pyRoCS: A Python package to evaluate the resilience of complex systems
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97 MATHEMATICS AND COMPUTING↗
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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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py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis
Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Modeling Flow and Mass Transfer within Hollow Fiber Packaging for Gas Separation
Hollow fiber membrane modules are used for gas purification by their selective permeation properties. Intensification of the process to minimize the retentate loss and gas pressure involves optimization at various scales. In this work, we outline a numerical investigation of the gas separation performance at the scale of fiber bundles and its impact on module performance. Flow channeling and anisotropy govern the mass-transfer coefficient in axial and cross-flow configurations. These effects are quantified in terms of a permeability tensor or an anisotropy ratio and the effective mass-transfer coefficient or the Sherwood number. The results show a trade-off between purification and recovery. While smaller fibers offer a large specific surface area to enable high purification, it comes at a huge penalty on the separation performance due to reduced penetration within bundles. Optimum performance indicators are emphasized.
Fibers↗
PSCF+: An Extended and Improved Open-Source Software Package for Polymer Self-Consistent Field Calculations
This work introduces PSCF+, a freely available open‑source software tool for modeling how block copolymers self‑assemble into ordered nanoscale structures. The software allows researchers to study a wide range of polymer models and interaction types, making it possible to directly compare theoretical predictions with molecular and simulation‑based studies in a consistent way. PSCF+ incorporates several recently developed numerical methods that significantly reduce computer memory requirements and speed up calculations, enabling efficient use of modern GPU hardware. Here, it also provides automated tools to calculate free‑energy landscapes and phase boundaries, which are essential for understanding and predicting material behavior. Together, these advances make PSCF+ a powerful and flexible platform for studying polymer self‑assembly and support the design of new polymeric materials for scientific and technological applications.
Chemical calculations↗
COLUMBUS─An Efficient and General Program Package for Ground and Excited State Computations Including Spin–Orbit Couplings and Dynamics
The COLUMBUS program system provides the tools for performing high-level multireference (MR) computations, including the multireference configuration interaction (MRCI) method and its multireference averaged quadratic coupled cluster (MR-AQCC) extension, allowing computations on a wide range of fascinating atomic and molecular systems, including the treatment of open-shells and complicated excited state phenomena. The inclusion of spin−orbit coupling (SOC) directly within the MRCI step enables the description of systems containing heavy elements, such as lanthanides and actinides, whose properties are strongly influenced by SOC. Analytic energy gradients and nonadiabatic couplings at the correlated MRCI level provide the foundation for a variety of dynamics studies, giving insight into ultrafast photochemistry. New and ongoing method developments in COLUMBUS include the computation of spin densities, improved descriptions of ionic states, enhancements to the AQCC method, and the porting of COLUMBUS to graphical processing units (GPUs). New external interfaces enable an enhanced description of electronic resonances and molecules in strong laser fields. This work highlights these new developments while providing a detailed account of the diverse applications of COLUMBUS in recent years.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The CP-PAW Code Package for First-Principles Calculations from a User’s Perspective
CP-PAW is a combined electronic structure and ab initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as solids, liquids, and molecular systems. As the name suggests, the CP-PAW code unifies the all-electron projector augmented-wave (PAW) method with the Car–Parrinello (CP) approach to determine not only the electronic and nuclear ground states of condensed matter but also to study their properties and dynamics. In addition to briefly outlining the underlying theory, the focus will be on the unique aspects of CP-PAW and how to correctly employ them as a user. How to install CP-PAW using the new build system will also be briefly mentioned.
Blöchl, Peter E [Institute for Theoretical Physic↗
Enzyme- and Relative Humidity-Responsive Antimicrobial Fibers for Active Food Packaging
Not provided.
