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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tomographic X-ray particle tracking velocimetry

We investigate the feasibility of in-laboratory tomographic X-ray particle tracking velocimetry (TXPTV) and consider creeping flows with nearly density matched flow tracers. Specifically, in these proof-of-concept experiments we examined a Poiseuille flow, flow through porous media and a multiphase flow with a Taylor bubble. For a full 360° computed tomography (CT) scan we show that the specially selected 60 micron tracer particles could be imaged in less than 3 seconds with a signal-to-noise ratio between the tracers and the fluid of 2.5, sufficient to achieve proper volumetric segmentation at each time step. In the pipe flow, continuous Lagrangian particle trajectories were obtained, after which all the standard techniques used for PTV or PIV (taken at visible wave lengths) could also be employed for TXPTV data. And, with TXPTV we can examine flows inaccessible with visible wave lengths due to opaque media or numerous refractive interfaces. In the case of opaque porous media we were able to observe material accumulation and pore clogging, and for flow with Taylor bubble we can trace the particles and hence obtain velocities in the liquid film between the wall and bubble, with thickness of liquid film itself also simultaneously obtained from the volumetric reconstruction after segmentation. While improvements in scan speed are anticipated due to continuing improvements in CT system components, we show that for the flows examined even the presently available CT systems could yield quantitative flow data with the primary limitation being the quality of available flow tracers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

EV Charging Infrastructure Energization An Overview of Approaches for Simplifying and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Characterization of self-magnetic pinch radiographic diode performance on RITS-6 at Sandia National Laboratories. II. Coupling between the inductive voltage adder and the SMP load

The self-magnetic pinch (SMP) diode is a type of radiographic diode used to generate an intense electron beam for radiographic applications. At Sandia National Laboratories, SMP was the diode load for the six-cavity radiographic integrated test stand inductive voltage adder (IVA) driver operated in a magnetically insulated transmission line (MITL). The MITL contributes a flow current in addition to the current generated within the diode itself. Extensive experiments with a MITL of 40Ω load impedance [T. J. Renk et al., Phys. Plasmas 29, 023105 (2022)] indicate that the additional flow current leads to results similar to what might be expected from a conventional high-voltage interface driver, where flow current is not present. However, when the MITL flow impedance was increased to 80 Ω, qualitatively different diode behavior was observed. This includes large retrapping waves suggestive of an initial coupling to low impedance as well as diode current decreasing with time even as the total current does not. A key observation is that the driver generates total current (flow + diode) consistent with the flow impedance of the MITL used. The case is made in this paper that the 80Ω MITL experiments detailed here can only be understood when the IVA-MITL-SMP diode is considered as a total system. Additionally, the constraint of fixed total current plus the relatively high flow impedance limits the ability of the diode (whether SMP or other type) to act as an independent load. An unexpected new result is that in tracking the behavior of the electron strike angle on the converter as a function of time, we observed that the conventional cIV x “Radiographic” radiation scaling (where x~2.2) begins to break down for voltages above 8 MV, and cubic scaling is required to recover accurate angle tracking.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Parameterization of the Elevated Convection With a Unified Convection Scheme (UNICON) and Its Impacts on the Diurnal Cycle of Precipitation

To improve the simulation of nocturnal precipitation, we develop a parameterization for the elevated convection that is launched from the level of maximum grid-mean moist static energy, when grid-mean vertical flow is upward at the launching interface. The parameterized elevated convection is forced by both cold pool-driven and partially resolved external mesoscale organized flows. Properties of the external mesoscale flow are estimated from grid-mean vertical velocity and three dimensional advection tendencies of temperature and moisture. The new parameterization is implemented into a unified convection scheme (UNICON) and tested for both the single-column case at the Southern Great Plain (SGP) site in US and in global simulations. At the SGP site, the parameterized elevated convection strengthens nocturnal convection, increases nocturnal precipitation, and better simulates the observed diurnal cycle of precipitation. It appears that the elevated and surface-based convections interact with each other by stabilizing the atmospheric column, which affects subsequent convection. Global simulation shows that the elevated convection mostly occurs over the continents during the night, and also over the oceanic mid-latitude warm air advection and storm track regions during summer. Without degrading global mean climate, the elevated convection improves the simulation of nocturnal precipitation in the mid-US but simulates somewhat strong nocturnal precipitation in northeastern Asia. It seems that a key to simulate observed nocturnal precipitation is to appropriately parameterize the impacts of external organized flow on the elevated convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

