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DOE OSTI2024

Gas Stopper Developments for Improved Purity and Intensity of Low-Energy, Rare Isotope Ion Beams (Final Technical Report)

This final technical report summarizes the work of the Michigan State University (MSU) team supported by grant # DE-SC0021423 awarded by the Office of Nuclear Physics, Department of Energy. Objectives: The successful fulfillment of the FRIB science mission hinges on ensuring the availability of fast, stopped, and reaccelerated beams consisting of rare isotopes. This project's research and development focus was dedicated to supporting the advancement and creation of a cutting-edge linear gas stopper. The primary aim is to efficiently convert the high-intensity fast beams of rare isotopes provided by FRIB into high-quality, low-energy beams. These beams are essential for conducting stopped beam experiments or for subsequent reacceleration. The overarching goal is to advance technology, aiming to increase the beam rate capability of the linear gas stopper for medium-to-heavy-mass rare isotopes by more than tenfold compared to the currently most effective gas stopper in operation, and to improve the purity of the delivered beams. Project Description: The existing technology employed in gas stopping devices designed for low-energy, rare-isotope beams presents limitations in both the purity of extracted beams and the intensities of injected beams. These limitations are incompatible with the requirements of the recently commissioned rare isotope beam facility, FRIB. Our research and development efforts, aligned with the previously outlined objectives, focused on addressing the most critical aspects for enhancing beam-rate capability and purity. Specifically, advanced particle-in-cell simulations were developed and integrated into a simulation pipeline to explore the efficacy of multi-layer RF carpets on increasing ion transport efficiency with high incoming beam rates that generate space charge fields which can limit it. We also explored the possibility of using a collision-induced-dissociation (CID) gas cell to break up molecular contaminant ions that are generated during the stopping process. A prototype CID gas cell was constructed and tested with beams from an offline ion source, validating the concept with the successful demonstration of breaking of molecular ions. The outcome of this research enabled the formulation a conceptual design for a next-generation linear gas stopping device specifically tailored for FRIB. This device is envisioned to deliver rare-isotope-ion beams at a rate of 10 8 particles per second or higher, accompanied by advancements in purity. Methods employed: This project leverages advancements in technologies initially designed for the Advanced Cryogenic Gas Stopper (ACGS), the current state-of-the-art linear gas stopper, through the use of new simulations and beam purification via collision-induced-dissociation. The methods include: 1. Development of a prototype low-energy, low-pressure CID gas stopper. This prototype features a thin, approximately 20 nm, Si 3 N 4 entrance window designed for dissociating stable and rare-isotope molecular ions. The goal is to enhance beam purification and overall efficiency. 2. Creation of Particle-in-cell (PIC) simulations to assess the advantages of multi-layer RF carpets and multi-point extraction for ion transport efficiency. These simulations rely on the 3DCylPIC package, specifically designed for studying devices of this nature. The goal is to quantify and mitigate ion transport losses due to space charge generated in the stopping process of large numbers of ions. 3. Perform ion transport simulations across an RF carpet using an 8-phase travelling wave and evaluate its performance. Compared to the 4-phase RF carpets used in ACGS, the 8-phase carpets will double the wavelength of the generated traveling wave allowing for larger maximum RF amplitudes that could result in improved ion transport efficiency for high-intensity incoming beams when large space charge fields are present. Impact: Tackling the primary challenges associated with transforming high-energy projectile fragment beams into low-energy beams—specifically, addressing efficiency and purity—holds significant promise for advancing FRIB science. This advancement will particularly impact precision mass measurements, laser spectroscopy of short-lived nuclei, and studies in astrophysics and nuclear reactions using reaccelerated beams. These domains play a crucial role in addressing key questions outlined in the 2023 NSAC long-range plan, spanning nuclear structure, nuclear astrophysics, and fundamental symmetries. Additionally, they contribute to addressing 10 out of the 17 benchmarks identified by the NRC RISAC. The development of a next-generation gas stopping device capable of delivering low-energy, rare-isotope beams at a rate of 10 8 particles per second, or more, with high purity holds the potential to unlock experiments that would otherwise be unfeasible. Furthermore, it is expected to reduce the time required for experiments at FRIB, thereby maximizing scientific output. The research and development activities performed as part of this project bolstered essential competencies at FRIB in beam physics and ion source technologies, provided valuable training opportunities for junior scientists.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

pmartR 2.0 : A Quality Control, Visualization, and Statistics Pipeline for Multiple Omics Datatypes

