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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Software Verification of VARPOW

The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power densities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. The purpose of this work is to verify the power distribution results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Software Verification of VARPOW

The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power desnities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. The purpose of this work is to verify the power distribution results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Software Verification of VARPOW

The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power desnities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. Recently the clad neutron damage calculation capability was introduced into VARPOW, and it now allows a pathway to get distributions of clad DPA. The purpose of this work is to verify the power distribution, fast neutron flux and clad DPA results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.

Zhong, Zhaopeng [Argonne National Laboratory (ANL)↗
DOE OSTI2021

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗
DOE OSTI2021

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗
DOE OSTI2024

Real-Time Ethernet Interface for NSTX-U’s Thomson Scattering Diagnostic (2023)

Here, the multipoint Thomson scattering (MPTS) diagnostic system at the National Spherical Torus Experiment Upgrade (NSTX-U) facility is undergoing an upgrade to operate in real-time and interface with the plasma control system (PCS) for NSTX-U. Previous prototyping efforts have shown that spectral analysis and rapid calculations of electron temperature and density are possible on a real-time Linux machine when using up to a 100-Hz laser pulse repetition rate. A remaining challenge was transferring the real-time data to NSTX-U’s PCS, which utilizes the front panel data port (FPDP) protocol. The original proposed method was to convert the real-time data into analog values, but a new solution was developed to keep the output format digital by using an Ethernet controller with a field-programmable gate array (FPGA). This article focuses on a new input module that has been developed to accept incoming user datagram protocol (UDP) packets sent over Ethernet, convert into FPDP format, and integrate into the existing data stream under NSTX-U’s real-time framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Safe Operations at Roadway Junctions: Intelligent Roadway Infrastructure as Functional Interlocking

Automated vehicle (AV) technology is quickly maturing, and the corresponding infrastructure systems that evaluate traffic and communicate to vehicles requires sophisticated sensing and perception technologies, referred to as intelligent roadway infrastructure (IRI), to complement emerging AV capabilities. IRI provides signals to vehicles, indicating right-of-way for vehicles and communicating to approaching AVs that no other vehicle is failing to yield. This capability, denoted as safety-affirmative signaling, provides a green light or a green arrow as appropriate and affirms through communication links to connected vehicles when it is safe to proceed. About 36% of collisions occur at intersections, with most occurring upon left turns (22.2%) or crossing over (12.6%), and only a small percentage (1.2%) while turning right at an intersection. Of all intersection crashes about half (52.5%) of those vehicles were traveling through a signalized intersection 2. Safety-affirmative signaling would guarantee safety of AV fleet vehicles, by providing the interlocking principle, a term from automated train control that only allows progression through a railway intersection after affirming no opportunity for a crash exists. IRI through safety-affirmative signaling would bring performance and safety to complex roadway intersections where AV transit fleet service is most needed, as well as safety benefits to traditional, non-automated vehicles and vulnerable road users. The implementation of IRI has functional, programmatic, and technical challenges. Research work performed at the National Renewable Energy Laboratory (NREL) in an integrative approach encapsulating these themes, and termed infrastructure perception and control (IPC) is motivated by improved performance (travel time), improved safety (reduced collisions), and improved energy efficiency (less fuel burned and minimized production of greenhouse gases). IPC is intended not only for roadway and intersection applications but also in extension to inform complementary buildings and grid systems to enable better co-management, as vehicles and their charging needs become increasingly integrated into the built environment. The NREL IPC project presents an open-source framework, architecture, and supporting technology to implement IRI, addressing critical issues such as fusion of data, reliability, standardization of data interfaces, and confidence of detection. The framework is informed by previous experience in U.S. Department of Defense research technology, specifically in the use of radar to detect, identify, and track aerial threats. These principles combined with multi-sensor fusion provides for a complete digital twin with known and measurable confidence and accuracy from which safety-affirmative signaling can be developed and deployed.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2024

AEcroscopy: A Software–Hardware Framework Empowering Microscopy Toward Automated and Autonomous Experimentation

