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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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Intermittent cluster dynamics and temporal fractional diffusion in a bulk metallic glass

Glassy solids evolve towards lower-energy structural states by physical aging. This can be characterized by structural relaxation times, the assessment of which is essential for understanding the glass’ time-dependent property changes. Conducted over short times, a continuous increase of relaxation times with time is seen, suggesting a time-dependent dissipative transport mechanism. By focusing on micro-structural rearrangements at the atomic-scale, we demonstrate the emergence of sub-diffusive anomalous transport and therefore temporal fractional diffusion in a metallic glass, which we track via coherent x-ray scattering conducted over more than 300,000 s. At the longest probed decorrelation times, a transition from classical stretched exponential to a power-law behavior occurs, which in concert with atomistic simulations reveals collective and intermittent atomic motion. Our observations give a physical basis for classical stretched exponential relaxation behavior, uncover a new power-law governed collective transport regime for metallic glasses at long and practically relevant time-scales, and demonstrate a rich and highly non-monotonous aging response in a glassy solid, thereby challenging the common framework of homogeneous aging and atomic scale diffusion.

42 ENGINEERING↗
DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗
DOE OSTI2020

Microscopic Theory of Long-Time Center-of-Mass Self-Diffusion and Anomalous Transport in Ring Polymer Liquids

We construct a microscopic theory at the level of segment-scale correlated space–time intermolecular forces for the long-time center-of-mass (CM) diffusion constant and intermediate-time non-Fickian transport in dense solutions and melts of ring polymers. The approach combines ideas of polymer, colloid, and liquid-state statistical mechanics to quantify how the multifractal intra-ring conformational structure and inter-ring packing correlations determine dynamic caging constraints and time-dependent friction. Breakdown of Rouse theory is predicted to occur due to length scale-dependent temporal correlation of forces exerted on pairs of tagged ring segments from surrounding polymers. At large enough degrees of polymerization (N), a stronger scaling of the CM diffusion constant (D ∝ N –2 ) is predicted, with a crossover N D proportional to the product of the system-specific macromolecular volume fraction and dimensionless compressibility. In analogy with caging effects in glass-forming fluids, the theory does appear to begin to fail at sufficiently high N/N D for the center-of-mass diffusivity, likely due to another crossover to an even slower activated transport regime. However, use of N/N D with the theoretically predicted N D , in conjunction with dynamic blob scaling ideas for local Rouse friction, collapses semidilute and concentrated solution simulation data onto a master curve. Based on the same physical ideas employed to predict the diffusion constant, a generalized Langevin equation description is formulated for intermediate-time CM transport. It predicts two subdiffusive regimes that emerge due to the self-similar nature of internal ring structure. Analytic and numerical predictions for the apparent non-Fickian exponent as a function of time, N/N D and dimensionless compressibility, the evolution of the maximum degree of subdiffusive motion with N/N D , and the time scale for recovering Fickian diffusion are made, all of which are in good accordance with melt simulations. Furthermore, the present work sets the stage to address activated dynamics and glass formation on the macromolecular scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2023

Dynamic mode decomposition for extrapolating nonequilibrium Green's-function dynamics

The Hartree-Fock generalized Kadanoff-Baym ansatz (HF-GKBA) offers an approximate numerical procedure for propagating the two-time nonequilibrium Green's function (NEGF). Here, using the GW self-energy, we compare the HF-GKBA to exact results for a variety of systems with long- and short-range interactions, different two-body interaction strengths, and various nonequilibrium preparations. We find excellent agreement between the HF-GKBA and exact time evolution in models when more realistic long-range exponentially decaying interactions are considered. Furthermore, this agreement persists for long times and for intermediate to strong interaction strengths. In large systems, HF-GKBA becomes prohibitively expensive for long-time evolutions. For this reason, we look at the use of dynamical mode decomposition (DMD) to reconstruct long-time NEGF trajectories from a sample of the initial trajectory. Using no more than 16% of the total time evolution, we reconstruct the total trajectory with high fidelity. Our results show the potential for DMD to be used in conjunction with HF-GKBA to calculate long-time trajectories in large-scale systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A reacting multiphase computational flow model for 2,3-butanediol synthesis in industrial-scale bioreactors

The microbe, Zymomonas mobilis, can efficiently convert sugars to 2,3 butanediol (BDO), an important intermediate for downstream chemical products, only in a well-controlled microaerated environment. However, controlling oxygen distribution in industrial-scale bioreactors is challenging, and at-scale BDO production is hard to optimize using traditional engineering methods. This study takes a step towards addressing this problem through a computational model for reacting multiphase flows in large-scale bioreactors. A phenomenological metabolic model was first developed and validated against experiments, and then it was coupled to a multiphase computational fluid dynamics (CFD) solver using a subcycling algorithm for simulating long conversion times (~30 hours). Large-scale (~500 m 3 ) bubble column simulations using this coupled approach demonstrated a 25% improvement in BDO yield with low sparging rates (0.002 m/s) and low height-to-diameter ratio (0.875) compared to a baseline bubble column (35 m height, 5 m diameter) with a superficial gas velocity of 0.06 m/s.