The pmartR (https://github.com/pmartR/pmartR) package was designed for the quality control (QC) and analysis of mass spectrometry (MS) data, tailored to specific characteristics of proteomic (isobaric or labelled), metabolomic, and lipidomic datasets. Since its initial release, the tool has been expanded to address the needs of its growing userbase and now includes QC and statistics for nuclear magnetic resonance (NMR) metabolomic data, and leverages the DESeq2, edgeR, and limma-voom R packages for some transcriptomic data analyses. These improvements have made progress towards a unified omics processing pipeline for ease of reporting and streamlined statistical purposes. The package’s statistics and visualization capabilities have also been expanded by adding support for paired data and by integrating pmartR with the trelliscopejs R package for the quick creation of trellis displays (https://github.com/hafen/trelliscopejs). Here, we present relevant examples of each of these enhancements to pmartR and highlight how each new feature benefits the omics community.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The CMS Statistical Analysis and Combination Tool: Combine

This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

gcamfaostat: An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling

The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat (v1.0) and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. One of the important features of the package is the possibility to construct the FAO Food Balance Sheets at the disaggregated commodity level (with over 500 commodities), which provides a comprehensive and detailed data input for a variety of analytical and modeling applications. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

pyEGAF: Modernization of the EGAF database

One of the most comprehensive resources for thermal neutron-capture data is the Evaluated Gamma-ray Activation File (EGAF), containing data from prompt gamma activation analysis measurements carried out at the Budapest Research Reactor for 245 isotopes. Although these valuable datasets have been freely available for many years, the outdated and cryptic adopted format makes it difficult to utilize the data and it is not generally suitable for modern computational technologies. Furthermore, to help overcome these challenges, we have converted the datasets into an open standard JSON format. Additionally, we have developed a Python implementation of an open-source software package, pyEGAF, designed to interact with the JSON data structures for general purpose access, manipulation, and rapid assessment of the capture-gamma data in EGAF.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗

DOE OSTI2023

PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization

We describe an update to our open-source Python package, PCAfold, designed to help researchers generate, analyze and improve low-dimensional data manifolds. In the current version, PCAfold 2.0, we introduce novel tools and algorithms for assessing and optimizing low-dimensional manifolds. This includes a method that generates a “map” of local feature sizes that can help pinpoint researchers to problematic regions on a manifold. We introduce a novel cost function that characterizes the quality of a manifold topology with a single number. We develop two algorithms for feature selection based on principal component analysis (PCA) that use the cost function as an objective function to minimize. We introduce a quantity of interest (QoI)-aware dimensionality reduction strategy where data projections are computed using an artificial neural network and are directly optimized towards representing various projection-independent and projection-dependent QoIs. We also introduce an implementation of partition of unity networks (POUnets) for efficient reconstruction of QoIs from low-dimensional manifolds based on combining neural network classification with localized polynomial regression. Our software can be broadly applicable in all domains of science and engineering that aim to reduce data dimensionality, as well as in the fundamental research on representation learning.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗

DOE OSTI2024

MolSym : A Python package for handling symmetry in molecular quantum chemistry

A consideration of the point group symmetry of molecules is often advantageous from a computational efficiency standpoint and sometimes necessary for the correct treatment of chemical physics problems. Many modern electronic structure software packages include a treatment of symmetry, but these are sometimes incomplete or unusable outside of that program’s environment. Therefore, we have developed the MolSym package for handling molecular symmetry and its associated functionalities to provide a platform for including symmetry in the implementation and development of other methods. Features include point group detection, molecule symmetrization, arbitrary generation of symmetry element sets and character tables, and symmetry adapted linear combinations of real spherical harmonic basis functions, Cartesian displacement coordinates, and internal coordinates. We present some of the advantages of using molecular symmetry as achieved by MolSym, particularly with respect to Hartree–Fock theory, and the reduction of finite difference displacements in gradient/Hessian computations. Furthermore, this package is designed to be easily integrated into other software development efforts and may be extended to further symmetry applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Temporal Analysis Of Products Statistical Analysis Processing

Temporal analysis of products statistical analysis package (tapsap) is a package for reading, cleaning, analyzing and making inference of temporal analysis of products (TAP) information. This package is designed with the intent for collaboration within the TAP community for advancing TAP analysis.