An Autonomous MCP Bridge to Rucio: Enhancing Data Management Accessibility for High Energy Physics

The Rucio Data Management System [1] is an important tool used by High Energy Physics experiments, including those at Fermi National Accelerator Laboratory, to store and manage exabyte-scale scientific datasets. Despite its central role in coordinating data across globally distributed storage sites, Rucio's command line interface (CLI) presents a steep learning curve, and makes it difficult for scientists to navigate through. To solve this issue, a containerized Model Context Protocol (MCP) [2] server was built that connects Large Language Models directly to Rucio, allowing AI agents to handle data tasks by using simple, natural language rather than memorized terminal commands. The core engineering focus of this project was moving the server away from slow terminal commands that require text parsing and replacing them with a native Python Client API toolset and a planned REST API framework. Moving to the Python API handles data operations directly in memory, which helps clear up formatting errors, provides the AI with clean, structured JSON data and speeds up tool execution. To prove that the system actually works, a benchmarking pipeline was also built with various questions to test the AI across four different model configurations. The questions included finding data scopes, tracking down specific datasets, and checking replication rules. Through benchmarking, early runs showed that with raw terminal text, the model would get confused and stuck, whereas switching to the Python API to feed the AI clean, structured data yielded massive improvement. By creating an intelligent and autonomous bridge to a storage network, this project shows how AI can be implemented in scientific data management, which ultimately helps scientists at Fermilab spend less time sorting through data and more time focusing on their experiments and analysis.

Akella, Kashyap [William Rainey Harper Coll.]↗
DOE OSTI2021

Three-dimensional Core-collapse Supernova Simulations with 160 Isotopic Species Evolved to Shock Breakout

We present three-dimensional simulations of core-collapse supernovae using the FLASH code that follow the progression of the explosion to the stellar surface, starting from neutrino radiation hydrodynamic simulations of the neutrino-driven phase performed with the Chimera code. We consider a 9.6 M ⊙ zero-metallicity progenitor starting from both 2D and 3D Chimera models and a 10 M ⊙ solar-metallicity progenitor starting from a 2D Chimera model, all simulated until shock breakout in 3D while tracking 160 nuclear species. The relative velocity difference between the supernova shock and the metal-rich Rayleigh–Taylor (R-T) "bullets" determines how the metal-rich ejecta evolves as it propagates through the density profile of the progenitor and dictates the final morphology of the explosion. We find maximum 56 Ni velocities of ~1950 and ~1750 km s -1 at shock breakout from 2D and 3D 9.6 M ⊙ Chimera models, respectively, due to the bullets' ability to penetrate the He/H shell. When mapping from 2D, we find that the development of higher-velocity structures is suppressed when the 2D Chimera model and 3D FLASH model meshes are aligned. The development of faster-growing spherical-bubble structures, as opposed to the slower-growing toroidal structure imposed by axisymmetry, allows for interaction of the bullets with the shock and seeds further R-T instabilities at the He/H interface. We see similar effects in the 10 M ⊙ model, which achieves maximum 56 Ni velocities of ~2500 km s -1 at shock breakout.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

CORAL: A framework for rigorous self-validated data modeling and integrative, reproducible data analysis

