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DOE OSTI2024

Iron( IV ) alkyl complexes: electronic structure contributions to Fe–C bond homolysis and migration reactions that form N–C bonds from N 2

High-valent iron alkyl complexes are rare, as they are prone to Fe–C bond homolysis. Here, we describe an unusual way to access formally iron(IV) alkyl complexes through double silylation of iron(I) alkyl dinitrogen complexes to form an NNSi 2 group. Spectroscopically validated computations show that the disilylehydrazido(2−) ligand stabilizes the formal iron(IV) oxidation state through a strongly covalent Fe–N π-interaction, in which one π-bond fits an “inverted field” description. This means that the two bonding electrons are localized more on the metal than the ligand, and thus an iron(II) resonance structure is a significant contributor, similar to the previously-reported phenyl analogue. However, in contrast to the phenyl complex which has an S = 1 ground state, the ground state of the alkyl complex is S = 2, which places one electron in the π* orbital, leading to longer and weaker Fe–N bonds. The reactivity of these hydrazido(2−) complexes is dependent on the steric and electronic properties of the specific alkyl group. When the alkyl group is the bulky trimethylsilylmethyl, the formally iron(IV) species is stable at room temperature and no migration of the alkyl ligand is observed. However, the analogous complex with the smaller methyl ligand does indeed undergo migration of the carbon-based ligand to the NNSi 2 group to form a new N–C bond. This migration is followed by isomerization of the hydrazido ligand, and the product exists as two isomers that have distinct η 1 and η 2 binding of the hydrazido group. Lastly, when the alkyl group is benzyl, the Fe–C bond homolyzes to give a three-coordinate hydrazido(2−) complex which is likely due to the greater stability of a benzyl radical compared to that for methyl or trimethylsilylmethyl. These studies demonstrate the availability of a hydrocarbyl migration pathway at formally iron(IV) centers to form new N–C bonds directly to N 2 , though product selectivity is highly dependent on the identity of the migrating group.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Hawai‘i Play Fairway (Final Report)