Microscopy has been pivotal in improving the understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most characterization labs. However, traditional microscopy operations are still limited largely by a human-centric click-and-go paradigm utilizing vendor-provided software, which limits the scope, utility, efficiency, effectiveness, and at times reproducibility of microscopy experiments. Here, in this work, a coupled software–hardware platform is developed that consists of a software package termed AEcroscopy (short for Automated Experiments in Microscopy), along with a field-programmable-gate-array device with LabView-built customized acquisition scripts, which overcome these limitations and provide the necessary abstractions toward full automation of microscopy platforms. The platform works across multiple vendor devices on scanning probe microscopes and electron microscopes. It enables customized scan trajectories, processing functions that can be triggered locally or remotely on processing servers, user-defined excitation waveforms, standardization of data models, and completely seamless operation through simple Python commands to enable a plethora of microscopy experiments to be performed in a reproducible, automated manner. This platform can be readily coupled with existing machine-learning libraries and simulations, to provide automated decision-making and active theory-experiment optimization to turn microscopes from characterization tools to instruments capable of autonomous model refinement and physics discovery.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

EXCHANGE Campaign 1: A Community-Driven Baseline Characterization of Soils, Sediments, and Water Across Coastal Gradients

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program is a consortium of scientists working together to improve our understanding of how the two-way exchange of water between estuaries or large lake lacustuaries and the terrestrial landscape influence the state and function of ecosystems across the coastal interface. EXCHANGE Campaign 1 (EC1) focuses on the spatial variation in biogeochemical structure and function at the coastal terrestrial-aquatic interface (TAI). In the Fall of 2021, the EXCHANGE Consortium gathered samples from 52 TAIs. Samples collected from EC1 were analyzed for bulk geochemical parameters, bulk physicochemical parameters, organic matter characteristics, and redox-sensitive elements.Please download ec1_README.pdf for a complete list of available data in each .zip folder, package version history, and detailed information about the project. This README will serve as the central place for EC1 Data Package updates. Experimental setup and v1 methods are documented in Myers-Pigg and Pennington et al., 2023 (https://doi.org/10.1038/s41597-023-02548-7).EC1 Data Package Structure:ec1_README.pdfec1_methods.pdfec1_metadata_v3.zip...ec1_dd.csv...ec1_flmd.csv...ec1_sample_catalog.csv...ec1_metadata_kitlevel.csv...ec1_metadata_collectionlevel.csv...ec1_data_collectionlevel.csv...ec1_igsn_metadata.csvec1_soil_v3.zipec1_sediment_v3.zipec1_water_v3.zipec1_processingscripts_v3.zipThis data package is on v3 and was originally published May 2023 (v1). Subsequent updates will be published here with new version numbers. Please see the Change History section in ec1_README.pdf for detailed changes.---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

iSPECTRON: a simulation interface for linear and nonlinear spectra with ab-initio quantum chemistry software

We introduce iSPECTRON, an open source (under the Educational Community License version 2.0) program that parses data from common quantum chemistry software (NWChem, OpenMolcas, Gaussian, Cobramm, etc.), produces the input files for the simulation of linear and nonlinear spectroscopy of molecules with the Spectron code, and analyzes the spectra with a broad range of tools. Vibronic spectra are expressed in term of the electronic eigenstates, obtained through quantum chemistry computations, and vibrational/bath effects are incorporated in the framework of the displaced harmonic oscillator model, where all required quantities are computed at the Franck-Condon point. The code capabilities are illustrated by simulating linear absorption, transient absorption and two dimensional electronic spectra of the pyrene molecule. Two levels of electronic structure theory, TDDFT (with NWChem) and RASSCF/RASPT2 (with OpenMolcas), are compared where possible. Acknowledgements: F.S., A.N., D.R.N., N.G., S.M, M.G. acknowledge support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division under Award Nos. DE-SC0019484, KC-030103172684. The Spectron code was developed with support from the National Science Foundation (Grant CHE- 1953045). This research benefited from computational resources provided by EMSL, a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research and located at PNNL. PNNL is operated by Battelle Memorial Institute for the United States Department of Energy under DOE Contract No. DE-AC05-76RL1830.

Segatta, Francesco↗
DOE OSTI2025

Ground surface temperature derived Snow Cover Properties, Seward Peninsula, Alaska, 2019-2023