Abstract Background Many organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks. Findings We present the Contextual Ontology-based Repository Analysis Library (CORAL), a platform that greatly facilitates adherence to all 4 of the FAIR principles, including the especially difficult challenge of making heterogeneous datasets Interoperable and Reusable across all parts of a large, long-lasting organization. To achieve this, CORAL's data model requires that data generators extensively document the context for all data, and our tools maintain that context throughout the entire analysis pipeline. CORAL also features a web interface for data generators to upload and explore data, as well as a Jupyter notebook interface for data analysts, both backed by a common API. Conclusions CORAL enables organizations to build FAIR data types on the fly as they are needed, avoiding the expense of bespoke data modeling. CORAL provides a uniquely powerful platform to enable integrative cross-dataset analyses, generating deeper insights than are possible using traditional analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Depth-Resolved X-Ray Nanoimaging of Coherent and Incoherent Energy Transport in Silicon Carbide

Understanding lattice dynamics is crucial for optimizing the process of creating functional structures, such as laser writing of color-center defects. However, existing structural probes have difficulty measuring structural dynamics with submicrometer depth sensitivity. Here, in this study, a depth-resolved ultrafast X-ray nanodiffraction technique is developed to track the lattice dynamics of silicon carbide (SiC) in three dimensions. Upon laser excitation of an aluminum layer that acts as a heat and strain transducer, a specular Bragg peak of SiC shows an overall increase in the X-ray diffraction intensity rather than a peak shift. The relaxation dynamics of the increased intensity are significantly different when probed on and off the Bragg peak. The fast subnanosecond relaxation probed at the maximum of the Bragg peak is a result of the propagation of a coherent strain wave along the depth direction, while a slow relaxation probed at the wings of the Bragg peak reflects a localized incoherent lattice heating. To further visualize these processes, spatiotemporal maps were obtained by scanning the relative position and delay between the laser pump and X-ray probe beams, which capture the propagation of the strain wave, as well as a stationary structural distortion close to the aluminum/SiC interface. These depth-resolved structural measurements disentangle energy dissipation mechanisms in laser-excited SiC, and they open opportunities for finer control of, for example, the formation of optically addressable defect complexes central to quantum information applications.

X-ray nanodiffraction↗
DOE OSTI2023

Deliver Signal Phase and Timing (SPAT) for Energy Optimization of Vehicle Cohort Via Cloud-Computing and LTE Communications

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques. An emulation-based algorithm is applied to predict the traffic signal state changes to provide adequate prediction horizon (e.g., at minimum 2 minutes) for the cohort energy optimization. In fact, the same connectivity and SPAT delivery methodology has been applied to traffic signalized intersections nationwide in the United States upon public agency approvals for access to their firewalled traffic control network and signal control systems or directly to individual controllers. This methodology proves its effectiveness and potential for rapid growth of such SPAT deliveries at mass production scale without needing infrastructure hardware retrofit or excessive communication means. To support the energy optimization of light and heavy-duty vehicle cohorts of mixed automation and propulsion systems (EV, ICE and hybrid), the connection and SPAT deliveries at two sites were completed, including public roads in Washtenaw County, Michigan and closed track test sites at American Center for Mobility (ACM) in Ypsilanti, Michigan. However, only closed test track results at ACM will be presented in this paper. A neuroevolution based optimizer is developed and implemented to control the speed of a vehicle cohort with different propulsion systems and automation levels. Closed track tests showed significant energy savings of the cohort operation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Waste Management Project Success - Regulatory Assurance Systems - 20118

