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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

IDAES-PSE 2.8.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.

AS↗
DOE OSTI2019

Implementation and Verification of Isolated Defects for GTS Lifecycle Analyses

Often, the presence of cracks in manufactured components are detrimental to their overall performance. We develop a workflow and tools in this report using CUBIT and Sierra/SM for generating and modeling crack defects to better understand their impact on such components. To this end, we provide a CUBIT library of various prototypical crack defects embedded in pipes and plates that can be readily used in a wide range of simulations, with specific application to those used in Gas Transfer Systems (GTS). We verify the accuracy of the J-integral post-processing capability in Sierra against solutions available in existing literature for the cracks and geometries of interest within the context of linear elastic fracture mechanics, and describe ongoing efforts to quantify and assess numerical errors. Through this process, we outline overall suggestions and recommendations to the user based on the proposed workflow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Verification of MOOSE/Bison's Heat Conduction Solver Using Combined Spatiotemporal Convergence Analysis

Bison is a computational physics code that uses the finite element method to model the thermo-mechanical response of nuclear fuel. Since Bison is used to inform high-consequence decisions, it is important that its computational results are reliable and predictive. One important step in assessing the reliability and predictive capabilities of a simulation tool is the verification process, which quantifies numerical errors in a discrete solution relative to the exact solution of the mathematical model. One step in the verification process—called code verification—ensures that the implemented numerical algorithm is a faithful representation of the underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. In this paper, the code verification process is applied to spatiotemporal heat conduction problems in Bison. Simultaneous refinement of the discretization in space and time is employed to reveal any potential mistakes in the numerical algorithms for the interactions between the spatial and temporal components of the solution. For each verification problem, the correct spatial and temporal order of accuracy is demonstrated for both first- and second-order accurate finite elements and a variety of time-integration schemes. Furthermore, these results provide strong evidence that the Bison numerical algorithm for solving spatiotemporal problems reliably represents the underlying mathematical model in MOOSE. The selected test problems can also be used in other simulation tools that numerically solve for conduction or diffusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Real-Time Automated pH Control within Batch Processes Relying on Raman pH Measurement

Nuclear fission is an energy source that can provide consistent power with very low associated carbon emissions. However, management of the used nuclear fuel is an important aspect of the application of nuclear power. Recycling of useful components from used fuel is an attractive option, but this involves chemical processing of the fuel. Possible chemical separation technologies that might be used in this regard are sensitive to solution pH. Raman spectroscopy is a promising technique for monitoring the pH of solutions in real time. Classical pH probes are too fragile to be used in the harsh environments encountered in nuclear fuel processing. Raman probes are robust and can withstand these harsh environments to track pH. Coupled with chemometric analysis, the demonstration of the use of Raman spectroscopy to track and predict the pH in carboxylate-buffered systems is made possible. Utilizing this spectroscopy in conjunction with Programmable Logic Controllers mimics industrial control systems used in many modern industrial settings. This showcases a pragmatic approach toward leveraging Raman spectroscopy and chemometric model outputs as inputs for a real-time control system. The model to predict pH created by chemometrics proved to be successful in tracking pH. The optimal pH for TALSPEAK extraction of lanthanides and actinides from aqueous solution is known to proceed in a narrow pH range of around pH = 2.8 ± 0.1. This study uses Raman optical monitoring and automated control to return and maintain solution pH within this range after acid or base perturbations move the solution pH well outside this region. Root-mean-square errors show that pH changes measured using Raman spectroscopy on the batch process solution are reliably measured and used to automatically correct and maintain solution pH. Measurement of solution pH tracks favorably with electrochemical pH probe comparison measurements. As a result, the ability to showcase Raman spectroscopy paired with chemometrics analysis acts as a durable, better alternative data source compared to traditional pH probes to optimize the separation efficiency in the used nuclear fuel processing.