Most of Hawai'i's geothermal resources are blind—their manifestations, such as hot springs and steam vents, do not appear on the ground surface because the heated water flows far below. With the exception of $K\bar{i}lauea East Rift Zone$, in most areas of Hawai'i, high lateral permeability in the first kilometer below ground surface prevents surface thermal features from developing. As a methodology for discovering these blind resources, Play Fairway Analysis (PFA) involves finding potential locations of blind hydrothermal systems and describing potential geothermal sources in rift-zone settings. Using the PFA to find Hawai'i's geothermal resources, the University of Hawai'i (UH) conducted the Hawai‘i Play Fairway Project, Hawai'i's first statewide geothermal resource assessment since 1985. Sponsored by the U.S. Department of Energy, the Hawai'i Play Fairway Project provided an updated resource assessment, a roadmap for additional exploration activities, and the identification of areas for further exploration. Benefitting from UH's core competency in earth sciences and experienced geothermal researchers, the project comprised three phases. During the first phase, the team identified, compiled, and ranked existing geologic, groundwater, and geophysical datasets relevant to subsurface heat, fluid and permeability. Using a Bayesian statistical approach, the team developed a statistical methodology to integrate these data into a resource probability map. The team evaluated the confidence in the probability value and considered development viability of areas with geothermal resources. With these analyses, the team identified 10 locations in the Hawaiian Islands for exploration activities. For the second phase, the team collected new groundwater data in 10 locations across the state and new geophysical data on $L\bar{a}na‘i, Maui$, and central Hawai'i Island and modeled topographically induced stress to better characterize subsurface permeability. Analyzing the subsurface stresses, the team evaluated the potential for fracture-induced permeability. The team inverted the MT and gravity data to produce 3D models of resistivity and density, respectively, on $L\bar{a}na‘i$, across $Haleakal\bar{a}'s$ SW rift (Maui), and surrounding Mauna Kea (Hawai‘i Island). The team developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The team incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. Through combining data from the first and second phases, the team determined locations for further exploration during the third phase. For MT and gravity surveys, the team recommended $Kaua'i's$ $L\bar{i}hu'e$ $Basin$, the east rift of $Maui's$ $Haleakal\bar{a}$ volcano, and the southwest rift of Hawai'i Island's Mauna Loa volcano. The MT and gravity surveys aimed to enable improved confidence in the resource potential in these locations. For drilling deep groundwater well(s), the team recommended Southeast Mauna Kea and $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$. During the third phase, further exploration involved drilling a groundwater well in $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$ and performing more geophysical surveys. We deepened an existing water well proximal to our target area on $L\bar{a}na'i$ due to funding constraints that precluded us from spudding a new well that would exceed 1km depth. Drilling was preceded by a number of substantial elements including: writing an Environmental Assessment and the subsequent legal process, performance of deviation logging, lowering a camera down the well, coordinating site preparation with $P\bar{u}lama$ $L\bar{a}na'i$, shipping the UH-owned rig interisland, procuring supplies, and leading 3 community meetings on $L\bar{a}na'i$. Drilling occurred 24/7 the entire month of June 2019 over which time $L\bar{a}na'i$ $Well$ 10 was deepened from 427 m to 1057 m, with continuous core collected. We measured a roughly linear temperature gradient averaging 42°C/km and a maximum bottom hole temperature of 66°C. This gradient is more than twice the background for Hawai'i and within a range of gradients measured in this depth range for some exploration wells within KERZ. We consider these results encouraging for $L\bar{a}na'i's$ resource potential and recommend following with a slim hole within $L\bar{a}na'i's$ caldera (our target zone) to ~ 2 km. Further, the positive implications such results have for the island of O‘ahu are substantial - the shield stage of O'ahu's volcanoes ended 1-2 My earlier. However, O'ahu uses more electricity than the rest of the islands combined, and the utility recently called for 500-700MW of firm, dispatchable renewable electricity on O'ahu by 2033. In Phase 3, we also collected limited new encouraging groundwater data, and updated our thoughts on the probabilities of fluid and permeability at resource depths (Pr F = 1; Pr P = mostly unconstrained). Ultimately, we advocate for using our final probability of heat, and confidence in this probability, to drive the next phase of exploration. We contend further development of geothermal in Hawai‘i will enable the state to achieve its 100% renewable policy objective and Hawai'i to transition off of fossil fuels through geothermal discovery and development. The project not only produced a large amount of data and expanded the existing knowledge of Hawai'i's geothermal resources, but also produced publications, theses, presentations, core photos, datasets, media reports, television interviews, community events, and a blog. Students and new professionals benefitted from the project's hands-on research experiences and educational opportunities and earned awards and recognition.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Numerical Codes for the DESC-LSST Analysis Pipeline: Core Cosmology Library Standard Modules and Beyond wCDM Modules (Final Technical Report)

