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DOE OSTI2023

Batteries 2022 Annual Progress Report

This document summarizes the progress of VTO battery R&D projects supported during the fiscal year 2022. Its R&D focus was on the development of high-energy batteries for PEVs. The electrochemical energy storage roadmap describes ongoing and planned efforts to develop electrochemical storage technologies for EVs. To advance battery technology, which can in turn improve market penetration of PEVs, the program investigates various battery chemistries to overcome specific technical barriers, e.g., battery cost, performance, life (both the calendar life and the cycle life), its tolerance to abusive conditions, and its recyclability/sustainability.

25 ENERGY STORAGE↗

DOE OSTI2024

Batteries (2023 Annual Progress Report)

This document summarizes the progress of VTO battery R&D projects supported during the fiscal year 2023. Its R&D focus was on the development of high-energy batteries for PEVs. The electrochemical energy storage roadmap describes ongoing and planned efforts to develop electrochemical storage technologies for EVs. To advance battery technology, which can in turn improve market penetration of PEVs, the program investigates various battery chemistries to overcome specific technical barriers, e.g., battery cost, performance, life (both the calendar life and the cycle life), its tolerance to abusive conditions, and its recyclability/sustainability.

25 ENERGY STORAGE↗

DOE OSTI2026

Machine Learning-Based Anomaly Detection for PMT Data Quality Monitoring in the SBN and DUNE

Maintaining high-quality detector data is essential for achieving the scientific objectives of the Short-Baseline Neutrino (SBN) Program at Fermilab. Current data quality monitoring (DQM) procedures rely primarily on threshold-based metrics and manual inspection of detector monitoring plots, making the detection of subtle or gradually developing anomalies both time-consuming and dependent on expert interpretation. This project developed and evaluated a machine-learning workflow for automatically identifying anomalous photomultiplier tube (PMT) channels in the Short-Baseline Near Detector (SBND) using optical-hit amplitude data. A Python-based analysis program was developed to process ROOT files, extract statistical features describing individual PMT amplitude distributions, and generate feature vectors for anomaly detection. These features were used to train an Isolation Forest model using data representing normal detector operation. The trained model was subsequently applied to independent detector runs to identify channels exhibiting statistically unusual behavior relative to the learned reference response. To support expert interpretation, the workflow generated complementary diagnostic products, including anomaly score distributions, normalized amplitude comparisons, decision-tree visualizations, and principal component analysis (PCA) projections. This project demonstrated the feasibility of integrating unsupervised machine learning into detector data-quality monitoring and developed a complete workflow for automated PMT performance assessment to aid expert-driven review. Beyond its technical contributions, the VFP appointment fostered a research collaboration between Aurora University and Fermilab and provided direct workforce development benefits by training the visiting faculty member in detector-scale machine-learning methods that are now being incorporated into undergraduate coursework and research. The methodology developed here provides a foundation for future applications to ProtoDUNE and other liquid argon time projection chamber (LArTPC) detectors, contributing to ongoing efforts to improve detector reliability, reduce manual monitoring requirements, and enable scalable data quality monitoring for future large-scale neutrino experiments, including the Deep Underground Neutrino Experiment (DUNE).

Colón Santana, Juan A. [Unlisted, US, IL]↗

DOE OSTI2026

Draft ASME Code Case to qualify L-PBF 316H material for Section III, Division 5 applications

This report documents the AMMT program’s development and submission of a draft ASME Code Case to qualify Laser Powder Bed Fusion (L PBF) Type 316H stainless steel for Section III, Divi-sion 5 Class A and SM high temperature nuclear applications. It summarizes the technical basis, the comprehensive high temperature mechanical test database assembled between 2023–2026, and the proposed code language and qualification framework submitted to ASME. The work was co-ordinated across multiple national laboratories and leverages prior ASME efforts to integrate additive manufacturing into the Boiler & Pressure Vessel Code. The body of the report describes the experimental database and analysis supporting the Code Case: tensile, creep, fatigue, creep fatigue, and thermal aging tests collected from multiple additive manufacturing sites, machine types, and powder lots, with material processed by a solution anneal heat treatment. The dataset — including both full size and subsized specimens and tests oriented parallel and perpendicular to build direction — shows limited tensile anisotropy, tensile properties comparable to wrought 316H, creep strength within the scatter of wrought material, but markedly reduced creep ductility above about 650 °C associated with rapid σ phase formation in L PBF microstructures. The draft Code Case itself prescribes a staged qualification model (manufacturing process qualification, component qualification, and per build witness testing), treats L PBF components as equivalent to Type 316 weld metal for design and inspection, and requires mechanical, chemical, and metallographic controls tied to ASTM/ISO 52946. Key acceptance criteria include tensile tests within a 90% prediction interval of the AMMT dataset, a creep fatigue screening test adapted from ASME Section III, Division 5, Subsection HB, HBB 2800 but with the cycle acceptance reduced to 100 for L PBF material, and double volumetric inspection of production components. The report concludes that the present data support treating L PBF 316H as analogous to conventional fusion weld metal for Division 5 design and inspection, while highlighting important caveats: the σ phase driven loss of creep ductility above ~650 °C, preliminary indications of enhanced creep fatigue sensitivity in some lots, and remaining gaps in long term aging and additional cyclic testing. Recommended next actions include completing outstanding cyclic and long duration creep/aging tests on the solution annealed condition, supporting inclusion of the 316H chemistry and heat treatment in ASTM/ISO 52946, and continuing engagement with ASME and NRC during balloting and review to enable industry adoption.