Snow-ground interface temperatures have been collected at the Teller mile marker 27 and Kougarok mile marker 64 field sites on the Seward Peninsula, Alaska from 2019 through 2023 (with data missing from Fall 2020 through Summer 2021 due to COVID). Temperatures were measured using iButton Link DS1921G-F5# Thermochron miniature temperature sensors and Tinytag TGP-4017 internal sensors deployed across the Kougarok 64 and Teller 27 field sites. These sensors are a cost-efficient way to collect snow-ground interface temperatures at a high spatial resolution, and when paired with air temperature data these measurements can provide insight into fine-scale variability in snowpack characteristics across the study sites. From this data, snow process metrics were calculated at each sensor location based on the methods outlined in Staub and Delaloye, 2017. Metrics are calculated daily for each sensor as well as over the entire season. These metrics include ground surface temperature (°C), the number of days under snow cover (number of days), the insulation effect of snow (unitless), the length of the transitional snow periods (number of days), as well as intermediaries such as temperature variability. Calculating these snow processes relies on the assumption that when snow covers a temperature sensor, it is buffered from diurnal fluctuations in air temperature by the insulating snow layer. More information on the calculated metrics can be found in the User Guide of this dataset, as well as in Staub and Delaloye’s 2017 publication Using Near-Surface Ground Temperature Data to Derive Snow Insulation and Melt Indices for Mountain Permafrost Applications. This dataset includes one daily and one seasonal *.csv file of metrics for every year of data, a daily and a seasonal *.csv data dictionary, and one User Guide document (*.pdf) describing data collection and processing.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
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

Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning

Here, we develop a computational database, website applications (web-apps), and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D) heterostructures. Using density functional theory (DFT) based lattice parameters and electronic band energies for 674 nonmetallic exfoliable 2D materials, we generate 226 779 possible bilayer heterostructures. We classify these heterostructures into type-I, -II, and -III systems according to Anderson’s rule, which is based on the relative band alignments of the noninteracting monolayers. We find that type II is the most common and type III the least common heterostructure type. We subsequently analyze the chemical trends for each heterostructure type in terms of the Periodic Table of constituent elements. The band alignment data can also be used for identifying photocatalysts and high-work-function 2D metals for contacts. We validate our results by comparing them to experimental data as well as hybrid-functional predictions. Additionally, we carry out DFT calculations of a few selected systems (MoS 2 /WSe 2 , MoS 2 /h-BN, and MoSe 2 /CrI 3 ), to compare the band-alignment description with the predictions from Anderson’s rule. We develop web-apps to enable users to virtually create combinations of 2D materials and predict their properties. Additionally, we use ML tools to predict band-alignment information for 2D materials. The web-apps, tools, and associated data will be distributed through the JARVIS-HETEROSTRUCTURE website. Our analysis, results, and the developed web-apps can be applied to the screening and design applications, such as finding alternative photocatalysts, photodetectors, and high-work-function (WF) 2D-metal contacts.

2-dimensional systems↗
DOE OSTI2023

Skin-integrated stretchable actuators toward skin-compatible haptic feedback and closed-loop human-machine interactions

Abstract Skin-integrated haptic interfaces that can relay a wealth of information from the machine to the human are of great interest. However, existing haptic devices are not yet able to produce haptic cues that are compatible with the skin. In this work, we present the stretchable soft actuators for haptic feedback, which can match the perception range, spatial resolution, and stretchability of the skin. Pressure-amplification structures are fabricated using a scalable self-assembly process to ensure an output pressure beyond the skin perception threshold. Due to the minimized device size, the actuator array can be fabricated with a sufficiently high spatial resolution, which makes the haptic device applicable for skin locations with the highest spatial acuity. A haptic feedback system is demonstrated by employing the developed soft actuators and highly sensitive pressure sensors. Two proof-of-concept applications are developed to illustrate the capability of transferring information related to surface textures and object shapes acquired at the robot side to the user side.

Chen, Si↗
DOE OSTI2019

Multiscale porous elastomer substrates for multifunctional on-skin electronics with passive-cooling capabilities

In addition to mechanical compliance, achieving the full potential of on-skin electronics needs the introduction of other features. For example, substantial progress has been achieved in creating biodegradable, self-healing, or breathable, on-skin electronics. However, the research of making on-skin electronics with passive-cooling capabilities, which can reduce energy consumption and improve user comfort, is still rare. Herein, we report the development of multifunctional on-skin electronics, which can passively cool human bodies without needing any energy consumption. This property is inherited from multiscale porous polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene (SEBS) supporting substrates. The multiscale pores of SEBS substrates, with characteristic sizes ranging from around 0.2 to 7 µm, can effectively backscatter sunlight to minimize heat absorption but are too small to reflect human-body midinfrared radiation to retain heat dissipation, thereby delivering around 6 °C cooling effects under a solar intensity of 840 W∙m -2 . Other desired properties, rooted in multiscale porous SEBS substrates, include high breathability and outstanding waterproofing. The proof-of-concept bioelectronic devices include electrophysiological sensors, temperature sensors, hydration sensors, pressure sensors, and electrical stimulators, which are made via spray printing of silver nanowires on multiscale porous SEBS substrates. The devices show comparable electrical performances with conventional, rigid, nonporous ones. Also, their applications in cuffless blood pressure measurement, interactive virtual reality, and human–machine interface are demonstrated. Notably, the enabled on-skin devices are dissolvable in several organic solvents and can be recycled to reduce electronic waste and manufacturing cost. Such on-skin electronics can serve as the basis for future multifunctional smart textiles with passive-cooling functionalities.