Waste management (WM) and remediation projects are essential within a restorative environmental culture. Despite years of experience, challenges and obstacles associated with efficient and effective WM project execution remain. Although some obstacles are project specific, a common challenge is navigating the regulatory landscape from planning through execution, particularly with first of a kind (FOAK) and first in a while (FIAW) projects. The absence of a comprehensive regulatory assurance strategy places significant hurdles in the path of project success. To clear a path for the successful execution of increasingly complex WM projects, this paper focuses on development of a comprehensive regulatory assurance strategy and implementation plan that effectively engages stakeholders, agencies, and performers to produce project plans that fully and cost effectively integrate applicable regulatory requirements. The most reliable way to align regulatory processes and decisions needed for mission success is through a regulatory assurance system. This system establishes a healthy interface with regulatory decision makers, to work in a collaborative manner, to create a common vision for regulatory decisions on an agreed upon schedule. A regulatory assurance system consists of several elements. Although the mission may vary from cleanup to site closure to nuclear component production, the elements of a regulatory assurance system remain essentially constant and must include: 1) identifying a common vision or end state, 2) developing a long-term, integrated strategy and schedule, 3) establishing a regulatory partnering team consisting of key decision-makers, 4) regular and frequent communication with decision-makers, 5) ensuring consistent surveillance for early identification of issues and changes that may impact the project, 6) quick resolution of emerging issues to prevent schedule impact, 7) identifying core compliance functions, 8) periodically assessing progress of the project as it relates to regulatory assurance and, 9) providing constructive feedback to improve the process. A regulatory assurance system provides a living, multi-faceted approach to planning, visioning, communicating and tracking to avoid surprises and ensure smooth and timely progress to the project. The overall success measures will be whether the system produces common sense regulatory decisions supporting the vision on time without appeal. Effective regulatory frameworks rarely happen on their own. Balanced, common-sense regulatory decisions stem from teams that are trained to work together to achieve shared goals. In this paper, particular attention is placed on the importance of starting with a shared vision for a regulatory assurance and execution strategy that leverages experience to establish optimal approaches. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

How Water Attacks MXene

Two-dimensional (2D) transition metal carbides and nitrides (MXenes) have shown outstanding performances in electrochemical energy storage and many other applications. However, the stability of MXene remains a concern, especially its quick degradation in aqueous solutions under ambient conditions. Here, we report on the water/Ti 3 C 2 O 2 -MXene interfacial chemistry from first-principles molecular dynamics simulations at room temperature. Surprisingly, we find that the water molecules can attack the basal plane of Ti 3 C 2 O 2 and pull the surface Ti atoms out, thereby reconstructing the surface. Further, by tracking close encounters of water molecules and surface Ti atoms on the basal plane of Ti 3 C 2 O 2 , we show that the attack is initiated by the chemisorption of a water molecule on a surface Ti atom, followed by the breaking of Ti–C bonds and deprotonation of the water molecule, leading to the formation of Ti–OH on the Ti 3 C 2 O 2 surface and a hydronium ion in the aqueous phase. Our finding highlights the susceptibility of Ti 3 C 2 O 2 MXene to water attack, supporting recent experimental observations. Furthermore, we demonstrate that preventing close encounters of water molecules and the surface Ti atoms is key to the stability of the basal plane and can be realized by negatively charging the surface (thereby reorienting the O atoms of water away from the surface) or converting the surface O to -OH groups (thereby shifting the water layer further away from the surface). Our insights and approach highlight the importance of the reactivity of water when interfacing with 2D materials such as MXenes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Phase Transformations among TiO2 Polymorphs

Polymorphs widely exist in nature and synthetic systems and are well known to determine material properties. Understanding phase transformation mechanisms among polymorphs enables the design of structures and tuning of phases to tailor material properties. However, current understanding is limited due to the lack of direct observations that track the processes and the structural evolution is not known at atomic scale. Here, integrating (semi) in situ transmission electron microscopy and density functional theory, we report atomic structural evolutions of phase transformation from anatase (A) to rutile (R), brookite (B), R-phase, and TiO. Besides the consistent paths with previous reports, we discover several unreported paths, including a [001] direction and (020) plane of anatase to [100]A and (011)R of rutile, respectively, ( , ) and , . Density functional theory analysis elucidates atomic structural evolution during the processes and over 16% of Ti-O bonds break and reform during the processes with energy barriers of ~0.7-1.0 eV per TiO2 formula unit. Under electron-beam irradiation, anatase particles transform into TiO2-R phase or TiO at high or room temperature, respectively. We also reveal the anisotropic nature of electron-beam effect, which is seldom discussed: dependence of crystallographic orientation with respect to electron-beam irradiation direction. Understanding the atomic structural evolution sheds light on interpreting and controlling TiO2 polymorphs and interface structures for various applications. The revealed electron-beam effects in our work provide guidance for in situ transmission electron microscopy studies.

