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Results for “charge patterning”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Battery Wear from Disparate Duty-Cycles: Opportunities for Electric-Drive Vehicle Battery Health Management; Preprint

Electric-drive vehicles utilizing lithium-ion batteries experience wholly different degradation patterns than do conventional vehicles, depending on geographic ambient conditions and consumer driving and charging patterns. A semi-empirical life-predictive model for the lithium-ion graphite/nickel-cobalt-aluminum chemistry is presented that accounts for physically justified calendar and cyclingfade mechanisms. An analysis of battery life for plug-in hybrid electric vehicles considers 782 duty-cycles from travel survey data superimposed with climate data from multiple geographic locations around the United States. Based on predicted wear distributions, opportunities for extending battery life including modification of battery operating limits, thermal and charge control are discussed.

25 ENERGY STORAGE↗
DOE OSTI2021

Data mining of plug-in electric vehicles charging behavior using supply-side data

This paper aims to better understand the charging patterns of plug-in electric vehicles (PEVs) and identify factors that may significantly impact PEVs’ charging behavior. We collected 189,864 supply-side charging session data over 13 months from 821 charging stations in Illinois from ChargePoint. Through descriptive and regression analyses, we characterize the distributions of key charging behavior indicators, including charging location, dwell time, and battery start state of charge (SOC), and quantify the impacts of closely related factors on these charging behaviors. In this work, we find that: (1) PEVs are more likely to charge in the morning at multifamily commercial locations with a lower start SOC compared with single family residential locations; (2) Weekday and morning sessions are more likely to utilize workplace charging and have shorter dwell time compared with weekend and afternoon sessions; (3) Single family residential area and locations with Levels 1/2 chargers have a higher start SOC and longer dwell time compared with other locations and DC fast chargers (DCFCs). These findings provide policy insights to identify potential time and locations to incentivize PEVs for grid services, as well as identify critical location categories for further charging infrastructure investment to better reduce range anxiety and promote PEV adoption.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Charge order landscape and competition with superconductivity in kagome metals

In the kagome metals AV 3 Sb 5 (A = K, Rb, Cs), three-dimensional charge order is the primary instability that sets the stage for other collective orders to emerge, including unidirectional stripe order, orbital flux order, electronic nematicity and superconductivity. In this report we use high-resolution angle-resolved photoemission spectroscopy to determine the microscopic structure of three-dimensional charge order in AV 3 Sb 5 and its interplay with superconductivity. Our approach is based on identifying an unusual splitting of kagome bands induced by three-dimensional charge order, which provides a sensitive way to refine the spatial charge patterns in neighbouring kagome planes. Here we found a marked dependence of the three-dimensional charge order structure on composition and doping. The observed difference between CsV 3 Sb 5 and the other compounds potentially underpins the double-dome superconductivity in CsV 3 (Sb,Sn) 5 and the suppression of T c in KV 3 Sb 5 and RbV 3 Sb 5 . Our results provide fresh insights into the rich phase diagram of AV 3 Sb 5 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Optimal Control of Differentially Private EV Charging: A Scalable Learning Approach Under Uncertainty

Internet of Things (IoT)-enabled electric vehicles (IoEVs) enable intelligent charging coordination that accounts for grid congestion. However, increased data exchange raises privacy concerns, as charging patterns can reveal sensitive driver behavior to grid operators. Here, we propose a differentially private (DP) EV charging framework that enables coordinated control while protecting driver data with theoretical privacy guarantees. Nevertheless, integrating DP inevitably introduces uncertainty into the control strategy for EVs, which can lead to infeasible solutions. To tackle this challenge, we develop a feasible and scalable control algorithm based on constrained reinforcement learning (CRL) and convex hulls. While our framework is designed to handle the uncertainty introduced by DP, it is general and also applicable to other sources of uncertainty in EV charging, such as the stochastic nature of driver behavior and renewable variability. This ensures feasible and privacy-preserving coordination of EV charging at scale. Our method constructs convex hulls within the action space to guarantee feasibility under stochastic constraints and incorporates constraint reduction techniques to improve scalability. Case studies based on IEEE benchmark systems demonstrate that the proposed approach effectively balances feasibility under uncertainty, scalability, and privacy in large-scale EV charging control.