09 BIOMASS FUELS↗
DOE OSTI2023

Quantifying the Relevance of Long-Range Forces for Crystal Nucleation in Water

Understanding nucleation from aqueous solutions is of fundamental importance in a multitude of fields, ranging from materials science to biophysics. The complex solvent-mediated interactions in aqueous solutions hamper the development of a simple physical picture, elucidating the roles of different interactions in nucleation processes. In this study, we make use of three complementary techniques to disentangle the role played by short- and long-range interactions in solvent-mediated nucleation. Specifically, the first approach we utilize is the local molecular field (LMF) theory to renormalize long-range Coulomb electrostatics. Second, we use well-tempered metadynamics to speed up rare events governed by short-range interactions. Third, the deep learning-based State Predictive Information Bottleneck approach is employed in analyzing the reaction coordinate of the nucleation processes obtained from the LMF treatment coupled with well-tempered metadynamics. We find that the two-step nucleation mechanism can largely be captured by the short-range interactions, while the long-range interactions further contribute to the stability of the primary crystal state under ambient conditions. Furthermore, by analyzing the reaction coordinate obtained from the combined LMF-metadynamics treatment, we discern the fluctuations on different time scales, highlighting the need for long-range interactions when accounting for metastability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Interactive Mesh Generation and Comparison Tools for Nuclear Energy Advanced Modeling & Simulation Phase I. Final Report

The promise of computer simulations for nuclear reactor designs is the opportunity to speed up the design process while also improving safety, providing more detail and higher fidelity, reducing cost, minimizing schedule risk, and avoiding many other potential problems; because simulations have the potential to be much less expensive and time-consuming than traditional development – where scale models and physical tests require construction and long lead times – it is possible to consider more alternatives and complete more comprehensive assessments before the design is finalized and constructed. As more design scenarios are studied by simulation, the speed that simulations promise is only available as long as bottlenecks are addressed for these scenarios. A frequent bottleneck is the amount of human labor required to describe the shape of the objects being designed and decompose the shape into simple elements, such as hexahedra, that are small enough to capture the physical phenomena of interest without being so small that even fast computers cannot perform the simulation in a reasonable amount of time. Recently, techniques for creating all-hexahedral decompositions have been developed, but they require some human input. Many simulation codes prefer all-hexahedral decompositions, so we proposed to evaluate the feasibility of these techniques on nuclear reactor geometries to see whether they required too much human input to be commercially viable. Our study concluded that they can be made viable with some additional software tools to reduce the amount of user input required.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Stability, metallicity, and magnetism in niobium silicide nanofilms

Modern superconducting qubits based on two-dimensional (2D) transmons typically involve the growth of Nb thin films on high-resistivity Si substrates. Since imperfections at the Nb-Si heterointerface have been implicated as a source of two-level systems that limit quantum coherence times, detailed characterization and understanding of niobium silicide interfacial layers are critical to improving superconducting qubit technology. While bulk binary intermetallic niobium silicide phases are well understood, the thermodynamic phase stability and properties of ultrathin niobium silicides, such as those found at the Nb-Si heterointerface in 2D transmons, have not yet been explored. Here, we report finite-sized effects for ultrathin niobium silicide films using density functional theory calculations and predict nanoscale stabilization of Nb 6 Si 5 over the bulk α-Nb 5 Si 3 phase. This result is consistent with our experimental observations of a niobium silicide interfacial layer between a sputtered Nb thin film and the underlying Si substrate. Furthermore, our calculations show that Nb 6 Si 5 nanofilms are nonmagnetic, making them superior to nanofilms of α-Nb 5 Si 3 that exhibit antiferromagnetic correlations detrimental to long coherence times in superconducting qubits. Furthermore, by providing atomic-scale insight into niobium silicide nanofilms, this paper can help guide ongoing efforts to optimize Nb-Si heterointerfaces for long coherence times in superconducting qubits.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗
DOE OSTI2022

THE DESIGN OF LAYER TIME OPTIMIZATION IN LARGE SCALE ADDITIVE MANUFACTURING WITH FIBER REINFORCED POLYMER COMPOSITES

In this study, we have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale additive manufacturing (AM) via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreement with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation.

