls with ƒ a ~ 10 11 GeV. The size of the baryon asymmetry is tied to the mass of the PQ field. In simple supersymmetric theories, it is independent of UV parameters and predicts the supersymmtry breaking mass scale to be $ \mathcal{O} $(10 - 10 4 ) TeV, depending on the masses of the neutrinos and whether the condensate is thermalized during a radiation or matter dominated era. The high supersymmetry breaking mass scale may be free from cosmological and flavor/CP problems. We also construct a theory where TeV scale supersymmetry is possible. Parametric resonance may give warm axions, and the radial component of the PQ field may give signals in rare kaon decays from mixing with the Higgs and in dark radiation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗

Bulk viscosity from Urca processes: n p e μ matter in the neutrino-transparent regime

We study the bulk viscosity of moderately hot and dense, neutrino-transparent relativistic npeμ matter arising from weak-interaction direct Urca processes. This work parallels our recent study of the bulk viscosity of npeμ matter with a trapped neutrino component. The nuclear matter is modeled in a relativistic density functional approach with two different parametrizations—DDME2 (which does not allow for the low-temperature direct-Urca process at any density) and NL3 (which allows for low-temperature direct-Urca process above a low-density threshold). Here, we compute the equilibration rates of Urca processes of neutron decay and lepton capture, as well as the rate of the muon decay, and find that the muon decay process is subdominant to the Urca processes at temperatures T ≥ 3 MeV in the case of DDME2 model and T ≥ 1 MeV in the case of NL3 model. Thus, the Urca-process-driven bulk viscosity is computed with the assumption that pure leptonic reactions are frozen. As a result the electronic and muonic Urca channels contribute to the bulk viscosity independently and at certain densities the bulk viscosity of npeμ matter shows a double-peak structure as a function of temperature instead of the standard one-peak (resonant) form. In the final step, we estimate the damping timescales of density oscillations by the bulk viscosity. We find that, e.g., at a typical oscillation frequency f = 1~kHz, the damping of oscillation is most efficient at temperatures 3 ≤ T ≤ 5~MeV and densities n B ≤ 2n 0 where they can affect the evolution of the post-merger object.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simulation of Compound Flooding Using River‐Ocean Two‐Way Coupled E3SM Ensemble on Variable‐Resolution Meshes

Abstract Coastal zone compound flooding (CF) can be caused by the interactive fluvial and oceanic processes, particularly when coastal backwater propagates upstream and interacts with high river discharge. The modeling of CF is limited in existing Earth System Models (ESMs) due to coarse mesh resolutions and one‐way coupled river‐ocean components. In this study, we present a novel multi‐scale coupling framework within the Energy Exascale Earth System Model (E3SM), integrating global atmosphere and land with interactively coupled river and ocean models using different meshes with refined resolutions near the coastline. To evaluate this framework, we conducted ensemble simulations of a CF event (Hurricane Irene in 2011) in a Mid‐Atlantic estuary. The results demonstrate that the novel E3SM configuration can reasonably reproduce river discharge and sea surface height variations. The two‐way river‐ocean coupling improves the representation of coastal backwater effects at the terrestrial‐aquatic interface that are caused by the combined actions of tide and storm surge during the CF event, thus providing a valuable modeling tool for better understanding the river‐estuary‐ocean dynamics in extreme events under climate change. Notably, our results show that the most significant CF impacts occur when the highest storm surge generated by a tropical cyclone meets with a moderate river discharge. This study highlights the state‐of‐the‐art advancements developed within E3SM for simulating multi‐scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗

Giant Angular Nernst Effect in the Organic Metal α-(BEDT-TTF) 2 KHg(SCN) 4

We have detected a large Nernst effect in the charge density wave state of the multiband organic metal α-(BEDT-TTF) 2 KHg(SCN) 4 . We find that apart from the phonon drag effect, the energy relaxation processes that govern the electron–phonon interactions and the momentum relaxation processes that determine the mobility of the q1D charge carriers have a significant role in observing the large Nernst signal in the CDW state in this organic metal. The emphasised momentum relaxation dynamics in the low field CDW state (CDW 0 ) is a clear indicator of the presence of a significant carrier mobility that might be the main source for observation of the largest Nernst signal. The momentum relaxation is absent with increasing angle and magnetic field, i.e., in the high-field CDW state (CDW x ) as evident from the much smaller Nernst effect amplitude in this state. In this case, only the phonon drag effect and electron–phonon interactions are contributing to the transverse thermoelectric signal. Our findings advance and change previous observations on the complex properties of this organic metal.

