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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Novel 3D Cubic Topology in Hybrid Lead Halides with a Symmetric Aromatic Triammonium Exhibiting Water Stability

The limitations of three-dimensional (3D) perovskites are related to their narrow structural tunability of the organic cations and their moisture sensitivity. Herein, we report a new family of 3D cubic hybrid metal halides (T-Et 6 ) 3 Pb 11 X 31 (X = I, Br), where T is 1,3,5-tris-(4-aminophenyl)benzene. The materials are synthesized through an in situ N-alkylation of T and an efficient one-step solvothermal reaction containing ethanol, initiating a tunable synthetic avenue for the acquisition of structurally complex hybrid halides with luminophores. (T-Et 6 ) 3 Pb 11 X 31 consist of an unprecedented Ia3̅ framework of [Pb 11 X 31 ] 9– one-dimensional (1D) chains embedded with (T-Et 6 ) 3+ cations, affording an overall 3D topology. Here, the constituent [Pb 11 X 31 ] 9– chains include exclusively octahedral lead halide units with clusters of face- and edge-sharing connectivity, giving rise to weak broad emission centered at ~660 nm observed at 78 K. (T-Et 6 ) 3 Pb 11 I 31 demonstrates water stability for at least 7 days. Synthesis through ambient pressure results in tunable structural variations of zero-dimensional (0D) structures rendering T 7 Pb 3 Br 27 ·DMF and T 2 Sn 3 Br 18 ·4H 2 O·0.5Br 2 , both of which feature blue PL emission at room temperature.

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

Tetris-inspired detector with neural network for radiation mapping

Abstract Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Molecular-scale Understanding of Selective Oxidative Transformations of Alcohols Promoted by Au and Au-based Alloys

This project developed a molecular-scale mechanistic framework for complex selective oxidation of alcohols and amines on O-covered Au and Ag-Au alloys that guides the design of selective and energy efficient processes. Our work has led to the discovery of new classes of reactions. We have also bridged a wide range of pressures and materials complexity by demonstrating catalytic activity using nanoporous Au catalysts. The selective oxidation of alcohols with each other and with other reactants, such as CO or amines, were focused on in this work because it is a key technology for large-scale chemical synthesis. Theory and experiment were combined to understand selective oxidation reactions on Au. Significant accomplishments are: (i) development of molecular-scale mechanisms for selective alcohol oxidation over Au surfaces; (ii) discovery of two new classes of reactions on O/Au—amide synthesis from amines and aldehydes and carbonylation of alcohols; and, (iii) demonstration that the mechanisms derived from our fundamental work predict the conditions for efficient catalysis using nanoporous Au catalysts under flow conditions at atmospheric pressure. This work has made an unprecedented connection between fundamental surface science studies and their implementation under catalytic conditions. This research fits squarely in the DOE-BES mission articulated in several BES Basic Research Needs (BRN) reports. “Catalysis for Energy” emphasizes the need to fabricate, design, characterize, and assemble new structures, including nanoscale alloys, and to understand and model their chemical behavior for energy-related applications. Our studies of nanoporous materials also exploit unique mesoscale phenomena to address complex energy-related issues (http://www.meso2012.com/).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Rethinking materials simulations: Blending direct numerical simulations with neural operators

Abstract Materials simulations based on direct numerical solvers are accurate but computationally expensive for predicting materials evolution across length- and time-scales, due to the complexity of the underlying evolution equations, the nature of multiscale spatiotemporal interactions, and the need to reach long-time integration. We develop a method that blends direct numerical solvers with neural operators to accelerate such simulations. This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism to enable accurate extrapolation and efficient time-to-solution predictions of the dynamics. We demonstrate the effectiveness of this hybrid framework on simulations of microstructure evolution via the phase-field method. Such simulations exhibit high spatial gradients and the co-evolution of different material phases with simultaneous slow and fast materials dynamics. We establish accurate extrapolation of the coupled solver with large speed-up compared to DNS depending on the hybrid strategy utilized. This methodology is generalizable to a broad range of materials simulations, from solid mechanics to fluid dynamics, geophysics, climate, and more.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Orchestration of materials science workflows for heterogeneous resources at large scale