The overall objective of the project is to investigate and develop specific software modules and analysis components for the software pipeline of LSST Dark Energy Science Collaboration (DESC). Following the key projects of DESC Science Roadmap (SRM), we will write and test computer codes for the Core Cosmology Library (CCL) in order to complete its modules, functionalities, and interface to work with the analysis pipelines from the five science probes of DESC (parts of SRM deliverables CX4.2TJP, CX6.2CS). We will also code modules for CCL to test models beyond w-Cold-Dark-Matter (wCDM) and modification to gravity (MG). Interfaces for MG models will also be developed for the TJPCOSMO software which is the main pipeline of the Theory and Joint Probe (TJP) working group (deliverable TJP2.3). In order to use the full power of LSST data to constrain MG models, we will also work on constraints from nonlinear regime by running and analyzing MG N-Body simulations using a Parameterized-Post-Friedmann framework into the Gadget-2 simulation package (deliverable TJP2.2). Preliminary results for the simulations were obtained in the past. In collaboration with other DESC groups, we plan to make these simulations feedable to cosmic emulators that are practical for likelihood analyzes (deliverable TJP2.2, parts of CX6.2CS). We will also modify and integrate our current codes for consistency tests between data sets and probes into the pipeline (parts of deliverables CX8.2TJP, TJP2.3). We understand that other groups will contribute to some of these objectives but our team will focus and collaborate with others on the particular part of testing MG and models beyond wCDM and refine the DESC pipeline for this purpose. PI has been coordinating his work with the TJP and CS working groups and the DESC management team. PI is a full member of DESC since June 2013. He and his students have been contributing to LSST-DESC activities and work including TJP telecons, collaboration meetings, hack-weeks, and workshops. PI chaired or co-chaired sessions at collaboration meetings and hack-weeks about testing gravity and models beyond wCDM using LSST. He is coordinating the TJP2 projects for testing models beyond wCDM including the writing of DESC-research-note, development of code for pipeline, and N-Body simulations for MG and beyond wCDM models testable with LSST analyses. As stressed in the DESC white paper, SRM, and P5 report, one of the important questions in understanding cosmic acceleration and dark energy is to be able to distinguish whether the acceleration is due to a dark energy component in the universe or a modification to gravity. Answering these questions will have a significant impact on the question of cosmic acceleration and dark energy. The methods that we will use include analytical work, numerical code, and N-Body simulations. A first approach that that we will use consists of using growth rate parameters that enter the perturbed dynamics equations. These parameters take distinctive values for distinct gravity theories and have potential to distinguish between Dark Energy and Modified Gravity. The second method is to look for inconsistencies in Dark Energy parameter spaces using specific combinations of cosmological data sets. Our investigation addresses the Dark Energy problem that is relevant to the mission of the HEP program to understand how our universe works at its most fundamental level. It will allow us to make progress on the HEP mission to explore the nature of Dark Energy and the basic nature of space and time using future surveys such as LSST. The investigation supports the DOE HEP program Cosmic Frontier as it will contribute to the study and understanding of dark energy and fundamental properties of the universe. The investigation contributes directly to LSST-DESC key projects and their deliverables as described in the Science Road-map document to build analysis pipeline and to test dark energy and beyond wCDM models using LSST.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A Theory of Ultrafast Charge Transfer Relaxation with Non-Innocent Solvent Molecules

In this work we revisit the photodynamics of tetracyanoethylene-hexamethylbenzene (TCNE- HMB), the molecular complex studied by Hochstrasser et al. [J. Chem. Phys. 100, 4797–4810, 1994] that has long challenged the applicability of Marcus’s theory of elec- tron transfer for predicting photochemical reactions. Using a novel black-box electronic structure algorithm (time-dependent density functional theory with one double, TD- DFT-1D) to efficiently run molecular dynamics that can treat charge recombination, we run ab initio surface hopping molecular dynamics and confirm that, for a polar solvent, charge recombination rates can be incredibly fast (indeed faster than the sol- vent relaxation time); for non-polar solvents, the rate is much slower. We demonstrate that, although Marcus theory cannot be directly applied, these nonequilibrium (and sometimes incredibly fast) photoexcited dynamics can be effectively explained within a two-state model without any evidence of a transition through a conical intersection. Most importantly, for this paradigmatic model system, we are able to identify two nuclear coordinates of interest (rather than the single coordinate predicted by Marcus or a full set of internal quantum modes studied by Bixon and Jortner): the solvent relaxation in the first shell (that strongly modulates the energies of the charge trans- fer state and differentiates time scales for relaxation) and a nuclear displacement in the TCNE-HMB complex arising from a handful of vibrations that induces non-Born Oppenheimer motion and eventually facilitates an abrupt electronic transition to the ground state. Altogether, these findings suggest a tractable generalization of Marcus theory for future simulations of photochemistry with non-innocent solvent environ- ments in the spirit of a Hamiltonian suggested by Stuchebrukhov (J. Chem. Phys. 107, 3821, 1997).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Heterobimetallic multi-site concerted proton electron transfer (MS-CPET) promotes coordination-induced O–H bond weakening