36 MATERIALS SCIENCE↗

Potential Constraints to Neutrino-Nucleus Interactions Based on Electron Scattering Data

A thorough understanding of neutrino-nucleus interactions physics is crucial to achieving precision goals in broader neutrino physics programs. The complexity of nuclei comprising the detectors and limited understanding of their weak response constitutes one of the biggest systematic uncertainties in neutrino experiments - both at intermediate energies affecting the short- and long-baseline neutrino programs as well as at lower energies affecting coherent scattering neutrino programs. While electron and neutrino interactions are different at the primary vertex, many underlying relevant physical processes in the nucleus are the same in both cases, and electron scattering data collected with precisely controlled kinematics, large statistics and high precision allows one to constrain nuclear properties and specific interaction processes. To this end, electron-nucleus scattering experiments provide vital complementary information to test, assess and validate different nuclear models and event generators intended to be used in neutrino experiments. In fact, for many decades, the study of electron scattering off a nucleus has been used as a tool to probe the properties of that nucleus and its electromagnetic response. While previously existing electron scattering data provide important information, new and proposed measurements are tied closely to what is required for the neutrino program in terms of expanding kinematic reach, the addition of relevant nuclei and information on the final states hadronic system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

First-principles calculations of defects and electron–phonon interactions: Seminal contributions of Audrius Alkauskas to the understanding of recombination processes

First-principles calculations of defects and electron–phonon interactions play a critical role in the design and optimization of materials for electronic and optoelectronic devices. The late Audrius Alkauskas made seminal contributions to developing rigorous first-principles methodologies for the computation of defects and electron–phonon interactions, especially in the context of understanding the fundamental mechanisms of carrier recombination in semiconductors. Alkauskas was also a pioneer in the field of quantum defects, helping to build a first-principles understanding of the prototype nitrogen-vacancy center in diamond, as well as identifying novel defects. Here, we describe the important contributions made by Alkauskas and his collaborators and outline fruitful research directions that Alkauskas would have been keen to pursue. Audrius Alkauskas’ scientific achievements and insights highlighted in this article will inspire and guide future developments and advances in the field.

36 MATERIALS SCIENCE↗

A statistical mechanics approach to macroscopic limits of car-following traffic dynamics

Herein we study the derivation of macroscopic traffic models from car-following vehicle dynamics by means of hydrodynamic limits of an Enskog-type kinetic description. We consider the superposition of Follow-the-Leader (FTL) interactions and relaxation towards a traffic-dependent Optimal Velocity (OV) and we show that the resulting macroscopic models depend on the relative frequency between these two microscopic processes. If FTL interactions dominate then one gets an inhomogeneous Aw–Rascle–Zhang model, whose (pseudo) pressure and stability of the uniform flow are precisely defined by some features of the microscopic FTL and OV dynamics. Conversely, if the rate of OV relaxation is comparable to that of FTL interactions then one gets a Lighthill–Whitham–Richards model ruled only by the OV function. We further confirm these findings by means of numerical simulations of the particle system and the macroscopic models. Unlike other formally analogous results, our approach builds the macroscopic models as physical limits of particle dynamics rather than assessing the convergence of microscopic to macroscopic solutions under suitable numerical discretisations.

97 MATHEMATICS AND COMPUTING↗

Deep reinforcement learning control of hydraulic fracturing

Hydraulic fracturing is a technique to extract oil and gas from shale formations, and obtaining a uniform proppant concentration along the fracture is key to its productivity. Recently, various model predictive control schemes have been proposed to achieve this objective. But such controllers require an accurate and computationally efficient model which is difficult to obtain given the complexity of the process and uncertainties in the rock formation properties. In this article, we design a model-free data-based reinforcement learning controller which learns an optimal control policy through interactions with the process. Deep reinforcement learning (DRL) controller is based on the Deep Deterministic Policy Gradient algorithm that combines Deep-Q-network with actor-critic framework. In addition, we utilize dimensionality reduction and transfer learning to quicken the learning process. We show that the controller learns an optimal policy to obtain uniform proppant concentration despite the complex nature of the process while satisfying various input constraints.