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

Selective recovery of critical materials in zero-liquid discharge supercritical water desalination

Zero-liquid discharge desalination techniques are being actively studied as alternative means to produce drinkable water and recover valuable resources without polluting the environment. Supercritical water desalination is one of such alternatives that can overcome the technical and environmental challenges in standard desalination techniques. In addition to these attractive features, this work explores the possibility of utilizing supercritical water desalination for the selective recovery of strategic (critical) materials as co-products. Here, to validate the technical and economic feasibility of the process, we prepared model brine solutions that consist of sodium, neodymium, and different anions and conducted a series of desalination experiments. The results were analyzed experimentally and theoretically and were utilized to evaluate the economic feasibility of the process. When a few tens or hundreds of parts-per-million critical materials are dissolved in the feed, the proposed method becomes more cost-effective in producing critical materials than existing technologies. In addition, it does not discharge any concentrated contaminants while producing drinkable water. These results suggest that supercritical water desalination can recover critical materials while producing freshwater in an economically feasible fashion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Biphasic production of 2,4,6-triamino-1,3,5-trinitrobenzene (TATB)

Production of 2,4,6-triamino-1,3,5-trinitrobenzene (TATB) through a safer, less harmful process while yielding a superior product is disclosed. The biphasic production process may include mixing a solution of 1,3,5-trichloro-2,4,6-trinitrobenzene (TCTNB) and a surfactant into a solvent in a sealed, heated vessel such that TATB is formed in a mixture. The biphasic production process may also include pressurizing the vessel with gaseous ammonia such that aqueous TATB is formed and separating the TATB from the mixture.

Leonard, Philip↗
DOE OSTI2018

Ionic Liquids as Additives to Polystyrene- Block -Poly(Methyl Methacrylate) Enabling Directed Self-Assembly of Patterns with Sub-10 nm Features

Polystyrene- block -poly(methyl methacrylate) (PS- b -PMMA) is one of the prototypical block copolymers in directed self-assembly (DSA) research and development, with standardized protocols in place for processing on industrially relevant 300 mm wafers. Scaling of DSA patterns to pitches below 20 nm using PS- b -PMMA, however, is hindered by the relatively low Flory–Huggins interaction parameter, $χ$. In this work, we investigate the approach of adding small amounts of ionic liquids (ILs) into PS- b -PMMA, which selectively segregates into the PMMA domain and effectively increases the $χ$ parameter and thus the pattern resolution. The amount of IL additive is small enough to result in limited changes in PS- b -PMMA’s surface and interfacial properties, thus maintaining industry-friendly processing by thermal annealing with a free surface. Three different ILs are studied comparatively regarding their compositional process window, capability of increasing $χ$, and thermal stability. By adding ~3.1 vol % of the champion IL into a low-molecular-weight PS- b -PMMA ( M n = 10.3k- b -9.5k), we demonstrated DSA on chemically patterned substrates of lamellar structures with feature sizes <8.5 nm. Compatibility of the PS- b -PMMMA/IL blends with the standardized processes that have been previously developed suggests that such blend materials could provide a drop-in solution for sub-10 nm lithography with the processing advantages of PS- b -PMMA.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Cavitation energies can outperform dispersion interactions

Amongst all intermolecular interactions that bring molecules, biomolecules, and even molecular fragments together, dispersion interactions are the omnipresent ones. Nevertheless, their contribution to solution-phase phenomena has recently become a matter of debate. In aqueous solution, in particular, they compete with the hydrophobic effect, which also drives associative processes, and when macrocyclic cavities are involved, the release of high-energy water has been identified as an extra driving force. We have now studied the binding of noble gases (He, Ne, Ar, Kr, Xe) with the macrocyclic receptor cucurbit[5]uril (CB5) in aqueous solution through a displacement strategy by using methane and ethane as 1H NMR probes. We dissected the hydration free energies of the noble gases into an attractive dispersive contribution and a repulsive one for cavity formation. This allowed us to fine-grain the components that contribute to host-guest binding and we reach the conclusion that the binding process in solution is driven by differential cavitation energies rather than dispersion interactions. This means that the free energy required to create a cavity to accept the noble gas inside CB5 is much lower (actually zero, since the cavity of the host is non-solvated) than that to create a similarly sized cavity in bulk water, and it is the recovery of the latter cavitation energy, which drives the overall process. The concept of differential cavitation energies merges seamlessly two previous approaches for predicting supramolecular thermodynamics, namely that of cohesive energy density (which applies to bulk solvent) and that of high-energy water (which becomes important for discrete concave binding sites). The dominance of differential cavitation energies in driving guest binding to poorly hydrated, concave binding sites (V < 100 Å3) has implications for the refinement of gas-storage materials and the understanding of biological receptors.