Coordination-induced bond weakening of X–H bonds (X = O, N, C) has been observed in a number of low-valent transition metal compounds. However, the impact of an appended electron reservoir on the bond dissociation free energy of the O–H bond (BDFE O–H ) of a substrate bound to a d 0 metal is poorly understood. To gain insight into the ability of separated deprotonation and oxidation sites to decrease the BDFE O–H during proton-coupled electron transfer (PCET) reactions, a bimetallic system in which the sites of proton and electron loss are two distinct metal sites is described. Herein, the interconversion of tris(phosphinoamide) Zr/Co complexes HO–Zr(MesNP i Pr 2 ) 3 CoCN t Bu and O$≡$Zr(MesNP i Pr 2 ) 3 CoCN t Bu via hydrogen atom addition/abstraction was studied. Since the Zr center remains in the d 0 Zr IV state throughout these transformations, the electron transfer process is mediated by the appended redox-active Co 0/I center. A series of open-circuit potential (OCP) measurements on the HO–Zr(MesNP i Pr 2 ) 3 CoCN t Bu and O$≡$Zr(MesNP i Pr 2 ) 3 CoCN t Bu complexes was performed, from which the BDFE O–H was found to be 64 ± 1 kcal mol −1 . The BDFE O–H value was further verified through a series of stoichiometric H atom transfer reactions, stoichiometric protonation/deprotonation reactions, and computational studies.

Chemistry↗

DOE OSTI2022

Exploring mechanistic routes for light alkane oxidation with an iron–triazolate metal–organic framework

In this work, we computationally explore the formation and subsequent reactivity of various iron-oxo species in the iron–triazolate framework Fe 2 (m-OH) 2 (bbta) (H2bbta = 1H,5H-benzo(1,2-d:4,5- d0)bistriazole) for the catalytic activation of strong C–H bonds. With the direct conversion of methane to methanol as the probe reaction of interest, we use density functional theory (DFT) calculations to evaluate multiple mechanistic pathways in the presence of either N 2 O or H 2 O 2 oxidants. These calculations reveal that a wide range of transition metal-oxo sites – both terminal and bridging – are plausible in this family of metal–organic frameworks, making it a unique platform for comparing the electronic structure and reactivity of different proposed active site motifs. Based on the DFT calculations, we predict that Fe 2 (m-OH)2(bbta) would exhibit a relatively low barrier for N 2 O activation and energetically favorable formation of an [Fe(O)] 2+ species that is capable of oxidizing C–H bonds. In contrast, the use of H 2 O 2 as the oxidant is predicted to yield an assortment of bridging iron-oxo sites that are less reactive. We also find that abstracting oxo ligands can exhibit a complex mixture of both positive and negative spin density, which may have broader implications for relating the degree of radical character to catalytic activity. In general, we consider the coordinatively unsaturated iron sites to be promising for oxidation catalysis, and we provide several recommendations on how to further tune the catalytic properties of this family of metal–triazolate frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Eliminating Imaginary Vibrational Frequencies in Quantum-Chemical Cluster Models of Enzymatic Active Sites

In constructing finite models of enzyme active sites for quantum-chemical calculations, atoms at the periphery of the model must be constrained to stop unphysical rearrangements during geometry relaxation. A simple fixed-atom or “coordinate-lock” approach is commonly employed but leads to undesirable artifacts in the form of small imaginary frequencies. These preclude evaluation of finite-temperature free-energy corrections, limiting thermochemical calculations to enthalpies only. Full-dimensional vibrational frequency calculations are possible by replacing the fixed-atom constraints with harmonic confining potentials. Here, we compare that approach to an alternative strategy in which fixed-atom contributions to the Hessian are simply omitted. While the latter strategy does eliminate imaginary frequencies, it tends to underestimate both the zero-point energy and the vibrational entropy while introducing artificial rigidity. Harmonic confining potentials eliminate imaginary frequencies and provide a flexible means to construct active-site models that can be used in unconstrained geometry relaxations, affording better convergence of reaction energies and barrier heights with respect to the model size, as compared to models with fixed-atom constraints.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Virtual node graph neural network for full phonon prediction