42 ENGINEERING↗

A Concept of a Convection–Cloud Chamber to Study Aerosol–Cloud–Drizzle Interactions

Understanding and quantifying the full chain of processes from aerosol activation to drizzle formation, and the associated feedbacks to the aerosol chemical and physical properties, all within a turbulent cloud are some of the toughest challenges in atmospheric chemistry and physics and are keys to the cloud–precipitation puzzle. This paper describes a concept for a new type of research facility consisting of a cloud chamber plus associated instrumentation and computational models, to explore aerosol–cloud interactions and processing, cloud optical properties, entrainment–cloud interactions, and quantitative assessment of drizzle onset. The envisioned design is for a 3 m × 3 m × 9 m chamber, such that the height is sufficient to achieve long lifetimes for aerosol processing and for significant drizzle growth by collision and coalescence. A suite of computational tools for simulating microphysical properties in the chamber provides a digital twin for designing the chamber and a range of example experiments. Theory and test results from novel remote sensing systems for exploring chemical and physical interactions and evolution of aerosols, cloud droplets, and drizzle within turbulent clouds are described. Testing of technology needed for the operation of a large-volume chamber, including aerosol generation methods and novel materials for water vapor boundary conditions, is described. Simulations suggest that spatially uniform turbulence and microphysical properties can be sustained in a steady state, with reasonable aerosol and water vapor fluxes, and that substantial drizzle can be produced through collision and coalescence of cloud droplets. Remaining challenges for more detailed engineering design and a discussion of possible first-light experiments are described.

54 ENVIRONMENTAL SCIENCES↗

Nitroxide Radical Polymer–Solvent Interactions and Solubility Parameter Determination

Redox-active polymers such as macromolecular nitroxide radicals have been studied as electrode materials for organic batteries and electronics. Polymer–solvent interactions are essential to processing and device performance, but macromolecular nitroxide radical–solvent interactions are currently not well described. In this work, the Hildebrand and Hansen solubility parameters of poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl methacrylate) (PTMA), oxidized PTMA (PTMA + ), and PTMA’s precursor (PTMPM) are determined using both experimental and group contribution methods for the first time. This work indicates that the hydrogen-bonding Hansen solubility parameter (δ h ) and the solubility sphere radii (R) provide the best prediction of the macromolecular radical’s interaction with solvents. From these solubility parameters, the group contribution values for the nitroxide and oxoammonium cation were then calculated. It is shown that this information allows for the prediction of polymer–solvent interactions for other nitroxide-based macromolecular radicals. Lastly, the discovered solubility parameters are used to predict PTMA electrode formulations for batteries that outperform controls.