Materials Science↗
Counterintuitive Compatibilization of Poly(-Valerolactone) and Poly(L-Lactic Acid) by Statistical Copolymers toward Compostable and Recyclable Packaging
Poly(δ-valerolactone) (PVL) and poly(l-lactic acid) (PLLA) are bioderivable, compostable, and chemically recyclable plastics with synergistic properties for addressing plastic waste accumulation in receiving environments. Though recyclable-by-design polymers often fall short of competing with incumbent materials, blending affords a means to leverage individual component strengths toward ideal tunable properties. Polymer blends are often immiscible, but a range of methodologies are available to promote mixing. Here, we report on the compatibilization of 9 immiscible PVL and PLLA blends with three different compatibilization agents: thermoplastic starch, synthesized PVL-co-PLLA statistical copolymers (SCPs), and synthesized PVL-b-PLLA block-type copolymers. Resulting degrees of compatibilization are observed through scanning electron microscopy, corroborated by thermal and mechanical analyses monitoring performance as a function of microdomain size. Small-angle and wide-angle X-ray scattering experiments are conducted to observe the influence of compatibilizers on individual crystalline phases to further elucidate material behavior. Molecular dynamics simulations provide key insights into the interfacial interactions between homopolymers and compatibilizers. Finally, a suite of end-of-life avenues is established by biodegradation in industrial composting conditions, chemical recycling by deconstruction to hydroxymethyl esters, and direct chemical depolymerization to lactone precursors in mixed feed. Overall, we highlight several promising blends and the counterintuitive SCP compatibilization phenomenon toward high-performance, sustainable materials.
Compatibilization, copolymer compatibilizer, bio-b↗
Assessing Clouds in GFDL's AM4.0 With Different Microphysical Parameterizations Using the Satellite Simulator Package COSP
We evaluate cloud simulations using satellite simulators against multiple observational data sets. These simulators have been run within the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0), as well as an alternative configuration where a fully two‐moment Morrison‐Gettelman cloud microphysical parameterization with prognostic precipitation (MG2) is applied, denoted as AM4‐MG2. The modeled cloud spatial distributions, vertical profiles, phase partitioning, cloud‐to‐precipitation transitions, and radiative effects compare reasonably well with satellite observations. Model biases include the under‐prediction of total and low‐level clouds, especially optically thin/intermediate clouds with cloud optical depth of less than 23, but the over‐prediction of thick clouds, indicating “too few, too bright” biases. These biases counteract each other, and give rise to reasonable estimates of cloud radiative effects. The underestimate of low‐level clouds is associated with too early and too frequent drizzle/precipitation formation. The precipitation bias is improved in AM4‐MG2, where the autoconversion scheme initiates the precipitation more realistically. There also exist discrepancies between models and observations for midlevel and high‐level clouds. Additional biases include the underestimate of liquid cloud fraction and the overestimate of ice cloud fraction.
54 ENVIRONMENTAL SCIENCES↗
Biomimetic layered, ecological, advanced, multi-functional film for sustainable packaging
Not provided.
Science & Technology - Other Topics↗
MISPR : an open-source package for high-throughput multiscale molecular simulations
Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.
36 MATERIALS SCIENCE↗
Emerging Packaging Concepts and Technologies
Explore the source record for details and available documents.
Gurpinar, Emre↗
Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs
High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as p2r, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these miniapps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Coupled-cluster techniques for computational chemistry: The CFOUR program package
An up-to-date overview of the CFOUR program system is given. After providing a brief outline of the evolution of the program since its inception in 1989, a comprehensive presentation is given of its well-known capabilities for high-level coupled-cluster theory and its application to molecular properties. Subsequent to this generally well-known background information, much of the remaining content focuses on lesser-known capabilities of CFOUR, most of which have become available to the public only recently or will become available in the near future. Each of these new features is illustrated by a representative example, with additional discussion targeted to educating users as to classes of applications that are now enabled by these capabilities. Lastly, some speculation about future directions is given, and the mode of distribution and support for CFOUR are outlined in the appendix.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Recent developments in the PySCF program package
PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. Here, we explain the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Erratum: “DFTB+, a software package for efficient approximate density functional theory based atomistic simulations” [J. Chem. Phys. 152, 124101 (2020)]
The implementation of the GPU support in DFTB+, as described in Sec. III C of the original publication,1 was developed based on a previous unpublished implementation by Jacek Jakowski. In order to acknowledge his work on this first implementation, the authors of the original publication wish to include J. Jakowski as co-author. The scientific content of the original publication is not affected.
42 ENGINEERING↗