Kunz, MatthewR↗

DOE OSTI2022

dfdjaxGP

A small python package to fit Gaussian processes using Jax and leveraging the automatic differentiation in Jax to predict arbitrary derivatives from the GP. This package is meant to supplement the scientific community use of Gaussian process prediction with derivatives. The package is designed to smoothly work standalone or be used with the numpyro probabilistic programming language.

Grosskopf, Micheal↗

DOE OSTI2023

Jester

Jester is a Rust CLI designed to package and send time series or tabular data to the data warehouse DeepLynx. It primarily reads .csv files and then sends those via HTTP or Websocket requests to an external instance of DeepLynx. It is meant to run on a host computer which has access to the data.

Darrington, John↗

DOE OSTI2023

GHEDesigner [SWR-23-33]

GHEDesigner is a Python package for designing ground heat exchangers (GHE) used with ground source heat pump (GSHP) systems.

Mitchell, Matt↗

DOE OSTI2020

Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes a medium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

EOSPAC User’s Manual: V.6.5

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Physics of the Serrano Sn Transport Package

Serrano is a software package for simulating photon transport in moving material. It presently supports 1-D, unstructured 2-D for a wide variety of element types, and 3-D for tetrahedra and hexahedra. The package is designed to be a component of larger codes, such as radiation hydrodynamics codes. Only the radiation transport equations are solved by Serrano itself.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Pushing the Limits of Micro battery Capacity and Energy

Micro battery with higher energy density will extend the service life of the miniature sensors so that the scientists and engineers could be able to collect more data along with the time in ecological and environmental vectors, such as animal tracking. Within this project, a completely new cell design (Gen2) for micro batteries to further increase their cell capacity and energy is developed. The new cell design directly packages the active material in a hard aluminum case, decreasing the percentage of non-active components. The manufacturing process to improve wetting ability is studied and the trial run is finally given to evaluate the feasibility of the proposed technology. It’s found that both the capacity and energy with same battery size could be increased by 30% comparing with Gen1 micro battery technology previously developed by PNNL. The yield of Gen2 micro batteries is still lower due to the high degree of manual operation, especially for drilling process where more precise position control is needed. More effort is still required to improve the capability of automatic manufacturing processes. The new battery technology will support the development of smaller and lighter miniature sensors at PNNL and could potentially contribute to the large-scale manufacturing capabilities of micro batteries in US with reliable performances and long-term shelf life.

25 ENERGY STORAGE↗

DOE OSTI2025

EOSPAC User's Manual: Version 6.5 Second Edition (Rev. 3)

The EOSPAC utility package is a collection of interface routines, which can be used to access the SESAME data library and perform various data adjustments and interpolations on the SESAME data. The SESAME data library contains both thermodynamic (e.g., equation of state) and transport coefficients (e.g., opacity and conductivity). Note, for simplicity, the term EOS (equation of state) used herein includes both thermodynamic variables and transport coefficients. The EOSPAC utility package is designed to be used by physics codes (henceforth ”host codes”) written in multiple languages and on multiple platforms. The remainder of this manual is organized into several sections. Chapter 2 discusses conventions such as data organization and routine names. Chapter 3 provides a general overview of basic theory and models implemented within EOSPAC. Chapter 4 provides a general overview of how to use the EOSPAC interface library. Chapters 5 to 7 describe the public interfaces of EOSPAC in detail. Chapter 8 provides a brief introduction to some related tools, which may be of use to the user. Chapter 9 provides details related to some selected numerical features of EOSPAC. Chapter 10 gives examples for using the interface routines described in chapters 5 to 7. Chapter 11 provides technical support contact information. Chapter 12 contains a brief set of acknowledgments. Chapter 13 contains a list of referenced documents. Finally, chapter 14 lists the “table types: mnemonic conventions”, “table types: grouped by category, sorted by name”, “table types: eospac version 5 cross reference”, “options: setup phase”, “data information parameters”, “meta-data information parameters”, “options: interpolation phase”, and the “error codes”.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