36 MATERIALS SCIENCE↗

Investigating Covalent Bonding in f-elements using Gas-phase Ion Chemistry

Introduction In the reprocessing of f-elements present in used nuclear fuels, a variety of diglycolamides (DGA’s) are used as extractants for actinide partitioning. In particular, the Actinide-Lanthanide Separation (ALSEP) process typically utilizes either the N,N,N’,N’-tetraoctyl diglycolamide (TODGA) or N,N,N',N'-tetra-2-ethylhexyl diglycolamide (T2EHDGA) extractant ligands following the partitioning of uranium and plutonium from used nuclear fuel. To better understand fundamental interactions in these processes, covalent bonding of several f-elements with diglycolamides, primarily TODGA, is investigated in the gas phase using nanospray ionization and a quadrupole time-of-flight mass spectrometer. Further, analysis of the identity and relative strength of the cluster is enabled by MS2 isolation and collision induced dissociation. Methods Metal ion cluster analysis was completed using a Bruker mircOTOF-Q II quadrupole time-of-flight mass spectrometer equipped with a CaptiveSpray nanospray ion source. Metal:ligand solutions were prepared as 30 µM europium nitrate, samarium nitrate, cerium nitrate, or holmium nitrate and 3 µM DGA in acetonitrile or a 50:50 mixture of acetonitrile: isopropanol. Cluster mass spectra and collision-induced dissociation experiments were conducted in positive mode. Preliminary data To examine the patterns and relative strength of lanthanide: DGA interactions, MS2 experiments were completed with each lanthanide species listed above. Preliminary analyses of samarium and europium TODGA clusters suggest several combinations of TODGA and nitrate forming. The samarium cluster experiments yielded Sm(TODGA)x clusters with a samarium:TODGA ratio of up to 1:7 able to be isolated and evidence of greater ratios present in the mass spectrum. This is surprising, as metal clusters are not expected to have a coordination space able to accommodate this many ligands as large as TODGA. MS2 experiments show that, at higher ratios and with sufficient collision energy, entire TODGA ligands are removed instead of being fragmented. These experiments show that a lower collision energy is required to remove ligands as the number of bound TODGA’s increases, suggesting that in larger clusters, ligands are more delicately complexed to the metal. In addition to Sm(TODGA)x, several clusters were observed with nitrate ions bound to the metal in addition to TODGA. With a single nitrate ion, clusters with up to six TODGA’s were able to be isolated. In a similar pattern to the samarium clusters with only TODGA, less collision energy is required to eliminate one or more TODGA’s with increasing size. MS2 experiments suggest clusters with one nitrate appear to be of an equivalent or greater stability to clusters which replace the nitrate with a TODGA, as more collision energy is required to remove a TODGA ligand. These species with one nitrate are also in a higher abundance than the equivalent TODGA only cluster. With two nitrate ions, only clusters with a single TODGA were able to be isolated. Analogous europium experiments resulted in very similar clusters. Ratios of up to 1:7 Eu:TODGA were able to be isolated, and clusters with one nitrate and up to five TODGAs were isolated. In clusters with two nitrate ions, one or two TODGA’s could also be bound to the metal. MS2 experiments suggested, similarly to samarium, that larger clusters required less collision energy to eliminate TODGA. Europium clusters with one nitrate are in greater abundance and are stronger than the equivalent cluster which replaces the nitrate with TODGA. Similar analysis with cerium and holmium is ongoing, as well as analysis with other DGA ligands to compare relative strengths of the lanthanide metals with various extractant ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatiotemporal Studies of Soluble Inorganic Nanostructures with X‐rays and Neutrons

Abstract This Review addresses the use of X‐ray and neutron scattering as well as X‐ray absorption to describe how inorganic nanostructured materials assemble, evolve, and function in solution. We first provide an overview of techniques and instrumentation (both large user facilities and benchtop). We review recent studies of soluble inorganic nanostructure assembly, covering the disciplines of materials synthesis, processes in nature, nuclear materials, and the widely applicable fundamental processes of hydrophobic interactions and ion pairing. Reviewed studies cover size regimes and length scales ranging from sub‐Ångström (coordination chemistry and ion pairing) to several nanometers (molecular clusters, i.e. polyoxometalates, polyoxocations, and metal‐organic polyhedra), to the mesoscale (supramolecular assembly processes). Reviewed studies predominantly exploit 1) SAXS/WAXS/SANS (small‐ and wide‐angle X‐ray or neutron scattering), 2) PDF (pair‐distribution function analysis of X‐ray total scattering), and 3) XANES and EXAFS (X‐ray absorption near‐edge structure and extended X‐ray absorption fine structure, respectively). While the scattering techniques provide structural information, X‐ray absorption yields the oxidation state in addition to the local coordination. Our goal for this Review is to provide information and inspiration for the inorganic/materials science communities that may benefit from elucidating the role of solution speciation in natural and synthetic processes.

