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DOE OSTI2021

Uncontrolled Electric Vehicle Charging Impacts on Distribution Electric Power Systems with Primarily Residential, Commercial or Industrial Loads

An increase in Electric Vehicles (EV) will result in higher demands on the distribution electric power systems (EPS) which may result in thermal line overloading and low voltage violations. To understand the impact, this work simulates two EV charging scenarios (home- and work-dominant) under potential 2030 EV adoption levels on 10 actual distribution feeders that support residential, commercial, and industrial loads. The simulations include actual driving patterns of existing (non-EV) vehicles taken from global positioning system (GPS) data. The GPS driving behaviors, which explain the spatial and temporal EV charging demands, provide information on each vehicles travel distance, dwell locations, and dwell durations. Then, the EPS simulations incorporate the EV charging demands to calculate the power flow across the feeder. Simulation results show that voltage impacts are modest (less than 0.01 p.u.), likely due to robust feeder designs and the models only represent the high-voltage (“primary”) system components. Line loading impacts are more noticeable, with a maximum increase of about 15%. Additionally, the feeder peak load times experience a slight shift for residential and mixed feeders (≈1 h), not at all for the industrial, and 8 h for the commercial feeder.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Evaluation of Light-Element Reactions in the Resolved Resonance Region

Light-element reactions at low energies in the resolved resonance region are important for a range of applications in basic and applied sciences including nuclear reactors, nonproliferation, cultural heritage, forensics and environmental control, rare event investigations and nuclear astrophysics. In this paper, we report on an effort to evaluate charged-particle cross sections in the resolved resonance region and produce evaluated nuclear data files for further processing and inclusion in evaluated data libraries. We discuss the open issues in R-matrix calculations as we extend to higher energies, such as dealing with the rapidly growing number of open channels and merging with the regime of smooth cross sections described by the statistical model, and present attempts to address these issues in neutron-induced reactions relevant to nuclear reactor applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Second Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Tunable Nanoscale Structure via Divalent Ion Identity in Charged-Neutral Polymer Blends

Charged-neutral polymer blends, wherein an ioncontaining polymer is blended with a neutral polymer, are potential candidates for battery electrolytes due to their improved ion transport properties and electrochemical stability. Though electrostatic interactions in charged polymer blends can theoretically stabilize ordered nanostructures analogous to those observed in neutral block copolymers, direct experimental evidence remains limited. Here, we investigate the effects of divalent cation identity on the nanoscale morphology of charged-neutral polymer blends composed of poly(ethylene oxide) (PEO) and Mg 2+ or Ca 2+ ioncontaining polymers, poly[3-(methylacryloxy)propylsulfonyl-1-(trifluoromethanesulfonylimide)] (P(Mg(MTFSI) 2 ) or P(Ca- (MTFSI) 2 ). By tuning the size of the divalent counterion, we are able to precisely tune the ion solvation between the free cation and PEO, which acts as a solvent in this system. Differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS) measurements reveal that Mg 2+ and Ca 2+ ions induce distinct structural behavior. In both systems, the blends become more miscible as the concentration of ion-containing polymer is increased indicated by increased suppression of PEO crystallinity. At the highest concentrations of P(Mg(MTFSI) 2 ), the blends undergo microphase separation and generate nanostructures with shortranged ordering. In contrast, calcium ions, which are more readily solvated by PEO, produce more homogeneous blends characterized by a single glass-transition temperature and featureless SAXS data. The results demonstrate the novel experimental confirmation that charged-neutral polymer blends can undergo microphase separation and show that counterion identity can be exploited as a design parameter to control nanoscale morphology.