Engineering - Power transmission and distribution↗
DOE OSTI2026

Interpretable Machine Learning for Characterizing Electric Vehicle Charging Behavior: Insights from Real-World Data

As electric vehicle (EV) adoption rises globally, concerns about the impact on aging electrical grids grow, particularly regarding the charging behavior of EV drivers. This study analyzes real-world driving and charging data from Ford battery electric vehicles (BEVs) collected between 2018 and 2019 to develop interpretable models that characterize charging behavior and quantify influencing factors. Prior research has relied on assumptions regarding driver behavior, often overlooking actual charging patterns. By employing generalized linear mixed models (GLMMs), this work offers insights into how various elements, such as next trip distance and state of charge (SOC), influence charging decisions. The dataset comprises over three million park-trip pairs from 1,997 vehicles, revealing that features related to driving behavior significantly dictate charging behavior, while infrastructure and regional factors have lesser impacts. The findings suggest that existing simulation models may oversimplify EV charging behavior assumptions. This work utilizes real-world EV driving and charging data to train interpretable models that describe charging behavior and quantify the factors most associated with how drivers use charging infrastructure. This research underscores the need for interpretable, data-driven methodologies to inform future EV infrastructure planning and grid management.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2019

Charge Order in {ital {beta}''}-Phase BEDT-TTF Salts.

Experimentally, we establish the quantitative phase diagram of 1/4-filled beta ''-(BEDT-TTF)(2)SF5RSO3 with a tendency toward charge order. Comprehensive optical, transport, and susceptibility measurements reveal the insulating nature and magnetic properties of the charge-ordered ground state. Going from R = CHF via CH(2)CF(2 )and CHFCF2 toward CH2, a finite charge disproportionation appears and grows up to 28 = 0.5e, as evidenced by charge-sensitive molecular vibrations. This is accompanied by an increase of electronic correlation strength, i.e., the intersite Coulomb repulsion V becomes more pronounced in relation to the bandwidth W. The broadband electronic excitations and their anisotropy unveil a distinct charge pattern for R = CH2 (checkerboard type) as compared to the other compounds (stripelike). Our results validate theoretical predictions for 1/4-filled systems, substantiating the importance of charge fluctuations for unconventional superconductivity at the verge between metal and insulator.

Pustogow, A.↗
DOE OSTI2020

Identifying sequence perturbations to an intrinsically disordered protein that determine its phase-separation behavior

Phase separation of intrinsically disordered proteins (IDPs) commonly underlies the formation of membraneless organelles, which compartmentalize molecules intracellularly in the absence of a lipid membrane. Identifying the protein sequence features responsible for IDP phase separation is critical for understanding physiological roles and pathological consequences of biomolecular condensation, as well as for harnessing phase separation for applications in bioinspired materials design. To expand our knowledge of sequence determinants of IDP phase separation, we characterized variants of the intrinsically disordered RGG domain from LAF-1, a model protein involved in phase separation and a key component of P granules. Based on a predictive coarse-grained IDP model, we identified a region of the RGG domain that has high contact probability and is highly conserved between species; deletion of this region significantly disrupts phase separation in vitro and in vivo. We determined the effects of charge patterning on phase behavior through sequence shuffling. We designed sequences with significantly increased phase separation propensity by shuffling the wild-type sequence, which contains well-mixed charged residues, to increase charge segregation. This result indicates the natural sequence is under negative selection to moderate this mode of interaction. We measured the contributions of tyrosine and arginine residues to phase separation experimentally through mutagenesis studies and computationally through direct interrogation of different modes of interaction using all-atom simulations. Finally, we show that despite these sequence perturbations, the RGG-derived condensates remain liquid-like. Together, these studies advance our fundamental understanding of key biophysical principles and sequence features important to phase separation.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Emissions Associated with Electric Vehicle Charging: Impact of Electricity Generation Mix, Charging Infrastructure Availability, and Vehicle Type

With the aim of reducing greenhouse gas emissions associated with the transportation sector, policy-makers are supporting a multitude of measures to increase electric vehicle adoption. The actual level of emission reduction associated with the electrification of the transport sector is dependent on the contexts that determine when and where drivers charge electric vehicles. This analysis contributes to our understanding of the degree to which a particular electricity grid profile, vehicle type, and charging patterns impact CO2 emissions from light-duty, plug-in electric vehicles. We present an analysis of emissions resulting from both battery electric and plug-in hybrid electric vehicles for four charging scenarios and five electricity grid profiles. A scenario that allows drivers to charge electric vehicles at the workplace yields the lowest level of emissions for the majority of electricity grid profiles. However, vehicle emissions are shown to be highly dependent on the percentage of fossil fuels in the grid mix, with different vehicle types and charging scenarios resulting in fewer emissions when the carbon intensity of the grid is above a defined level. Restricting charging to off-peak hours results in higher total emissions for all vehicle types, as compared to other charging scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

National Dataset of EV Charging Stations With Estimates of Load and Vehicle Throughput