Yin, Jia‐Fu↗

Gas-Phase Stability of Large Lanthanide:Ligand Clusters Evaluated Using Collision-Induced Dissociation

Introduction In the reprocessing of f-elements present in used nuclear fuels, a variety of diglycolamides (DGA’s) are used as extractants for actinide partitioning. In particular, the Actinide-Lanthanide Separation (ALSEP) process typically utilizes either the N,N,N’,N’-tetraoctyl diglycolamide (TODGA) or N,N,N',N'-tetra-2-ethylhexyl diglycolamide (T2EHDGA) extractant ligands following the partitioning of uranium and plutonium from used nuclear fuel. To better understand fundamental interactions in these processes, covalent bonding of several f-elements with diglycolamides, primarily TODGA, is investigated in the gas phase using nanospray ionization and a quadrupole time-of-flight mass spectrometer. Further, analysis of the identity and relative strength of the cluster is enabled by MS2 isolation and collision induced dissociation. Methods Metal ion cluster analysis was completed using a Bruker (Billerica, MA, USA) mircOTOF-Q II quadrupole time-of-flight mass spectrometer with a CaptiveSpray nanospray ion source. Detection was accomplished using positive ionization mode. Metal: ligand solutions were assembled as 30 µM europium nitrate, samarium nitrate, cerium nitrate, or holmium nitrate and 3 µM DGA in acetonitrile or a 50:50 mixture of acetonitrile: isopropanol. Preliminary data The samarium cluster experiments yielded clusters with a samarium:TODGA ratio of up to 1:7 able to be isolated and evidence of greater ratios present in the mass spectrum. This is surprising, as metal clusters are not expected to have a coordination space able to accommodate this many TODGA ligands, due to its size and tridenticity. Collisional activation of [Sm(TODGA)3]3+ suggested loss of a TODGA radical cation, in addition to ligand fragmentation. In contrast, activation of clusters with higher Sm:TODGA ratios resulted in loss of entire ligands, with no evidence of fragmentation. A lower collision energy was required to remove ligands as the number of bound TODGAs increased, suggesting that in larger clusters, ligands are more delicately complexed to the metal. In addition, several clusters were observed with the composition [Sm(NO3)x(TODGA)n x]+3 x. With a single nitrate ion, clusters with up to six TODGAs were able to be isolated. In a similar pattern to the samarium clusters containing only TODGA, less collision energy was required to eliminate one or more TODGAs with increasing size. Clusters with composition [Sm(NO3)(TODGA)n-1]2+ appeared in lower abundance and were more collisionally stable than [Sm(TODGA)n]3+ clusters. With two nitrate ions, only clusters with a single TODGA were able to be isolated. Analogous europium experiments resulted in similar clusters. Ratios of up to 1:7 Eu:TODGA and clusters with one nitrate and up to five TODGAs were isolated. In clusters with two nitrate ions, only one or two TODGAs were observed to be bound. Similar to samarium, MS2 experiments with the Eu clusters suggested that larger clusters required less collision energy to eliminate TODGA. Europium clusters with the composition [Eu(NO3)(TODGA)n-1]2+ were observed in greater abundance and with greater stability than the equivalent cluster with the composition [Eu(TODGA)n]3+. Novel Aspect These are the first reported Ln:TODGA clusters, allowing us to begin to investigate intrinsic complexation of lanthanides with process-relevant ligands.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Spatiotemporal Studies of Soluble Inorganic Nanostructures with X‐rays and Neutrons

This Review addresses the use of X-ray and neutron scattering as well as X-ray absorption to describe how inorganic nanostructured materials assemble, evolve, and function in solution. We first provide an overview of techniques and instrumentation (both large user facilities and benchtop). We review recent studies of soluble inorganic nanostructure assembly, covering the disciplines of materials synthesis, processes in nature, nuclear materials, and the widely applicable fundamental processes of hydrophobic interactions and ion pairing. Reviewed studies cover size regimes and length scales ranging from sub-Ångström (coordination chemistry and ion pairing) to several nanometers (molecular clusters, i.e. polyoxometalates, polyoxocations, and metal-organic polyhedra), to the mesoscale (supramolecular assembly processes). Reviewed studies predominantly exploit 1) SAXS/WAXS/SANS (small- and wide-angle X-ray or neutron scattering), 2) PDF (pair-distribution function analysis of X-ray total scattering), and 3) XANES and EXAFS (X-ray absorption near-edge structure and extended X-ray absorption fine structure, respectively). While the scattering techniques provide structural information, X-ray absorption yields the oxidation state in addition to the local coordination. Our goal for this Review is to provide information and inspiration for the inorganic/materials science communities that may benefit from elucidating the role of solution speciation in natural and synthetic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