In the era of big data, materials science workflows need to handle large-scale data distribution, storage, and computation. Any of these areas can become a performance bottleneck. We present a framework for analyzing internal material structures (e.g., cracks) to mitigate these bottlenecks. We demonstrate the effectiveness of our framework for a workflow performing synchrotron X-ray computed tomography reconstruction and segmentation of a silica-based structure. Our framework provides a cloud-based, cutting-edge solution to challenges such as growing intermediate and output data and heavy resource demands during image reconstruction and segmentation. Specifically, our framework efficiently manages data storage, scaling up compute resources on the cloud. The multi-layer software structure of our framework includes three layers. A top layer uses Jupyter notebooks and serves as the user interface. A middle layer uses Ansible for resource deployment and managing the execution environment. A low layer is dedicated to resource management and provides resource management and job scheduling on heterogeneous nodes (i.e., GPU and CPU). At the core of this layer, Kubernetes supports resource management, and Dask enables large-scale job scheduling for heterogeneous resources. The broader impact of our work is four-fold: through our framework, we hide the complexity of the cloud’s software stack to the user who otherwise is required to have expertise in cloud technologies; we manage job scheduling efficiently and in a scalable manner; we enable resource elasticity and workflow orchestration at a large scale; and we facilitate moving the study of nonporous structures, which has wide applications in engineering and scientific fields, to the cloud. While we demonstrate the capability of our framework for a specific materials science application, it can be adapted for other applications and domains because of its modular, multi-layer architecture.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Lab-Scale, Closed-Loop Experimental Characterization, Model Refinement, and Validation of a Hydrokinetic Energy-Harvesting Ocean Kite

This paper presents a study wherein we experimentally characterize the dynamics and control system of a lab-scale ocean kite, and then refine, validate, and extrapolate this model for use in a full-scale system. Ocean kite systems, which harvest tidal and ocean current resources through high-efficiency cross-current motion, enable energy extraction with an order of magnitude less material (and cost) than stationary systems with the same rated power output. However, an ocean kite represents a nascent technology that is characterized by relatively complex dynamics and requires sophisticated control algorithms. In order to characterize the dynamics and control of ocean kite systems rapidly, at a relatively low cost, the authors have developed a lab-scale, closed-loop prototyping environment for characterizing tethered systems, whereby 3D printed systems are tethered and flown in a water channel environment. While this system has been shown to be capable of yielding similar dynamic characteristics to some full-scale systems, there are also fundamental limitations to the geometric scales and flow speeds within the water channel environment, making many other real-world scenarios impossible to replicate from the standpoint of dynamic similarity. Here, to address these scenarios, we show how the lab-scale framework is used to refine and validate a scalable dynamic model of a tethered system, which can then be extrapolated to full-scale operation. In this work, we present an extensive case study of this model refinement, validation, and extrapolation on an ocean kite system intended for operation in the Gulf Stream or similar current environments.

42 ENGINEERING↗
DOE OSTI2015

Nanoscale building blocks in a novel lithium arsenotungsten bronze: Synthesis and characterization