Jo, Eonyeon↗
DOE OSTI2020

Biomimetic Rebuilding of Multifunctional Red Blood Cells: Modular Design Using Functional Components

The design and synthesis of artificial materials that mimic the structures, mechanical properties, and ultimately functionalities of biological cells remains a current holy grail of materials science. Here based on a silica cell bio-replication approach, we report the design and construction of synthetic rebuilt red blood cells (RRBCs) that fully mimic the broad properties of native RBCs: size, biconcave shape, deformability, oxygen carrying capacity, long circulation time. Four successive nano-scale processing steps: RBC bioreplication, layer-by-layer polymer deposition, and precision silica etching, followed by RBC ghost membrane vesicles fusion are employed for RRBC construction. A panel of physicochemical analyses including zeta potential measurement, fluorescence microscopy, and antibody-mediated agglutination assay proved the recapitulation of RBC shape, size, and membrane structure. Flow-based deformation studies carried out in a microfluidic blood capillary model confirrned the ability of RRBCs to deform and pass through small slits and reconstitute themselves in a manner comparable to native RBCs. Circulation studies of RRBCs conducted ex-ovo in a chick embryo and in vivo in a mouse model demonstrated the requirement of both deformability and native cell membrane surface to achieve long-term circulation. To confer additional non-native functionalities to RRBCs, we developed modular procedures in which to load functional cargos such as hemoglobin, drugs, magnetic nanoparticles, and ATP biosensors within the RRBC interior to enable various functions, including oxygen delivery, therapeutic drug delivery, magnetic manipulation, and toxin biosensing and detection. Taken together, RRBCs represent a class of long circulating RBC-inspired artificial hybrid materials with a broad range of potential applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Transport Upscaling under Flow Heterogeneity and Matrix-Diffusion in Three-Dimensional Discrete Fracture Networks

For this work, we investigate the combined effects of network scale flow variability and retention due to matrix-diffusion on the scaling behavior of transport through fractured media. Two of the principal mechanisms controlling the transport of solutes through fractured low-permeability media are broad distributions of flow velocities and retention times in the solid matrix. We study the relative impact of these two processes under different initial conditions using a set of three-dimensional discrete fracture network simulations. We use these simulations to develop and calibrate an upscaled continuous time random walk (CTRW) approach for advective transport based on an Ornstein-Uhlenbeck model for the particle velocities that accounts for the fracture-matrix coupling using a compound Poisson process. This CTRW model can be conditioned on the initial solute distribution and allows to observe late-time scaling behavior at distances beyond what is feasible to observe using high-fidelity direct numerical simulations. We determine that the initial distribution of particles leads to marked differences in the persistent long-term scale behavior in the solute travel time distributions, even those undergoing retention due to matrix diffusion through implementation and analysis of the model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Nyström type exponential integrators for strongly magnetized charged particle dynamics

Solving for charged particle motion in electromagnetic fields (i.e. the particle pushing problem) is a computationally intensive component of particle-in-cell (PIC) methods for plasma physics simulations. This task is especially challenging when the plasma is strongly magnetized due numerical stiffness arising from the wide range of time scales between highly oscillatory gyromotion and long term macroscopic behavior. A promising approach to solve these problems is by a class of methods known as exponential integrators that can solve linear problems exactly and are A-stable. This work extends the standard exponential integration framework to derive Nyström-type exponential integrators that integrates the Newtonian equations of motion as a second-order differential equation directly. In particular, we derive second-order and third-order Nyström-type exponential integrators for strongly magnetized particle pushing problems. Numerical experiments show that the Nyström-type exponential integrators exhibit significant improvement in computation speed over the standard exponential integrators.

general physics↗
DOE OSTI2021

Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed

Integrated forecasting systems for precipitation, streamflow, and floodplain inundation are of critical importance in mitigating the impacts of destructive floods caused by extreme weather events. However, the skills of streamflow and floodplain inundation forecasts derived from various Quantitative Precipitation Forecasts (QPF) require a greater level of understanding. In this paper, a set of QPF developed by the National Weather Service (NWS) were used to drive a flood modeling system obtained utilizing offline coupling of a physics-based distributed hydrological model, the Distributed Hydrology Soil and Vegetation Model (DHSVM), and a hydrodynamic model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). This flood modeling system was used to produce forecasts of streamflow and floodplain inundation maps during three major flood events in the Brays Bayou Watershed (Houston, Texas, USA) for a range of QPF durations (6–72 h). Then, to investigate the effects of increasing QPF durations on the forecasts, the forecasting skills of precipitation, streamflow, and floodplain inundation were quantified. The results show that: 1) QPF skills for more intense and sustained events such as hurricanes and tropical storms are higher than for shorter, less intense events; 2) while QPF and streamflow forecasting skills decrease as QPF durations increase, inundation forecasts under longer QPF durations (24 or 72 h) show higher skills; 3) extending the maximum QPF duration in operational hydrologic modeling from 24 h (under normal circumstances) to 72 h (for extreme events) may increase the skills of long lead time forecasts for large-scale events like Hurricane Harvey.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Water Innovation and R&D Concept Exploration and Preliminary Assessment: Water Scoping Project Report Deliverable