Ions↗

DOE OSTI2020

Observation of the associated production of a top quark and a Z boson in pp collisions at $ \sqrt{s} $= 13 TeV with the ATLAS detector

Single top-quark production in association with a Z boson, where the Z boson decays to a pair of charged leptons, is measured in the trilepton channel. The proton-proton collision data collected by the ATLAS experiment from 2015 to 2018 at a centre-of-mass energy of 13 TeV are used, corresponding to an integrated luminosity of 139 fb -1 . Events containing three isolated charged leptons (electrons or muons) and two or three jets, one of which is identified as containing a b -hadron, are selected. The main backgrounds are from $ t\overline{t}Z $ and diboson production. Neural networks are used to improve the background rejection and extract the signal. The measured cross-section for t ℓ + ℓ - q production, including non-resonant dilepton pairs with $ {m}_{{\mathrm{\ell}}^{+}{\mathrm{\ell}}^{-}} $ > 30 GeV, is 97 ± 13 (stat.) ± 7 (syst.) fb, consistent with the Standard Model prediction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Precision Neutrino Oscillation Physics with the Daya Bay and DUNE Experiments

The team supported by this grant made significant contributions to the final results of the Daya Bay Reactor Antineutrino Experiment. This experiment utilized eight identically designed antineutrino detectors positioned at varying distances from six 2.9 GW th nuclear reactors to precisely measure the oscillation parameters that govern antineutrino disappearance at short (<2 km) baselines. Our group played a leading role in the calibration and data quality efforts, both of which have been crucial for all final results. Additionally, we co-led the development of an independent measurement of the neutrino mixing angle θ 13 and the atmospheric mass splitting using a sample of antineutrinos identified via neutron capture on hydrogen. Lastly, we laid the groundwork for a search for seasonal modulation in Daya Bay’s measured muon flux using the final dataset, a result expected to be published soon. Simultaneously, our team ramped up its participation in the Deep Underground Neutrino Experiment (DUNE). This experiment will employ a powerful neutrino beam from Fermilab in Illinois directed to the Homestake mine in South Dakota to address some of the most pressing questions in neutrino physics, including the ordering of neutrino masses and whether neutrinos violate the CP symmetry. Our work focused on the development of the pixelated and modularized Liquid Argon Time-Projection Chamber technology that is being prepared for DUNE’s Near Detector. Our group took responsibility for the development, testing, and maintenance of the firmware for the control boards of the detector’s charge readout system and played an active role in analyzing data produced by the very first fully integrated prototypes.

2x2 Demonstrator↗

DOE OSTI2020

A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles

The proliferation of electric vehicles (EVs) brings environmental benefits and technical challenges to power grids. An identification algorithm which can accurately extract individual EV charging profiles out of widely available smart meter measurements has attracted great interests. This paper proposes a non-intrusive identification framework for EV charging profile extraction, which is driven by deep generative models (DGM). First, the proposed DGM is designed as a representation layer embedded into the Markov process and used to model the joint probability distribution of available time-series data. A novel contribution is to approximate posterior distributions by neural networks whose parameters are obtained by variational inference and supervised learning. Second, the EV charging status is inferred from the DGM via dynamic programming. Lastly, the desired EV charging profile can be reconstructed by the rated power of EV models and inferred status. Compared with the benchmark Hidden Markov Models, the proposed framework can better handle noise in data with less computational complexity and better overall accuracy performances with smaller recall. The proposed framework is validated by numerical experiments on the Pecan Street dataset.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

What Shapes Transportation Charging Infrastructure Availability? Evidence from Tennessee

This study examines how community, travel, and freight characteristics relate to public charging infrastructure availability across Tennessee ZIP codes. We link Alternative Fuels Data Center station locations with traffic, socioeconomic, demographic, commuting, and freight employment data to build a ZIP code-level dataset. Ordinary least squares regression captures variation in chargers per 10,000 residents (R2=0.311). Quantile regressions at the 25th, 50th, and 75th percentiles, with pseudo R2 values up to 0.099, show that the determinants of infrastructure availability differ across low-, medium-, and high-availability areas. Percent female, percent car commuters, average household size, and median age are negatively associated with charging availability across much of the distribution. Truck traffic is positively associated only in lower-availability ZIP codes, while vehicle miles traveled shifts from a negative association at the lower end of the distribution to a positive association at the upper end. The results provide insight into how public charging deployment aligns with community characteristics, mobility demand, and freight activity across Tennessee. Future work can distinguish charger types and power levels, incorporate land-use and temporal rollout patterns, and examine how charging infrastructure needs differ across urban and rural contexts.