We report on a novel compound Li{sub 3}AsW{sub 7}O{sub 25} obtained by solid-state reaction and characterized by diffraction and spectroscopic methods. The bronze-type compound crystallizes in the orthorhombic space group Pbca with a=724.38(3) pm, b=1008.15(4) pm, c=4906.16(17) pm and Z=8. The structure is built up by chains of WO{sub 6} octahedra interconnected by AsO{sub 4} tetrahedra and WO{sub 6} octahedra forming a polyhedral arrangement as seen in intergrowth tungsten bronzes. The X-ray single crystal structure refinement allows solving the complex arsenotungstate framework. The powder neutron diffraction data analysis locates the lithium atoms. Thermal analysis showed that Li{sub 3}AsW{sub 7}O{sub 25} is stable up to its melting at 1135(3) K followed by a decomposition at 1182(5) K. The Kubelka–Munk treatment of the UV–vis spectrum revealed a wide band gap in the range of 2.84–3.40 eV depending on the presumed electron transition type. - Graphical abstract: Crystal structure of Li{sub 3}AsW{sub 7}O{sub 25} showing different schematic components. - Highlights: • A report on a novel compound Li{sub 3}AsW{sub 7}O{sub 25} obtained by solid-state reaction. • Chains and nano-blocks of WO{sub 6} octahedra and AsO{sub 4} tetrahedra formed a structure like intergrowth tungsten bronzes. • X-ray diffraction allowed solving the complex arsenotungstate framework. • Powder neutron diffraction data analysis locates the lithium atoms. • UV–vis spectrum revealed the band-gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Metal–organic frameworks assembled from lanthanide and 2,5-pyridinedicaboxylate with cubane-like [Ln{sub 4}(OH){sub 4}] building units

Lanthanide–organic frameworks based on 2,5-pyridinedicaboxylate (25p) ligand, formulated as [Yb{sub 4}(OH){sub 4}(25p){sub 4}(H{sub 2}O){sub 3}]·H{sub 2}O (25pYb), [Y{sub 4}(OH){sub 4}(25p){sub 4}(H{sub 2}O){sub 3}]·H{sub 2}O (25pY-1) and [Y{sub 6}(OH){sub 8}(25p){sub 5}(H{sub 2}O){sub 2}] (25pY-2), have been obtained as single phases under hydrothermal conditions. 25pYb and 25pY-1 are isostructural, and crystallize in the triclinic space group, P-1, with a=8.6075(5) Å, b=14.8478(7) Å, c=15.9164(9) Å, α=86.277(4)°, β=80.196(5)°, γ=81.785(4)°, and a=8.7166(6) Å, b=14.966(1) Å, c=15.966(1) Å, α=86.260(6)°, β=80.036(6)°, γ=81.599(6)°, respectively. 25pY-2 crystallizes in the monoclinic space group, P2{sub 1}/c, with a=24.9117(17) Å, b=13.7340(8) Å, c=14.3385(10) Å, β=100.551(7)°. 25pYb and 25pY-2 have been structurally characterized by single-crystal X-ray diffraction. The 25pYb structure is based on tetranuclear cubane-like [Yb{sub 4}(OH){sub 4}]{sup 8+} clusters, which are interconnected to eight neighbouring clusters through teen surrounding 25p ligands leading to neutral 3D framework, while the structure of 25pY-2 is based on two independent cuban-like [Y{sub 4}(OH){sub 4}]{sup 8+} clusters, which are joined together through Y1 cation leading to the formation of hexanuclear [Y{sub 6}(OH){sub 8}]{sup 10+} clusters, which in turn are joined via Y2 cation resulting in infinite inorganic chain extending along c-axis, and each chain is interconnected to six adjacent chains through 25p ligands leading finally to 3D framework. The luminescence properties of Eu{sup 3+} and Tb{sup 3+} doped 25pY-1 and 25pY-2 compounds have also been investigated. All materials has been characterized by powder X-ray diffraction, thermal analyses (TG–SDTA–MS), FTIR spectroscopy, C–H–N elemental analysis, scanning electron microscopy (SEM-EDX), and powder X-ray thermodiffraction. - Graphical abstract: Nowadays, lanthanide–organic frameworks (LOFs) attract tremendous attention due to the unique characteristic of lanthanide cations, such as variable coordination numbers and geometries which often lead to novel complex structures, and also to their magnetic and photoluminescence properties. Herein, three LOFs formulated as [Ln{sub 4}(OH){sub 4}(25p){sub 4}(H{sub 2}O){sub 3}]·H{sub 2}O (Ln=Y, Yb) and [Y{sub 6}(OH){sub 8}(25p){sub 5}(H{sub 2}O){sub 2}] have been obtained by hydrothermal method and characterized, and the photoluminescence properties of the Eu and Tb doped compounds are discussed. - Highlights: • Three novel LnOFs has been synthesized and characterized. • Crystal structures are based on tetranuclear cuban-like [Ln{sub 4}(OH){sub 4}]{sup 8+} clusters. • 25pYb and 25pY-1 are based on isolated [Ln{sub 4}(OH){sub 4}]{sup 8+} clusters. • 25pY-2 is based on infinite inorganic chains built up from [Y{sub 4}(OH){sub 4}]{sup 8+} clusters. • Photoluminescence studies show strong red and green light emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine-learning for designing nanoarchitectured materials by dealloying