Current data from the AFDC provide locations and many details about EV charging stations, but not estimates of their peak loads or the number of vehicles they can accommodate. This dataset will augment the AFDC charging station locations with estimates of transmission load and vehicle throughput based on engineering specifications of the chargers, charging patterns based on vehicle types, battery capacities, and user behavior.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Current rectification for transport of room-temperature ionic liquids through conical nanopores

Here, we studied the transport of room-temperature ionic liquids (RTILs) through charged conical nanopores using a Landau-Ginzburg-type continuum model that takes steric effect and strong ion-ion correlations into account. When the surface charge is uniform on the pore wall, weak current rectification is observed. When the charge density near the pore base is removed, the ionic current is greatly suppressed under negative bias voltage while nearly unchanged under positive bias voltage, thereby leading to enhanced current rectification. These predictions agree qualitatively with prior experimental observations, and we elucidated them by analyzing the different components of the ionic current and the structural changes of electrical double layers (EDLs) at the pore tip under different bias voltages and surface charge patterns. These analyses reveal that the different modifications of the EDL structure near the pore tip by the positive and negative bias voltages cause the current rectification and the observed dependence on the distribution of surface charge on the pore wall. The fact that the current rectification phenomena are captured qualitatively by the simple model originally developed for describing EDLs at equilibrium conditions suggests that this model may be promising for understanding the ionic transport under nonequilibrium conditions when the EDL structure is strongly perturbed by external fields.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Polyampholyte physics: Liquid–liquid phase separation and biological condensates

Here we review the current understanding of molecular interactions that govern liquid-liquid phase separation (LLPS) of biological condensates. The connection between sequence, chain conformation, and phase separation of intrinsically disordered proteins (IDPs) and their model polyampholytes is discussed. In particular, we highlight how the charge pattern influences the conformation and phase behavior of natural IDPs. We then describe recent results from theoretical treatments of polyampholytes implementing random phase approximation, field-theoretic simulations, and transfer matrix theory that show an increase in charge segregation results in an increased tendency to phase separate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A Forward-Looking Dataset of EV Managed Charging Resource and Costs

This presentation summarizes a high-resolution, forward-looking dataset of EV adoption, EV charging, and managed charging resource. Vehicle-level data are grounded in current adoption and charging patterns, and ~200,000 real-world vehicle-weeks of travel data covering all on-road segments (i.e., light-duty, transit and school buses, local, regional and long-haul medium- and heavy-duty). The data, which include multiple charging profiles per vehicle to bound flexibility, are then processed and aggregated to describe baseline charging and charge management resource by county, hour, year, scenario, and vehicle type. Coupled with one of four scenarios of how EV managed charging costs might evolve over time, the dataset enables a power sector capacity expansion model to select cost-optimal quantities of EV managed charging and supply-side resources to reliably satisfy demand. Five integration strategies: Baseline, Daytime and Flat (passive), Flex (active), and Stress (anti-strategy), illustrate how baseline charging and flexibility potential changes with EVSE build-out and charging preferences.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Dissecting neurofilament tail sequence-phosphorylation-structure relationships with multicomponent reconstituted protein brushes

Neurofilaments (NFs) are multisubunit, bottlebrush-shaped intermediate filaments abundant in the axonal cytoskeleton. Each NF subunit contains a long intrinsically disordered tail domain, which protrudes from the NF core to form a “brush” surrounding each NF. Precisely how the tails’ variable charge patterns and repetitive phosphorylation sites mediate their conformation within the brush remains an open question in axonal biology. We address this problem by grafting recombinant NF tail protein constructs NF-Light, -Medium, and -Heavy (NFL, NFM, and NFH) to surfaces, yielding protein brushes of defined stoichiometry that can be phosphorylated in vitro. Atomic force microscopy measurements reveal that brush height depends on composition monotonically but not always linearly for binary NFL:NFM or NFL:NFH systems, and that NFM-based brushes are highly extended, while brushes incorporating the much larger NFH are surprisingly compact even after multisite phosphorylation. Complementary self-consistent field theory (SCFT) predicts multilayer brush morphologies for NFM and phosphorylated NFH brushes. Further experiments and SCFT analysis with designed mutants reveal that N-terminal negative charges in the NFH tail repel phosphorylated residues to generate the multilayer morphology, while the C-terminal charge-neutral region contributes to multilayer brush morphology but not total brush height. Charge-shuffled NFM variants show that charge segregation promotes brush collapse near physiological ionic strengths. Collectively, this study supports a role for NFM in establishing a dynamic range for NF brush conformation, lending insight into previous in vitro and in vivo findings. More broadly, this work establishes a platform for dissecting contributions of disordered protein sequence to conformation at interfaces.