Messner, Mark C. (ORCID:0000000200404385)↗

DOE OSTI2022

Real-time Measurements of Complex Transition Metal Oxide Nanostructure Growth (Final Technical Report)

This is the final technical report for a collaborative project between the Ross Lab at MIT and the Filler Lab at Georgia Tech. The project aimed to combine in situ microscopy and spectroscopy measurements to answer fundamental questions about the physics and chemistry governing the bottom-up vapor-solid-liquid (VLS) growth of one-dimensional (1-D) functional oxides. This work supported one PhD student and 1 postdoc. One paper has been published and 5 others are in preparation. To date, this work has been presented at 5 conferences.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗

DOE OSTI2022

Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) Version 4.1 Technical Reference Manual

The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 4.1. The two most significant changes for HyRAM+ version 4.1 from HyRAM+ version 4.0 are direct incorporation of unconfined overpressure into the QRA calculations and modification of the models for cryogenic liquid flow through an orifice. In QRA mode, the user no longer needs to input peak overpressure and impulse values that were calculated separately; rather, the unconfined overpressure is estimated for the given system inputs, leak size, and occupant location. The orifice flow model now solves for the maximum mass flux through the orifice at constant entropy while conserving energy, which does not require a direct speed of sound calculation. This does not affect the mass flow for all-gaseous releases; the method results in the same speed of sound for choked flow. However, this method does result in a higher (and more realistic) mass flow rate for a given leak size for liquid releases than was previously calculated.

08 HYDROGEN↗

DOE OSTI2022

High-Accuracy Angle Generator for Angular Calibrations to Support Optical Metrology Laboratories and Light Source Facilities

The overarching vision for this project was to build the most accurate full-rotation angular positioning system in the Americas, and that goal remains. In labs performing similar work, the environment is typically closer to a clean room than an office space, like we had before the upgrades. We are now positioned to achieve our intended result with our upgraded infrastructure, system hardware, calibration techniques, and software. As detailed below, the combination of the pandemic schedule and technical challenges have set us back, but we will continue on the path toward our vision beyond the end of this Phase 2. It’s too important for us, for industry, and for the nation not to do so.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

W.A. Parish Post-Combustion CO 2 Capture and Sequestration Demonstration Project (Final Technical Report)

The Petra Nova Project (Project) is a commercial scale post-combustion carbon capture project developed by a joint venture between NRG Energy, Inc. (NRG) and JX Nippon Oil Exploration (EOR) Limited (JX). The Project is designed to separate and capture carbon dioxide (CO2) from an existing coal-fired unit’s flue gas slipstream at NRG’s W.A. Parish Electric Generating Station (WAP) located southwest of Houston, Texas. The captured CO2 is dried, compressed, and transported via an 81-mile pipeline to the West Ranch oilfield (West Ranch) in Jackson County, Texas, where it is injected to boost oil production. The Project, which is partially funded by a grant (Grant) from the United States (U.S.) Department of Energy (DOE) under the Clean Coal Power Initiative (CCPI) Round 3, uses the Kansai Mitsubishi Carbon Dioxide Recovery advanced amine-based CO 2 absorption technology (KM-CDR Process®), which was jointly developed by Mitsubishi Heavy Industries, Ltd. (MHI) and the Kansai Electric Power Co. Inc., to treat and capture at least ninety percent (90%) of the CO 2 from a 240-megawatt equivalent (MWe) flue gas slipstream off of Unit 8 at WAP. When operating at full capacity, the Project captures approximately 5,200 short tons of CO 2 per day, which would otherwise be emitted into the atmosphere, representing the largest commercial scale deployment of post-combustion CO2 capture technology at a coal power plant to date. Under the Grant, the Project was managed in 3 phases: (1) Phase 1: Project Definition / Front End Engineering Design (FEED) (2) Phase 2: Detailed Engineering, Procurement & Construction (3) Phase 3: Demonstration and Monitoring. On December 29, 2016, commercial operation of the Project was achieved, ending Phase 2 and starting Phase 3, a 3-year demonstration period running from January 1, 2017 through December 31, 2019. The key objectives of Phase 3 were to (a) demonstrate the specific advanced technologies constructed during Phase 2 and (b) monitor the injected CO 2 at West Ranch to demonstrate technologies and protocols for monitoring, verification, and accounting (MVA). As of the end of Phase 3, Petra Nova captured 3,904,978 short tons of CO 2 (3,542,537 metric tons) that was transported to West Ranch. To support the DOE obligation to monitor, verify, and account for the sequestered CO 2 at West Ranch, Petra Nova contracted with the Bureau of Economic Geology (in the Jackson School of Geosciences at The University of Texas at Austin) to (a) design a monitoring program, (b) draft an MVA Plan for DOE review and approval, and (c) working with Petra Nova and the operator of West Ranch to manage and report on the MVA activity. This report discussed the technical aspects of the project during each of the 3 phases of the project as identified above.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗

DOE OSTI2025

Implications of Aerosol Physicochemical Properties Including Ice Nucleation at ARM Mega Sites for Improved Understanding of Microphysical Atmospheric Cloud Processes (Final Technical Report)

Continuous, long-term measurements of atmospheric ice-nucleating particles (INPs) that influence clouds and precipitation were conducted to investigate the abundance and variability of ground-level INPs across the world. Three field campaigns were organized by the DOE Atmospheric Radiation Measurement (ARM) program, including Examining INP from Southern Great Plains (ExINP-SGP, 2019), Examining INP from Eastern North Atlantic (ExINP-ENA, 2020 – 2021), and Examining INP from North Slope of Alaska (ExINP-NSA, 2021 – 2024). Additional small-scale supporting field experiments were performed in 2019 and 2021 to collect airborne particulate matter at SGP for complementary laboratory characterization of the particles’ physical and chemical properties [Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY), 2019; ExINP-SGP II, 2021]. In these studies, the PI’s team measured INP concentration with both real-time and laboratory measurements in a wide range of freezing temperatures ($T$ from 0 °C to about –30 °C). This project elucidated spatial variability and seasonality in the abundance of immersion mode active INPs across three ARM sites using a single instrument, a Portable Ice Nucleation Experiment (PINE) chamber version 03 (PINE-03 hereafter). Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient INP abundance, air mass origin region, and meteorological variability. Our findings suggest very high freezing efficiency of INPs at the NSA site across the measured temperatures (ice nucleation active surface site density, $n_s(T)$, $\approx 2 \times 10^{8} - 10^{10}$ m -2 for from –16 to –31 °C), which is a factor of 10 – 1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in autumn using the same instrument; surprisingly high INP abundance ($\ge 1 \text{ L}^{-1}$ at –25 °C) for the examined temperatures throughout the year that PINE-03 did not measure at other sites; and high INP concentration in spring, possibly related to arctic haze episodes.

58 GEOSCIENCES↗

DOE OSTI2025

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Merefa Community Microgrid: Supporting Distributed Energy Resource Deployment in Ukraine

A conceptual design is described for a community microgrid in Ukraine. Microgrid resources include solar photovoltaics, battery energy storage, and conventional natural gas fueled reciprocating engine generators. The conceptual architecture was informed by the microgrid developer, NREL subject matter experts, and the application of REopt, an NREL-developed software tool created for identification of least-cost combination of resources for achieving cost savings, resilience, and renewable energy goals. This fact sheet is a summary of a previously published technical report; see NREL/TP-7A40-89527, which includes conceptual architecture, estimates of key summary financial metrics, and sequence of operations.

battery storage↗

DOE OSTI2022

A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.

Bernholdt, David↗

DOE OSTI2023

Experiential findings for sustainable software ecosystems to support experimental and observational science

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. Here, the study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: (i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and (ii) data management requirements for data-driven science using artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Federal Energy Management Program’s Technical Resilience Navigator: Communications Plan

The Federal Energy Management Program is working to develop a standard, agency-neutral energy and water technical resilience navigator (TRN) to assist federal agencies with their resilience planning efforts, building on agency-expressed needs. The TRN Communications Plan defines how the project team and FEMP will generate awareness of the TRN, recruit validators, encourage its use across federal agencies, increase awareness among various audiences, and solicit user feedback on its usefulness including suggestions for improvement. In support of this purpose, the communications plan characterizes the key audiences, messages, communications channels, and activities needed to help ensure success. The role of communications is to define strategy and ensure leadership and consistency in messaging, writing, outreach, media relations, editing, and design related to the TRN.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Grid Planning for Building Electrification: A Report by the Energy Systems Integration Group’s Grid Planning for Building Electrification Task Force

The increased electrification of buildings across the United States is being driven by technical advancements, cost reductions for some building technologies, consumer preferences, and policy goals for decarbonization. However, the effects of this load growth on the electric distribution system are often only a minor consideration in policymaking and long-term planning studies. The long lead time and useful life of power system equipment means that the decisions taken today are expected to support our society well into the 2060s and beyond. Distribution planning stakeholders can take steps today to establish a grid foundation that captures the new challenges presented by building electrification. This report focuses on building electrification for the residential and commercial sectors, focusing most heavily on space heating, as this end use stands to most strongly impact demand.1 Across all end uses, building electrification could require somewhere between 10% and 70% more electricity generation capacity than exists today depending on technology adoption and energy efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