Machine learning-augmented materials design is an emerging method for rapidly developing new materials. It is especially useful for designing new nanoarchitectured materials, whose design parameter space is often large and complex. Metal-agent dealloying, a materials design method for fabricating nanoporous or nanocomposite from a wide range of elements, has attracted significant interest. Here, a machine learning approach is introduced to explore metal-agent dealloying, leading to the prediction of 132 plausible ternary dealloying systems. A machine learning-augmented framework is tested, including predicting dealloying systems and characterizing combinatorial thin films via automated and autonomous machine learning-driven synchrotron techniques. This work demonstrates the potential to utilize machine learning-augmented methods for creating nanoarchitectured thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials

Reliable models of the thermodynamic properties of materials are critical for industrially relevant applications that require a good understanding of equilibrium phase diagrams, thermal and chemical transport, and microstructure evolution. The goal of thermodynamic models is to capture data from both experimental and computational studies and then make reliable predictions when extrapolating to new regions of parameter space. These predictions will be impacted by artifacts present in real data sets such as outliers, systematic errors, and unreliable or missing uncertainty bounds. Such issues increase the probability of the thermodynamic model producing erroneous predictions. We present a Bayesian framework for the selection, calibration, and quantification of uncertainty of thermodynamic property models. The modular framework addresses numerous concerns regarding thermodynamic models including thermodynamic consistency, robustness to outliers, and systematic errors by the use of hyperparameter weightings and robust Likelihood and Prior distribution choices. Furthermore, the framework’s inherent transparency (e.g. our choice of probability functions and associated parameters) enables insights into the complex process of thermodynamic assessment. We introduce these concepts through examples where the true property model is known. Additionally, we demonstrate the utility of the framework through the creation of a property model from a large set of experimental specific heat and enthalpy measurements of Hafnium metal from 0 to 4900K.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dioxygen Activation Kinetics over Distinct Cu Site Types in Cu-Chabazite Zeolites

Cu-exchanged zeolites activate dioxygen to form active sites for partial methane oxidation (PMO), nitrogen oxide decomposition, and carbon monoxide oxidation. Apparent rates of O 2 activation depend both on the intrinsic kinetics of distinct Cu site types and the distributions of such sites within a given zeolite, which depend on the density and arrangement of the framework Al atoms. In this work, we use hydrothermal synthesis methods to control the arrangement of framework Al sites in chabazite (CHA) zeolites and, in turn, the distinct Cu site types formed. Time-resolved in situ Raman spectroscopy reveals the kinetics of O 2 adsorption and activation within these well-defined Cu-CHA materials and the concomitant structural evolution of copper–oxygen (Cu x O y ) complexes, which are interpreted alongside Cu(I) oxidation kinetics extracted from in situ X-ray absorption spectroscopy (XAS). Raman spectra of several plausible Cu x O y species simulated using density functional theory suggest that experimental spectra (λ ex = 532 nm) capture the formation of mono(μ-oxo)dicopper species (ZCuOCuZ). Transient experiments show that the timescales required to form Cu x O y structures that no longer change in Raman spectra correspond to the durations of oxidative treatments that maximize CH 3 OH yields in stoichiometric PMO cycles (approximately 2 h). Yet, these periods extend well beyond the timescales for the complete conversion of the initial Cu(I) intermediates to their Cu(II) states (<0.3 h, reflected in X-ray absorption near edge spectroscopy spectra), which demonstrates that Cu x O y complexes continue to evolve structurally following rapid Cu(I) oxidation. The dependence of ZCuOCuZ formation rates on O 2 pressure, H 2 O pressure, and temperature is consistent with a mechanism in which ZCuOH reduces to form ZCu + sites that bind molecular oxygen and form ZCu-O 2 intermediates. Subsequent reaction with proximate ZCu + forms bridging peroxo dicopper complexes that cleave O–O bonds to form ZCuOCuZ in steps facilitated by water. These data and interpretations provide evidence for the chemical processes that link rapid and kinetically irrelevant Cu oxidation steps (frequently probed by XAS and UV–vis spectroscopy) to the relatively slow genesis of reactive Cu complexes that form CH 3 OH during PMO. In doing so, we reveal previously unrecognized complexities in the processes by which Cu ions in zeolites activate O 2 to form active Cu x O y complexes, which underscore the insight afforded by judicious combinations of experimental and theoretical techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