Song, Miao↗
DOE OSTI2022

Procedure Parsing: A Method for Parsing Handwritten Documents into Computer-Based Procedures

The nuclear industry is heavily procedure driven, where almost everything has a step-by-step instruction that is expected to be followed in detail. Historically, these procedures were printed on paper copies. Recently, the industry transitioned towards electronic copies (i.e., PDFs on tablets). One major drive for this transition is the introduction of human error and loss of situation awareness when using paper copies. However, electronic copies of documents inherently have the same error traps as their paper cousins. Therefore, there is an increased interest in a way to utilize the information in the step-by-step guidance, but to present it in a dynamic manner that guides the user and adapts to any encountered conditions. Researchers at Idaho National Laboratory propose a flexible, automated method based on document parsing and augmented by natural language processing (NLP) techniques, to address these shortcomings and capitalize on these recent advancements in machine learning. The proposed method provides a cost-effective solution for computer-assisted procedure parsing of hand-written control room procedures, originally authored in Word or PDF formats, into instructions that can be displayed as computer-based procedures (CBP) in a modern graphical user interface. The researchers devised, implemented and demonstrated the Operating Procedure Extender for Novel Systems (OPENS) method in 2020. The key to OPENS is to map the original procedure text into a context-free grammar, tying content to equipment, locations, and other steps, actions, etc. This formal grammar is then used to isolate and define keywords and actions verbs, such as “measure” or “evaluate” and tie them to specific equipment referenced within that step or located in other steps, substeps, actions, subactions and tables throughout the procedure. OPENS generates an abstract syntax tree from the document which it uses to store a copy of this information in the open-standard, machine-readable and human-readable file formats XML and JSON. The XML is useful to preserve the relational aspects of the procedure for referencing tables and branching information so the user can be directed to the next appropriate active step based on the values entered for that step and previous steps. The JSON is useful for storing and exchanging data objects used to track responses to previous steps and state changes in simulated environments. In future iterations, these formats can also be used for storing more detailed information about input during plant operation or simulation. The techniques the researcher developed could further be improved by integration of recent advancements in machine learning. NLP methods could standardize documents, correct for grammatical error, and provide automated semantic validation. The researcher expects that self-supervised techniques applied to collections of natural language instructions could strengthen the model with broader context. All these methods together give us a practical way to automatically extract protocols from documents and user interactions, empowering researchers, procedure writers and nuclear operators while moving the industry forward.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗
DOE OSTI2022

Photo-Induced Charge Transfer of Fullerene and Non-Fullerene Conjugated Polymer Blends via Ab Initio Excited-State Dynamics

Organic conjugated polymers (CPs) are promising candidates for organic photovoltaic (OPV) devices due to their unique tunable mechanical and optoelectronic performance. Over the last decade, optoelectronic properties of narrow band gap CPs as a blend with acceptor units are largely optimized, which leads to noticeable progress in OPV technology. However, their power conversion efficiency is still lower than their organic counterparts (i.e., silicon), limiting their practical usage. In this study, we employ ab initio molecular dynamics to explore photo-induced charge transfer (CT) of the diketopyrrolopyrrole-based polymer as a blend with non-fullerene (i.e., ITIC) and fullerene (i.e., PCBM) acceptor units. The results of charge carrier dynamics induced by selected photoexcitation show that hole density redistribution in space is much faster than electron relaxation. We track the relaxation rates of charge carriers over time, where the derivative of the difference between the rate of electron and hole implies the current density at zero voltage. Furthermore, this can be utilized to characterize the CT performance of CPs blended with different acceptor units. Relaxation rate results indicate that CP blend with ITIC promises a better PV performance, illustrating that the current computational approach opens the door to determine bulk heterojunctions’ electronic performance for OPV devices and narrowing down the list of potential donor–acceptor candidates.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗
DOE OSTI2024