Understanding the structure-property relationship is crucial for designing materials with desired properties. The past few years have witnessed remarkable progress in machine-learning methods for this connection. However, substantial challenges remain, including the generalizability of models and prediction of properties with materials-dependent output dimensions. Here we present the virtual node graph neural network to address the challenges. By developing three virtual node approaches, we achieve Γ-phonon spectra and full phonon dispersion prediction from atomic coordinates. We show that, compared with the machine-learning interatomic potentials, our approach achieves orders-of-magnitude-higher efficiency with comparable to better accuracy. This allows us to generate databases for Γ-phonon containing over 146,000 materials and phonon band structures of zeolites. Additionally, our work provides an avenue for rapid and high-quality prediction of phonon band structures enabling materials design with desired phonon properties. The virtual node method also provides a generic method for machine-learning design with a high level of flexibility. In this study, the authors present a virtual node graph neural network to enable the prediction of material properties with variable output dimensions. This method offers fast and accurate predictions of phonon band structures in complex solids.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors

Abstract Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.

Computer Science↗

DOE OSTI2023

Toggling Stereochemical Activity through Interstitial Positioning of Cations between 2D V 2 O 5 Double Layers

The 5/6s 2 lone-pair electrons of p-block cations in their lower oxidation states are a versatile electronic and geometric structure motif that can underpin lattice anharmonicity and often engender electronic and structural instabilities that underpin the function of active elements in nonlinear optics, thermochromics, thermoelectrics, neuromorphic computing, and photocatalysis. In contrast to periodic solids where lone-pair-bearing cations are part of the structural framework, installing lone-pair-bearing cations in the interstitial sites of intercalation hosts provides a means of a systematically modulating electronic structure through the choice of the group and the period of the inserted cation while preserving the overall framework connectivity. The extent of stereochemical activity and the energy positioning of lone-pair-derived mid-gap states depend on the cation identity, stoichiometry, and strength of anion hybridization. V 2 O 5 polymorphs are versatile insertion hosts that can accommodate a broad range of s-, p-, and d-block cations. However, the insertion of lone-pair-bearing cations remains largely underexplored. In this article, we examine the implications of varying the 6s 2 cations situated in interlayer sites between condensed [V 4 O 10 ] n double layers. Systematic modulations of lattice distortions, electronic structure, and magnetic ordering are observed with increasing strength of stereochemical activity from group 12 to group 14 cations. We compare and contrast p-block-layered M x V 2 O 5 (M = Hg, Tl, and Pb) compounds and map the significance of local off-centering arising from the stereochemical activity of lone-pair cations to the emergence of filled antibonding lone-pair 6s 2 –O 2p-hybridized mid-gap states mediated by second-order Jahn–Teller distortions. Crystallographic studies of cation coordination environments and the resulting modulation of V–V interactions have been used in conjunction with variable-energy hard X-ray photoelectron spectroscopy measurements, first-principles electronic structure calculations, and crystal orbital Hamilton population analyses to decipher the origins of stereochemical activity. Magnetic susceptibility measurements reveal antiferromagnetic signatures for all the three compounds. However, the differences in V–V interactions significantly affect the energy balance of the superexchange interactions, resulting in an ordering temperature of 160 and 260 K for Hg 0.5 V 2 O 5 and δ-Tl 0.5 V 2 O 5 , respectively, as compared to 7 K for δ-Pb 0.5 V 2 O 5 . In δ-Pb 0.5 V 2 O 5 , the strong stereochemical activity of electron lone pairs and the resulting electrostatic repulsions enforce superlattice ordering, which strongly modifies the electronic localization patterns along the [V 4 O 10 ] slabs, resulting in disrupted magnetic ordering and an anomalously low ordering temperature. The results demonstrate a versatile strategy for toggling the stereochemical activity of electron lone pairs to modify the electronic structure near the Fermi level and to mediate superexchange interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