Pacific Northwest National Laboratory and Idaho National Laboratory produced a cursory review and initial framework to support the US Department of Energy’s Water Power Technologies Office (WPTO) in considering options for program development related to water. The laboratories provided a suite of tools – rationales, evaluation criteria, and visual maps – as well as R&D concepts that could be applied at various scales over short- and long-term time horizons. The effort is, by DOE request, largely the result of the authors’ creative efforts and not intended to be a comprehensive or detailed analytical exercise. This report summarizes the work provided to WPTO and is not intended for broad distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Subseasonal Variability of U.S. Coastal Sea Level from MJO and ENSO Teleconnection Interference

Abstract Climate variability affects sea levels as certain climate modes can accelerate or decelerate the rising sea level trend, but subseasonal variability of coastal sea levels is underexplored. This study is the first to investigate how remote tropical forcing from the MJO and ENSO impact subseasonal U.S. coastal sea level variability. Here, composite analyses using tide gauge data from six coastal regions along the U.S. East and West Coasts reveal influences on sea level anomalies from both the MJO and ENSO. Tropical MJO deep convection forces a signal that results in U.S. coastal sea level anomalies that vary based on MJO phase. Further, ENSO is shown to modulate both the MJO sea level response and background state of the teleconnections. The sea level anomalies can be significantly enhanced or weakened by the MJO-associated anomaly along the East Coast due to constructive or destructive interference with the ENSO-associated anomaly, respectively. The West Coast anomaly is found to be dominated by ENSO. We examine physical mechanisms by which MJO and ENSO teleconnections impact coastal sea levels and find consistent relationships between low-level winds and sea level pressure that are spatially varying drivers of the variability. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts. Significance Statement Coastal flooding due to sea level rise is increasingly threatening communities, but natural fluctuations of coastal sea levels can exacerbate the human-caused sea level rise trend. This study assesses the role of tropical influences on coastal subseasonal (2 weeks–3 months) sea level heights. Further, we explore the mechanisms responsible, particularly for constructive interference of signals contributing to coastal flooding events. Subseasonal signals amplify or suppress the lower-frequency signals, resulting in higher or lower sea level heights than those expected from known climate modes (e.g., ENSO). Low-level onshore winds and reduced sea level pressure connected to the tropical phenomena are shown to be indicators of increased U.S. coastal sea levels, and vice versa. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Short- vs . long-range elastic distortion: structural dynamics of a [2 × 2] tetrairon( II ) spin crossover grid complex observed by time-resolved X-Ray crystallography

Spin crossover complexes (SCO) are among the most studied molecular switches due to their potential use in displays, sensors, actuators and memory components. A prerequisite to using these materials is the understanding of the structural changes following the spin transition at out-of-equilibrium conditions. So far, out-of-equilibrium studies in SCO solids have been focused on mononuclear complexes, though a growing number of oligonuclear SCO complexes showing cooperative effects are being reported. Here, we use time-resolved pink Laue crystallography to study the out-of-equilibrium dynamics of a [2 × 2] tetranuclear metallogrid of the form [Fe II 4 L Me 4 ](BF 4 ) 4 ·2MeCN ([L Me ] - = 4-methyl-3,5-bis{6-(2,2'-bipyridyl)}pyrazolate). The out-of-equilibrium spin state switching induced by a ps laser pulse demonstrates that the metallogrid exhibits a multi-step response similar to that reported for mononuclear complexes. Contrary to the mononuclear complexes, the metallogrid shows two types of elastic distortions at different time scales. The first is a short-range distortion that propagates over the entire Fe 4 grid complex during the ps time scale, and it is caused by the rearrangement of the coordination sphere of the photo-switching ion and the constant feedback between strongly linked metal ions. The second is a long-range distortion caused by the anisotropic expansion of the lattice during the ns time scale, observed in mononuclear materials. The structural analysis demonstrates that the long-range prevails over the short-range distortion, inducing the largest deformation of both the entire grid and the coordination sphere of each metal ion. The present study sheds light on the out-of -equilibrium dynamics of a non-cooperative oligonuclear complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