He, Suhang↗
DOE OSTI2019

Panel Session 76: US DOE Problematic Waste Streams and Policy Impacts

This panel provided an overview of DOE problematic waste streams including status and path forward. Potential policy implications that exist now and/or in the future were discussed. Topics included, greater-than-Class C low level waste, depleted uranium, and sodium waste. The panel also discussed potential treatment options for these wastes. As part of the introduction, Renee Echols welcomed the audience and went over a quick overview of what would be discussed on the panel. Theresa Kliczewski provided an overview of why this panel is relevant to US Department of Energy's Office of Environmental Management: there are problematic waste streams that still exist across the DOE cleanup complex. Theresa noted that the DOE EM Headquarters Office of Waste and Materials Management (EM-4.2), for which she is employed with, continues to work with the DOE cleanup sites on a path forward for these problematic waste streams. Presentations proposed include: 1 - Overview of Greater-Than-Class C Low-Level Radioactive Waste Disposal Path Forward (Theresa Kliczewski, US DOE EM (USA)); 2 - Status of Draft Supplemental Environmental Impact Statement for Disposition of Depleted Uranium Oxide Conversion Product Generated from DoE's Inventory of Depleted Uranium Hexafluoride (Jaffet Ferrer-Torres, US DOE (USA)); 3 - Problematic Waste Streams on the Oak Ridge Reservation (John Wrapp, UCOR (USA)); 4 - K Basin Sludge Removal (Ryan Covert, CH2M Hill PRC (USA)); 5 - Providing Technology Solutions for Treatment of Challenging Waste Streams (Tammy Monday, Perma-Fix Environmental Services (USA)); 6 - Treatment of Problematic Reactive Metal Waste Using the GeoMelt{sup R} In-Container Vitrification (ICV{sup TM}) Process (Ron Mitchell, Veolia Nuclear Solutions (USA))

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

IDAES-PSE 2.2.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. New features in the 2.2 release include: DiagnosticsToolbox DiagnosticsToolbox (idaes.core.util.model_diagnostics. DiagnosticsToolbox is a new self-guiding toolbox for assisting with diagnosing modeling issues. The toolbox contains a wide range of tools for identifying common modeling issues and conveying these to the user, and more features will be added in the coming months. To try the new toolbox, use the following steps: from idaes.core.util import DiagnosticsToolbox Build an instance of your model Ensure your models has zero degrees of freedom (as best you can) dt = DiagnosticsToolbox(model) dt.report_structural_issues() Follow the prompts Deprecations DegeneracyHunter is being deprecated in favor of the new DiagnosticsToolbox. The features and capabilities of DegeneracyHunter will be moved over to the DiagnositcsToolbox in the coming months. Removal of usage of Pyomo's expr.current due to deprecation upstream. Removed support for radial basis functions in ALAMOpy as these did not work in the current implementation. Those wishing to use radial basis functions should use Pysmo instead. New Capabilities MSContactor model for unit operations involving mass transfer between 2 or more streams, such as membrane, solvent extraction and solids leaching operations. Other Improvements Improved formulation for solubility products with additional parameters for better scaling of terms Better backward compatibility, verification and robustness testing of core models and APIs Added support for Separator models without energy balances