TH-A-19A-12: A GPU-Accelerated and Monte Carlo-Based Intensity Modulated Proton Therapy Optimization System

Purpose: To develop a clinically applicable intensity modulated proton therapy (IMPT) optimization system that utilizes more accurate Monte Carlo (MC) dose calculation, rather than analytical dose calculation. Methods: A very fast in-house graphics processing unit (GPU) based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified gradient based optimization method was used to achieve the desired dose volume histograms (DVH). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve the spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that Result from maintaining the intrinsic CT resolution and large number of proton spots. The dose effects were studied particularly in cases with heterogeneous materials in comparison with the commercial treatment planning system (TPS). Results: For a relatively large and complex three-field bi-lateral head and neck case (i.e. >100K spots with a target volume of ∼1000 cc and multiple surrounding critical structures), the optimization together with the initial MC dose influence map calculation can be done in a clinically viable time frame (i.e. less than 15 minutes) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The DVHs of the MC TPS plan compare favorably with those of a commercial treatment planning system. Conclusion: A GPU accelerated and MC-based IMPT optimization system was developed. The dose calculation and plan optimization can be performed in less than 15 minutes on a hardware system costing less than 45,000 dollars. The fast calculation and optimization makes the system easily expandable to robust and multi-criteria optimization. This work was funded in part by a grant from Varian Medical Systems, Inc.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Microscopic origin of tunable assembly forces in chiral active environments

Across a variety of spatial scales, from nanoscale biological systems to micron-scale colloidal systems, equilibrium self-assembly is entirely dictated by—and therefore limited by—the thermodynamic properties of the constituent materials. In contrast, nonequilibrium materials, such as self-propelled active matter, expand the possibilities for driving the assemblies that are inaccessible in equilibrium conditions. Recently, a number of works have suggested that active matter drives or accelerates self-organization, but the emergent interactions that arise between solutes immersed in actively driven environments are complex and poorly understood. Here, we analyze and resolve two crucial questions concerning actively driven self-assembly: (i) how, mechanistically, do active environments drive self-assembly of passive solutes? (ii) Under which conditions is this assembly robust? We employ the framework of odd hydrodynamics to theoretically explain numerical and experimental observations that chiral active matter, i.e., particles driven with a directional torque, produces robust and long-ranged assembly forces. Overall, these developments constitute an important step towards a comprehensive theoretical framework for controlling self-assembly in nonequilibrium environments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Critical role of magnetic moments in heavy-fermion materials: Revisiting mysteries of SmB 6