42 ENGINEERING↗
DOE OSTI2024

Greenhouse gas and dissolved oxygen production and consumption rates associated with Regier et al. (2023)

Tidal inundation along the coastal terrestrial-aquatic interface controls soil and sediment biogeochemistry and gas dynamics. Although a rich literature exist on studies of the influence of tidal waters on the biogeochemistry of coastal ecosystem soils, few studies have experimentally addressed the reverse question: How do soils (or sediments) from different coastal ecosystems influence the biogeochemistry of the tidal waters that inundate them? We conducted short-term microcosm laboratory experiments where seawater was amended with sediments and soils collected across regional gradients of inundation exposure (i.e., frequently to rarely inundated) and measured changes in dissolved oxygen and greenhouse gas concentrations to calculate gas consumption or production rates occurring during seawater exposure to terrestrial materials. This data package contains dissolved oxygen and greenhouse gas data collected during incubation of soils and sediments collected at 18 sites, which were used in the publication Regier et al. (2023) entitled “Coastal inundation regime moderates the short-term effects of sediment and soil additions on seawater oxygen and greenhouse gas dynamics: a microcosm experiment” which is published in Frontiers in Marine Science (DOI: https://doi.org/10.3389/fmars.2023.1308590).---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Preconceptual Designs of Coupled Power Delivery between a 4-Loop PWR and 100-500 MWe HTSE Plants

This study develops a preconceptual design for the integration between a large-scale high-temperature electrolysis facility and a NPP. Two hydrogen facility sizes are considered: 100 MWnom and 500 MWnom. Both steam supply designs use cold reheat steam extraction as a heat source. A reboiler inside the protected area of the power plant transfers steam heat to the demineralized water supply for the hydrogen plant. After the heat transfer, the extracted steam condenses and returns to the condenser while the process steam routes out of the protected area to the electrolyzers. Electrical power is tapped off from the high voltage side of the GSU transformer, where it is then transported via a 345-kV transmission line to the hydrogen facility. Circuit breakers and disconnects are located at both ends of the transmission line. Step down transformers and miscellaneous switchgear/buses are located at the end of the transmission line inside the HTEF boundary. Control capabilities for the steam interfacing equipment and electrical dispatch are accessible from the Main Control Room, and protective relays for the transmission line are located inside the Relay Room. Computer modeling was performed for the thermal and electrical designs. PEPSE analysis provided the steady-state parameters for thermal extraction from the turbine cycle. These parameters were used to inform transients and size equipment in combination with Applied Flow Technology (AFT) Arrow and AFT Fathom modeling for steam and water piping, respectively. Electrical transients were analyzed using PSCAD. An ETAP model was used to evaluate power flow and short circuit, which enabled the sizing of transformers and protective equipment. A cost estimate was developed for both integration designs when considering plant separation distances of 250 m and 500 m. From these estimates, the modifications for thermal and electrical interfacing of a first-of-a-kind nuclear-integrated hydrogen facility are anticipated to cost between $60–250/kWnom., where the subscript “nom” refers to the nominal size of the hydrogen plant. On a thermal power basis, the thermal power has a cost of approximately $8/MWth for a 500 MWnom high temperature electrolysis plant located 500 m distant from the NPP. That value decreases to approximately $7.5/MWth for a 250 m separation distance between the hydrogen plant and the NPP. This value is lower than previous estimates of the cost of heat extracted from NPPs primarily because in this work the steam is extracted from cold reheat instead of the main steam line, which reduces the cost of the dispatched steam by approximately $3.5/MWth. Nuclear steam extraction can provide a profit avenue for many plants and is not restricted to hydrogen production. Ammonia production, oil refining, and paper production, among other industrial processes all require thermal energy, which can be provided by NPPs. Future work should look further at the details of thermal extraction for a variety of use cases. This can include increased levels of extraction and multiple simultaneous users. Additionally, site-specific studies should be performed to develop industry experience and improve cost accuracy.

08 HYDROGEN↗