Calderón, Oriana [University of Tennessee, Knoxvil↗

DOE OSTI2025

Search for same-charge top-quark pair production in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for the production of top-quark pairs with the same electric charge ($tt$ or $\overline{tt}$) is presented. The analysis uses proton-proton collision data at $\sqrt{s}$ = 13 TeV, recorded by the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb −1 . Events with two same-charge leptons and at least two b-tagged jets are selected. Neural networks are employed to define two selections sensitive to additional couplings beyond the Standard Model that would enhance the production rate of same-sign top-quark pairs. No significant signal is observed, leading to an upper limit on the total production cross-section of same-sign top-quark pairs of 1.6 fb at 95% confidence level. Corresponding limits on the three Wilson coefficients associated with the $\mathcal{O}^{(1)}_{tu}$, $\mathcal{O}^{(1)}_{Qu}$, and $\mathcal{O}^{(8)}_{Qu}$ operators in the Standard Model Effective Field Theory framework are derived.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Comprehensive Characterization of Water Group Ion Composition and Distributions in Saturn's Magnetosphere With Cassini Plasma Spectrometer Data

Saturn's magnetosphere is continuously supplied with neutrals from the Enceladus plume and the icy rings, which undergo ionization and charge-exchange to form a complex water-group plasma environment. While the Cassini Plasma Spectrometer (CAPS) instrument has provided extensive compositional information, detailed separation of individual water-group ion species in time-of-flight (TOF) data has not previously been achieved. In this study, we perform forward modeling of CAPS-IMS energy-per-charge (E/Q) and TOF spectra obtained between 2004 and 2012 to resolve O + , OH + , H 2 O + , and H 3 O + and to characterize their plasma properties, including number density, temperature, and thermodynamic κ. Our results demonstrate that O + is the dominant thermal ion species throughout Saturn's magnetosphere, comprising up to ∼70% of the total ion population beyond ∼5 Saturn radii (R S ). In contrast, molecular ions such as OH + , H 2 O + , and H 3 O + dominate closer to Enceladus but rapidly dissociate into atomic ions between ∼5 and 10 R S . This radial region is also characterized by the steepest increase in plasma flow speed, which rises from ∼40% to ∼80% of rigid corotation. Simultaneously, ion velocity distributions approach Maxwell–Boltzmann equilibrium, as indicated by high kappa values. These findings provide new constraints on the ion–neutral chemistry that regulates the balance between molecular and atomic ions in Saturn's magnetosphere. They also emphasize the critical role of the 5–10 R S region as a transition zone for both plasma composition and dynamics. Our results refine previous CAPS-based studies and underscore the need to incorporate seasonal variability and ionospheric coupling into future global models of Saturn's plasma environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Advanced Modeling of Beam Physics and Performance Optimization for Nuclear Physics Colliders