CMM Sequential Analysis Program

This report documents a design agency (DA) method to evaluate coordinate measuring machine (CMM) data by constructing an algorithm that is equivalent to the production agency (PA) algorithm for processing the raw CMM data. Several refinements of the CMM analyses were implemented at both the PA and the DA to process inherent limitations of the raw data, such as the absence of measurements at the exact ends of the connector-adapter assembly (CAA) and the recovery from these limitations through (worst-case) adjustments to the the positional errors. Also, inherent errors of the CMM measurements were accommodated by introducing a guard band, which effectively lowered the tolerance so that the CMM code could not pass bad parts. The DA and the PA showed remarkable agreement in all areas of analysis. The ultimate comparison is shown in Figures 13a and 13b, where the effect of using a guard band and end adjustments to the CMM measurements were clearly shown.

42 ENGINEERING↗

DOE OSTI2020

MPI Session: External Network Transport Implementation (V.1.0)

The MPI Sessions extensions to the MPI standard have been accepted by the MPI Forum and will be included in the upcoming MPI 4 version of the standard. MPI Sessions has the potential to address several limitations of MPI’s current specification: MPI cannot be initialized within an MPI process from different application components without a priori knowledge or coordination; MPI cannot be initialized more than once; and, MPI cannot be reinitialized after MPI finalization. MPI Sessions also offers the possibility for more flexible ways for individual components of an application to express the capabilities they require from MPI at a finer granularity than is presently possible. A prototype of MPI Sessions, based on the Open MPI implementation of the MPI standard, was developed to facilitate acceptance of the Sessions proposal by the Forum. The initial implementation had some limitations, one of the more significant ones being that it was limited in its ability to fully exploit modern network APIs such as OFI libfabric and OpenUCX and underlying network hardware. This report presents enhancements to the prototype implementation of MPI Sessions that removes this restriction for the networks to be used in the next generation of DOE exa–scale systems. Open MPI was used as the implementation vehicle, but results here are also relevant to other middleware stacks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

NEXT Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR Phase I & II)

The Ohio State University’s ARPA-E NEXTCAR project was a multi-phase, multi-year research, development, and demonstration program focused on improving the energy efficiency of connected and automated vehicles (CAVs). The team developed and validated advanced vehicle motion and powertrain control algorithms that coordinate propulsion and automation systems to optimize energy use. Key technologies included Dynamic Skip Fire engine control, predictive eco-driving functions such as Eco-Approach and Departure (Eco-AND) and Eco-Adaptive Cruise Control (Eco-ACC), and powertrain-agnostic optimization frameworks for hybrid, plug-in hybrid, and battery electric vehicles. The project successfully demonstrated up to 30% energy-efficiency improvement during real-world testing at the Transportation Research Center and the American Center for Mobility. The outcomes provide a foundation for scalable, cost-effective deployment of energy-optimized CAV technologies across the automotive industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Progress on Long-Term Objectives for the Development of Advanced Reactor Mechanistic Source Term Modeling and Simulation Tools

To assist both the advanced reactor industry and U.S. Nuclear Regulatory Commission (NRC) in the pursuit of reactor design and licensing, the U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has established a mechanistic source term (MST) research project under the auspices of the Multiphysics Applications technical area. MST analysis is central to the reactor licensing process and a focus of the NRC regarding their mission to provide reasonable assurance of adequate protection of public health and safety and environment. The MST research project is a collaboration between Argonne National Laboratory (Argonne) and Sandia National Laboratories (SNL) with a high-level objective to coordinate the development of comprehensive advanced reactor MST mod/sim capabilities to support risk-informed design and licensing decisions. As part of this effort, an MST mod/sim development pathway was developed in FY21, which outlines the high-level objectives and near-term tasks necessary to achieve the project objectives. Since publication of the development pathway, Argonne and SNL have focused initial efforts on addressing the “near-term tasks” outlined in the report, and the current work provides a status update of the progress achieved in FY22. This report is a progress update on 6 tasks supporting molten salt reactor (MSR) and sodium fast reactor (SFR) MST analyses which were initiated in FY22 as recommended high priority near-term tasks. These tasks were continued into FY23 as they also support previously recommended long-term development objectives to advance MST analyses for these advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