DiagnosticsToolbox↗
DOE OSTI2023

IDAES-PSE 2.1.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.1.0 Release Highlights New IDAES Examples Repository Starting with this release, the IDAES examples are developed in the new IDAES/examples repository. Along with many content and usability improvements, the most significant changes are: To install the examples, after installing IDAES, run pip install idaes-examples The idaes get-examples command, previously used for this, has been removed The HTML version is now available at https://idaes-examples.readthedocs.io The previous URL, https://idaes.github.io/examples-pse, will not be updated and may be removed at some point in the future For more details, refer to the resources available at IDAES/examples. Removal of Non-Functional Apps A review of the code in the idaes/apps and idaes/models_extra folders was undertaken, and a number of tools were identified as being outdated or non-functional and no longer supported by their development teams. Due to this, the following tools have been removed: idaes/apps/alamopy_depr (note that the new ALAMOpy interface remains avaialble in idaes/core/surrogates) idaes/apps/helmet idaes/apps/ripe idaes/apps/roundingRegression idaes/models_extra/carbon_capture Pyomo 6.6 This version of IDAES is the first requiring Pyomo 6.6. This version of Pyomo contains multiple internal improvements and refactorings. While for the majority of cases this should have positive or no impact on solvability of IDAES models, we are aware of a small number of models that have been affected as a result of these changes. For more information, refer to the Pyomo 6.6.1 release notes. Other highlights Model Initialization A prototype API for a new approach to initializing IDAES models is now available which makes available some new techniques for initializing models. This is documented in the Initializing Models Reference Guide Modular Properties Framework Support for some transport properties Helmholtz Equation of State properties Better error checking for case where unit models are set to include phase equilibrium but the property package is set to support only a single phase Multi-Stream Contactor model: a new base model for systems involving contacting of two or more streams with mass transfer. This model is intended to be used as the foundation for models such as membrane separators, solvent extraction and other similar processes. This is documented in the Multi-Stream Contactor Reference Guide idaes/models_extra/power_generation report() methods for unit models using Helmholtz equation of state General Code Maintenance Streamlining of dependencies and creation of new optional dependency groupings to support non-core tools General linting of codebase to ensure compliance with most pylint checks Spell checking of all code and doc strings Removal of backward compatibility code for Python 2

IDAES↗
DOE OSTI2023

IDAES-PSE 2.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.0.0 Release Highlights Removal of deprecated features from IDAES v1 Update to Pyomo v6.5 – this required a number of updates to support the new NL solver writer and to address some changes in Pyomo Creation of new testing suite for backward compatibility, model robustness and verification More general implementation of the Helmholtz EoS. This brings some new features like standard property diagrams, choice of mass or mole basis, and new state variable options Standardizing names in Heat Exchanger models (breaking change from v2.0.0a2): Control Volumes named hot_side and cold_side Ports names hot_side_inlet, hot_side_outlet, cold_side_inlet and cold_side_outlet Config Blocks names hot_side_config and cold_side_config Config arguments for user provided names for each side: hot_side_name and cold_side_name. Updating Keras surrogate tool to use v1.1 of OMLT New prototype API for model initialization (idaes.core.initialization) The new API uses "Model Initializer" objects instead of class methods, allowing for the definition of multiple initialization routines for a single model A number of common, model agnostic initialization routines have also been defined, including initialization from data, block-decomposition and a general hierarchical approach equivalent to the existing method for common unit models New metadata for thermophysical properties – valid_range This can be used to record the range of values over which a property value can be trusted, such as the range of experimental data used to regress parameters A number of new utility functions have been added to check for properties with values outside the valid range and to set bounds based on this metadata Updated construction of balance expressions in Control Volumes to remove unneeded terms In the past, unneeded terms were added as a constant 0 term, however they will now be dropped entirely from the expression This was necessary due to more strict unit checking in the new Pyomo solver writer which no longer ignores 0 terms Updates to metadata for thermophysical properties to better define known properties and units of measurement This results in more strict enforcement of standard naming for thermophysical and reaction properties Users can still define custom properties, but these must be done explicitly using the define_custom_properties() method instead of being implicitly created by add_property() Updated convergence tester utility tool to support definition of benchmark files (JSON format) and comparison of performance to benchmarks Set default iteration limit for IPOPT in IDAES config to 200 iterations Update scaling of example models to work with new Pyomo NL solver writer Improve testing of extensions and examples infrastructure to avoid need for downloading files Updated distillation column to centralize common functionality and remove a number of Pyomo warnings

IDAES↗
DOE OSTI2022

IDAES-PSE 1.13.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.