High energy colliders provide a critical tool in nuclear physics study by probing the fundamental structure and dynamics of matter. To maximize the potential of scientific discovery in nuclear physics study, it is important to optimize the parameters of these colliders to attain the best performance. The performance of a collider is typically measured by its integrated luminosity of colliding beams since the probability of a new event is proportional to the integrated luminosity. However, the achievable luminosity is limited by the electromagnetic interactions (beam-beam effects) of two colliding beams at higher energy, and the interplay between the space-charge effects and the beam-beam effects at lower energy. To achieve the best performance of a collider means to attain the highest luminosity of the collider with optimized collider parameters. Optimizing the collider’s machine parameters is both computationally and experimentally expensive. A fast and robust computational framework including beam-beam and space-charge effects will be critical to attaining the best performance of the collider. In this project, we will study the beam dynamics challenges, specifically the interplay of the space-charge and the beam-beam effects, and the machine tuning models for maximizing the performance of RHIC experiments. We will develop an advanced modeling framework based on first-principles physical simulations, lattice models and the state-of-the-art machine learning methods and apply this framework to performance improvement of the RHIC in operation. We will build data manipulation packages to connect the simulation data and the experimental data with the framework, develop a self-consistent hybrid model of space-charge and beam-beam effects, study underlying physics mechanisms, build surrogate models using the labeled data, integrate the models into the advanced modeling framework, and apply the framework to RHIC luminosity (STAR and sPHENIX) optimization. The success of this project would substantially improve the performance of existing and future colliders and increase the opportunity for scientific discovery.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Evaluating Direct and Indirect Influence on EV Charging Stations Across the US

The adoption of new technology for electric vehicles (EV) and mobility applications can bring underappreciated vulnerabilities to the power grid. One area of potential fraud and adversarial influence is through the business ecosystem of startups that own and deploy EV technology. Yet, there are no models or analyses that map the network of organizations and people that have direct and indirect influence over technologies currently deployed in the grid. To fill this gap, we develop a multilayer network model to measure direct and indirect influence on EV charging stations. First, we create and adversarial socio-technical network (ASTN) model via a data fusion pipeline for different US regions of interest (ROI). Then, we develop an integrated ASTN for Chicago, Los Angeles, New York, and Philadelphia. We rank EV charging companies direct influence within each geographic region as well as indirect influence via social network analysis. While some companies have strong direct and indirect influence (i.e., ChargePoint) others show a mismatch between their influence over charging stations and their position within the social network. For example, Tesla has strong direct influence on stations and weak indirect influence over competitors. In contrast, 7Charge has weak direct influence over stations, but strong indirect influence over competitors.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2022

Effects of Hydrogen Bonding on Nuclear Data Development of Liquid Anhydrous HF

Anhydrous Hydrogen Fluoride (HF) at high temperatures and pressures is used to process and manufacture nuclear fuel. As HF is often used directly with uranium, correct neutron thermal scattering cross sections are crucial to criticality safety applications. Classical molecular dynamics (CMD) simulation of the flexible HF system was used to create the thermal scattering law (TSL) and cross sections. The initial 2-site model is used in LAMMPS, and it can not capture the H-bond. To correctly represent the H-bond effects, a second, 3-site model was constructed in GROMACS. The 3-site model handled H-bonds by connecting a massless charge to the molecule. Key model parameters were compared to experimental data to verify the approach and models. To get the normalized VACF, the model was compared using hydrogen and fluorine bond length, density, potential energy, and diffusion coefficient. The phonon DOSs for both models were derived from the normalized VACF. DOSs were used to estimate the TSL ( S ( α, β )) and neutron thermal scattering cross sections for hydrogen in HF. The TSLs were evaluated using the FLASSH code with the Schofield diffusion model. It was observed that the representation of the hydrogen bonding changes the TSL's diffusional contributions. This is represented in the low energy scattering cross section, where intermolecular binding effects shift the cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Measurement of charged particle multiplicity distributions in DIS at HERA and its implication to entanglement entropy of partons

Charged particle multiplicity distributions in positron-proton deep inelastic scattering at a centre-of-mass energy √s = 319 GeV are measured. The data are collected with the H1 detector at HERA corresponding to an integrated luminosity of 136 pb -1 . Charged particle multiplicities are measured as a function of photon virtuality Q 2 , inelasticity y and pseudorapidity η in the laboratory and the hadronic centre-of-mass frames. Predictions from different Monte Carlo models are compared to the data. The first and second moments of the multiplicity distributions are determined and the KNO scaling behaviour is investigated. The multiplicity distributions as a function of Q 2 and the Bjorken variable x bj are converted to the hadron entropy S hadron , and predictions from a quantum entanglement model are tested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High- Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of $\mathcal{O}$(40 MHz) and intelligently reduces the data within the pixelated region of the detector at rate will enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 57.1%–75.7%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300 μW with an area of less than 0.2 mm 2 . The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Search for charged-lepton flavor violation in the production and decay of top quarks using trilepton final states in proton-proton collisions at $\sqrt{s}$ =13 TeV