Heavy-fermion family exhibits fascinating and often puzzling properties due to the presence of open-shell f ions and the complexity of the associated charge, orbital, and spin degrees of freedom. SmB 6 is a prototypical heavy-fermion compound that is electrically insulating but yet it displays quantum oscillations, which are a telltale signature of the metallic state. Adding to the enigma is the possibility that SmB 6 is a topological Kondo insulator. Here, by treating the spin degree of freedom on an equal footing with other degrees of freedom using the parameter-free strongly-constrained and appropriately-normed (SCAN) density functional, we explore the ground-state electronic structure of SmB6. A number of competing magnetic phases lying very closely in energy are found, indicating the key role of spin fluctuations in the material. The computed band structure, crystal-field splittings in the f-electron complex, the heavy effective electron mass at the Fermi energy, and the large specific heat are all in good agreement with the corresponding experimental results. In particular, our predicted FS explains the experimentally observed bulk quantum oscillations as well as the low electrical conductivity of SmB 6 . The topological Kondo state of SmB6 is shown to be robust regardless of its magnetic configuration. The excellent performance of SCAN in heavy-fermion systems is explained in terms of its ability to treat self-interaction errors and symmetry breaking within the framework of the density functional theory. Our study provides a new approach for modeling heavy-fermion materials

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Variational Asymptotic Homogenization of Finitely Deformed Viscoelastic-Viscoplastic Composites

The objective of this paper is to develop a constitutive model for finitely deformed viscoelastic-viscoplastic materials and a micromechanics approach to homogenizing composites consisting of such materials. The development of the constitutive model involves establishing a thermodynamic framework based on finite strain theory, developing a viscoelasticity and a viscoplasticity model based on the thermodynamic framework, developing a radial return algorithm based on a classic framework, and deriving a closed-from incremental constitutive relation in the spatial configuration. The development of the micromechanics approach involves pulling-back the above constitutive relation to the material configuration, formulating a variational statement with the resulting constitutive relation, discretizing variational statement in a finite-dimensional space, and solving the discretized variational statement using an Euler–Newton predictor–corrector method. The constitutive model is calibrated via monotonic uniaxial compression tests on a polymer, and the calibrated model is validated by comparing its predictions with the cyclic test data. It is shown capable of characterizing viscoelasticity, viscoplasticity, and complex loading paths. The micromechanics approach’s capabilities are demonstrated through homogenizing a unidirectional fiber-reinforced composite, subjected to uniaxial, biaxial, and shear loading, at different strain rates. It is demonstrated to be capable of handling rate dependence and complex loading paths. The present framework can be further improved by implementing more sophisticated viscoelasticity and viscoplasticity models in future work.

Finite element analysis↗
DOE OSTI2015

Degradation science: Mesoscopic evolution and temporal analytics of photovoltaic energy materials

Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance of material ensembles. Mesoscopic evolution modeling is shown to encompass the heterogeneity of these materials and systems, and enables the discrimination of the fast dynamics of their functional use and the slow and/or rare events of their degradation. As a result, we delineate paths forward for degradation science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Nonlinear dynamics and instability of aqueous dissolution of silicate glasses and minerals

Aqueous dissolution of silicate glasses and minerals plays a critical role in global biogeochemical cycles and climate evolution. The reactivity of these materials is also important to numerous engineering applications including nuclear waste disposal. The dissolution process has long been considered to be controlled by a leached surface layer in which cations in the silicate framework are gradually leached out and replaced by protons from the solution. This view has recently been challenged by observations of extremely sharp corrosion fronts and oscillatory zonings in altered rims of the materials, suggesting that corrosion of these materials may proceed directly through congruent dissolution followed by secondary mineral precipitation. Here we show that complex silicate material dissolution behaviors can emerge from a simple positive feedback between dissolution-induced cation release and cation-enhanced dissolution kinetics. This self-accelerating mechanism enables a systematic prediction of the occurrence of sharp dissolution fronts (vs. leached surface layers), oscillatory dissolution behaviors and multiple stages of glass dissolution (in particular the alteration resumption at a late stage of a corrosion process). In conclusion, our work provides a new perspective for predicting long-term silicate weathering rates in actual geochemical systems and developing durable silicate materials for various engineering applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