Understanding and modeling current and future coastal wetland methane dynamics (Final Report)

The coastal terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system that plays a critical role in biogeochemical cycling. Due to its dynamic nature, the processes that regulate decomposition and methane (CH 4 ) emissions are of greater significance at the TAI than in upland systems. Despite this, we have limited mechanistic understanding of how climate stressors interact to regulate the electron acceptors and donors that determine decomposition pathways within TAIs, including the generation of hot spots and hot moments. Accurately modeling these processes is critical for incorporating the coastal TAI into Earth systems models, such as DOE’s E3SM. With previous DOE support, we adapted an aerobic terrestrial representation of decomposition using PFLOTRAN, a reactive flow and transport model, and added anerobic decomposition pathways, salinity, and oxygen (O 2 ) that fluctuates independently of water table level. However, because this model (PFLOTRAN TAI ) is based on decomposition rates and organic matter carbon to nitrogen ratios from terrestrial systems, its performance in TAI systems is currently limited by the lack of empirical data to properly parameterize variables. In addition, while PFLOTRAN TAI can simulate movement of O 2 into sediments, it is not currently capable of tracking the movement of CH 4 gas through plant tissues due to both current model structure and lack of available data. Our overall objective of the project was the increase our mechanistic understanding of CH 4 dynamics in response to environmental change, such that we can improve the representation of these dynamics in PFLOTRAN. We installed automated flux chambers in a new field-scale active soil warming experiment and set up marsh organs (mesocosms) to test effects of warming, flooding, and salinity. This resulted in a new dataset consisting of chamber-level CH 4 flux measurements across multiple sites, ecological conditions, and timeframes, as well as corresponding measurements on porewater chemistry, soil carbon quality, plant biomass, and redox reaction rates. Using these data, we improved PFLOTRAN TAI to more accurately model CH 4 dynamics and successfully tested our hypotheses. This grant contributed to the professional development of 3 postdocs, 4 undergraduate interns, 4 teacher interns, 17 technicians, and 15 participatory scientists. The automated chamber technology designed for this grant has also been shared with multiple new projects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Methods to Observe Tribological Failures in Self-Mated Steel Contacts

Scuffing, a type of wear found in highly stressed or poorly lubricated contacts, is characterized by a rapid increase in friction and severe plastic deformation of the near-surface material. Scuffing has proven difficult to study because it initiates unpredictably, progresses rapidly, and typically develops within an inaccessible contact interface. Although there have been successful in-situ studies of scuffing in real-time, the transparent counter body needed for these studies changes the interactions between the surfaces and the lubricant, which affects the scuffing process in unknown ways. This paper describes the development of X-ray-compatible tribometry to study the scuffing of self-mated steels in-situ and in real-time. The method uses a crossed cylinders configuration with a thin (500 μm thick) stationary component and a small (≈200 μm) contact width to maximize X-ray interactions with atoms within the stress field generated by the contact. The resulting instrument and method are used to benchmark the scuffing response of self-mated 52,100 steel under tribologically challenging ‘oil-off’ lubrication conditions. The results demonstrate reliable scuffing in this configuration despite the relatively small contact areas and loads used. Following scuffing, gross plastic deformation was observed on both surfaces along with significant subsurface grain refinement and flow only on the stationary surface, which experienced constant contact. Interestingly, high friction initiated at specific locations of the migratory surface, which experienced intermittent contact, and then propagated across the track over time, suggesting that local conditions of the migratory surface dominated friction leading into the failure event.

36 MATERIALS SCIENCE↗