A search is performed for charged-lepton flavor violating processes in top quark (𝑡) production and decay. The data were collected by the CMS experiment from proton-proton collisions at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 138 fb −1 . The selected events are required to contain one opposite-sign electron-muon pair, a third charged lepton (electron or muon), and at least one jet of which no more than one is associated with a bottom quark. Boosted decision trees are used to distinguish signal from background, exploiting differences in the kinematics of the final states particles. The data are consistent with the standard model expectation. Upper limits at 95% confidence level are placed in the context of effective field theory on the Wilson coefficients, which range between 0.024–0.424 TeV −2 depending on the flavor of the associated light quark and the Lorentz structure of the interaction. These limits are converted to upper limits on branching fractions involving up (charm) quarks, 𝑡 → 𝑒⁢𝜇⁢𝑢 (𝑡 → 𝑒⁢𝜇⁢𝑐), of 0.032⁢(0.498) × 10 −6 , 0.022⁢(0.369) × 10 −6 , and 0.012⁢(0.216) × 10 −6 for tensorlike, vectorlike, and scalarlike interactions, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Search for top squark pair production using dilepton final states in ${\text {p}}{\text {p}}$ collision data collected at $\sqrt{s}=13\,\text {TeV} $

A search is presented for supersymmetric partners of the top quark (top squarks) in final states with two oppositely charged leptons (electrons or muons), jets identified as originating from ${\text {b}}$quarks, and missing transverse momentum. The search uses data from proton-proton collisions at $\sqrt{s}=13\,\text {TeV} $ collected with the CMS detector, corresponding to an integrated luminosity of 137$\,{\text {fb}}^{-1}$. Hypothetical signal events are efficiently separated from the dominant top quark pair production background with requirements on the significance of the missing transverse momentum and on transverse mass variables. No significant deviation is observed from the expected background. Exclusion limits are set in the context of simplified supersymmetric models with pair-produced lightest top squarks. For top squarks decaying exclusively to a top quark and a lightest neutralino, lower limits are placed at $95\%$ confidence level on the masses of the top squark and the neutralino up to 925 and 450$\,\text {GeV}$, respectively. If the decay proceeds via an intermediate chargino, the corresponding lower limits on the mass of the lightest top squark are set up to 850$\,\text {GeV}$ for neutralino masses below 420$\,\text {GeV}$. For top squarks undergoing a cascade decay through charginos and sleptons, the mass limits reach up to 1.4$\,\text {TeV}$ and 900$\,\text {GeV}$ respectively for the top squark and the lightest neutralino.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Helium-4 gravitational form factors: Exchange currents

We evaluate the leading exchange corrections to the helium-4 gravitational form factors (GFFs) to momenta of the order of the nucleon mass. We use both the K-harmonic method with simple pair nucleon potential, and a Jastrow trial function using the Argonne 𝑣 14 potential, to evaluate the helium-4 GFFs. The exchange current contributions include the pair interaction, plus the seagull and the pion exchange interactions, modulo the recoil corrections. To estimate the off-shellness of the pion nucleon coupling in this momenta range, we discuss the results using either the pseudoscalar (PS) or pseudovector (PV) pion-nucleon couplings. When the PV coupling is used, the pair diagram contribution is higher order in the nonrelativistic expansion. The results for the helium-4 A-GFF are comparable to those given by the impulse approximation, especially for the PS coupling using both the K-harmonic method and variational method. The exchange current contributions with the PS coupling for the charge form factor of helium-4, yield better agreement with the existing data over a broad range of momenta, especially when the Argonne 𝑣 14 potential including the D-wave admixture is used.

A ≤ 5↗