Science & Technology - Other Topics↗
DOE OSTI2016

Polarization of gold in nanopores leads to ion current rectification

Biomimetic nanopores with rectifying properties are relevant components of ionic switches, ionic circuits, and biological sensors. Rectification indicates that currents for voltages of one polarity are higher than currents for voltages of the opposite polarity. Ion current rectification requires the presence of surface charges on the pore walls, achieved either by the attachment of charged groups or in multielectrode systems by applying voltage to integrated gate electrodes. Here we present a simpler concept for introducing surface charges via polarization of a thin layer of Au present at one entrance of a silicon nitride nanopore. In an electric field applied by two electrodes placed in bulk solution on both sides of the membrane, the Au layer polarizes such that excess positive charge locally concentrates at one end and negative charge concentrates at the other end. Consequently, a junction is formed between zones with enhanced anion and cation concentrations in the solution adjacent to the Au layer. This bipolar double layer together with enhanced cation concentration in a negatively charged silicon nitride nanopore leads to voltage-controlled surface-charge patterns and ion current rectification. The experimental findings are supported by numerical modeling that confirm modulation of ionic concentrations by the Au layer and ion current rectification even in low-aspect ratio nanopores. Lastly, our findings enable a new strategy for creating ionic circuits with diodes and transistors.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Charging of moving surfaces by corona discharges sustained in air

Atmospheric pressure corona discharges are used in electrophotographic (EP) printing technologies for charging imaging surfaces such as photoconductors. A typical corona discharge consists of a wire (or wire array) biased with a few hundred volts of dc plus a few kV of ac voltage. An electric discharge is produced around the corona wire from which electrons drift towards and charge the underlying dielectric surface. The surface charging reduces the voltage drop across the gap between the corona wire and the dielectric surface, which then terminates the discharge, as in a dielectric barrier discharge. In printing applications, this underlying surface is continuously moving throughout the charging process. For example, previously charged surfaces, which had reduced the local electric field and terminated the local discharge, are translated out of the field of view and are replaced with uncharged surface. The uncharged surface produces a rebound in the electric field in the vicinity of the corona wire which in turn results in re-ignition of the discharge. The discharge, so reignited, is then asymmetric. We found that in the idealized corona charging system we investigated, a negatively dc biased corona blade with a dielectric covered ground electrode, the discharge is initially sustained by electron impact ionization from the bulk plasma and then dominated by ionization from sheath accelerated secondary electrons. Depending on the speed of the underlying surface, the periodic re-ignition of the discharge can produce an oscillatory charging pattern on the moving surface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Systematic coarse-grained modeling of complexation between small interfering RNA and polycations

All-atom molecular dynamics simulations can provide insight into the properties of polymeric gene-delivery carriers by elucidating their interactions and detailed binding patterns with nucleic acids. However, to explore nanoparticle formation through complexation of these polymers and nucleic acids and study their behavior at experimentally relevant time and length scales, a reliable coarse-grained model is needed. Here, we systematically develop such a model for the complexation of small interfering RNA (siRNA) and grafted polyethyleneimine copolymers, a promising candidate for siRNA delivery. We compare the predictions of this model with all-atom simulations and demonstrate that it is capable of reproducing detailed binding patterns, charge characteristics, and water release kinetics. Since the coarse-grained model accelerates the simulations by one to two orders of magnitude, it will make it possible to quantitatively investigate nanoparticle formation involving multiple siRNA molecules and cationic copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure

This paper presents a behavioral model of public, revealed preferences (RP) for various types of electric vehicles (EVs) while accounting for a latent (green) travel pattern construct and charging infrastructure characteristics. Specifically, a two-level nested logit (NL) model is estimated to explain households' fuel type choice among five alternatives and three nests: (1) battery electric vehicles (BEVs); (2) hybrid vehicles including hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs); and (3) conventional vehicles including gasoline and diesel vehicles. Further, a latent travel pattern construct which captures a week-long number of trips by non-vehicle travel modes as well as daily vehicle and tollway use is estimated in a structural equation setting and subsequently fed into the NL model. Using a recent RP dataset from the California Household Travel Survey, we identify market segments for alternative fuel types based on households' socio-economic characteristics, built environment factors concerning public plug-in EV (PEV) charging infrastructure characteristics, latent and observable travel behavior factors of a household vehicle's principal driver, and vehicle attributes. The results highlight that the number of public PEV charging stations is only significant for households choosing PHEVs and interestingly insignificant in the BEV utility. Furthermore, the sensitivity analysis of the findings reveals that PHEV users are elastic with respect to household vehicle ownership ratio and the latent green travel pattern construct, while BEV users are inelastic to any explanatory variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