IDAES↗
DOE OSTI2023

IDAES-PSE 2.3.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. New Features and Models • New diagnostics toolboxes and examples o Tutorial for using the DiagnosticsToolbox o Methods to identify potential evaluation errors in models o SVDToolbox for performing singular value decomposition analysis on models to identify possible degeneracies and poor scaling o DegeneracyHunter for identifying irreducible degenerate sets in models • Model for solid-liquid separation which takes two inputs (solid and liquid streams) and produces three outlets (solids, liquid entrained with solids and pure liquid) • Example of temperature swing adsorption in models_extra Deprecation Warnings • With the update to Pyomo 6.7.0, the plate heat exchanger model has begun failing tests on some CI platforms. If this is not addressed by the February release, this model may be removed due to failing tests. See #1294. Offers to help identify the cause and fix this issue are welcome. Improvements and bug fixes • Fixed oversight which precluded using Mixer and Separator models when inherent reactions were present in property package • Added reporting methods to the MSContactor model • Minor corrections in some examples where values were being fixed outside of declared variable bounds

DiagnosticsToolbox,IDAES,PSE,Process Systems Engin↗
DOE OSTI2024

IDAES-PSE 2.4.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. Deprecations • Convergence Analysis tool (idaes/core/util/convergence): deprecated in favor of new Parameter Sweep tools. To be removed in v3.0.0. New Beta Capabilities • Parameter Sweep Tool (idaes.core.util.parameter_sweep) o A new API for defining and performing parameter sweep studies on IDAES models has been developed • Diagnostics Tools (idaes.core.util.model_diagnostics) o New methods for identifying duplicate variables and constraints have been added to the diagnostics toolbox o New tools for detecting ill conditioning in Jacobians have been developed and are available in the model_diagnostics module. These provide alternatives to the existing DegeneracyHunter toolbox, and will eventually be merged with this capability, but initial working versions have been provided as beta capabilities for interested users o IpoptConvergenceAnalysis (replaces deprecated Convergence Analysis tool):  A new tool for performing convergence analysis studies that leverages the new Parameter Sweep tools has been developed. This tool allows users to define the input parameters to their model and sampling methods for these (leveraging Pysmo's sampling tools) and to then solve their model across the sampled domains and return a summary of the solver performance (IPOPT only) Improved Models • Thickener model (idaes.models.unit_models.solid_liquid.thickener) o Improved model to include predictive correlations for unit sizing based on settling velocity measurements (steady-state only) • Modular Property Packages o Added general support for calculating critical properties of mixtures using defined Equation of State modules. New API defined for Equation of State modules in order to define the necessary constraints for calculating critical properties (most EoS modules DO NOT support calculation of critical properties (yet)) o Added new methods to Cubic Equation of State module to support calculation of critical properties

DiagnosticsToolbox↗
DOE OSTI2024

IDAES-PSE 2.5.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.5.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

AS↗
DOE OSTI2018

Silver Nanocube and Nanobar Growth via Anisotropic Monomer Addition and Particle Attachment Processes

Understanding the growth mechanism of noble metal nanocrystals during solution synthesis is of significant importance for shape and property control. However, much remains unknown about the growth pathways of metal nanoparticles due to lack of direct observation. Using an in-situ transmission electron microscopy technique, we directly observed Ag nanocube and nanobar growth in aqueous solution through both classical monomer-by-monomer addition and non-classical particle attachment processes. During the particle attachment process, Ag nanocubes and nanobars formed via both oriented and non-oriented attachment. Our calculations, along with dynamics of the observed attachment, showed that van der Waals force overcame hydrodynamic and friction forces and drove the particles toward each other. During classical growth, an anisotropic growth was also revealed, and the resulting unsymmetrical shape constituted an intermediate state for Ag nanocube growth. We hypothesized that the temporary symmetry breaking resulted from different growth rates on {001} surfaces due to a local surface concentration variation caused by the imbalance between the consumption of Ag+ near the surface and the diffusion of Ag+ from bulk to surface.

Xiao, Dongdong↗