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At least 73 records · Page 4

Revisiting the assignment of atomic charges in metal oxides based on core-level x-ray photoelectron spectra: The case of Ti in SrTiO3(001)

We demonstrate that assigning formal charges to transition metal (TM) cations based on core-level (CL) x-ray photoemission binding energies in oxides leads to physically inconsistent pictures of electronic structure. O 2p–TM 3d hybridization is well known to result in significant covalency in TM–O bonds, thereby reducing TM cation charges from their fully ionic values. However, the ionic bonding model remains the working paradigm for assigning TM CL features, and the resulting cation charges are often taken to be representative of the material under study. Here, we show that a more physically meaningful way to assign charges is to extract information about charge distributions utilizing Dirac–Hartree–Fock theory to calculate CL spectra from first principles and then use the resulting wave functions to determine charges based on orbital occupancies. TM cation charges can also be determined using density functional theory and Bader population analysis. We illustrate these two methods using the Ti 2p spectrum for SrTiO3(001) and show that the agreement between them is excellent. Significantly, the resulting Ti charge is considerably lower than the formal charge. The high degree of similarity between the Ti 2p spectrum for SrTiO3 and those for the rutile and anatase polymorphs of TiO2 suggests that the charge densities surrounding Ti in the latter materials are similar to that in SrTiO3. Taking a broader perspective, oxides containing other first-row transition metals also exhibit covalent character, leading to TM cation charges lower than the analogous fully ionic values in these materials as well.

Chambers, Scott A. (ORCID:000000025415043X)↗

All-optical control of charge-trapping defects in rare-earth doped oxides

Abstract Charge-trapping defects in crystalline solids play important roles in applications ranging from microelectronics, optical storage, sensing and quantum technologies. On one hand, depleting trapped charges in the host matrix reduces charge noise and enhances coherence of solid-state quantum emitters. On the other hand, stable charge traps can enable high-density optical storage systems. Here we report all-optical control of charge-trapping defects via optical charge trapping (OCT) spectroscopy of a rare-earth ion doped oxide (Y 2 O 3 ). Charge trapping is realized by low intensity optical excitation in the 200–375 nm range. Charge detrapping or depletion is carried out by optically stimulated luminescence (OSL) under 532 nm stimulation. Using a Pr-doped Y 2 O 3 polycrystalline ceramic host matrix, we observe charging pathways via the inter-band optical absorption of Y 2 O 3 and via the 4f-5d transitions of Pr 3+ . We demonstrate effective control of the density of trapped charges within the Y 2 O 3 matrix at ambient environment. These results point to a viable method for controlling the local charge environment in rare-earth doped crystals via all-optical means, and pave the way for further development of efficient optical storage technologies with ultrahigh storage capacity, as well as for the localized control of quantum coherence in rare-earth doped solids.

França, Leonardo V. S. [Pritzker School of Molecul↗

Window-integrated charge-mode digital-to-analog converter for arbitrary waveform generator

A digital-to-analog converter circuit that creates an analog waveform from an input digital waveform. Operating the circuit comprises using the input digital waveform to 1) operate a charge control switch to set a charge time period, 2) operate a discharge control switch to set a discharge time period, 3) set a charge current magnitude using a charge gain, and 4) set a discharge current magnitude using a discharge gain. A charge source electrically charges a load capacitor during the charge time period (i.e., the charge mode). A discharge source electrically discharges the load capacitor during the discharge time period (i.e., the discharge mode). A circuit output transmits the analog waveform defined by the charge mode and the discharge mode. A charge current magnitude greater than the discharge current magnitude produces an upward-sloping analog waveform. A charge current magnitude less than the discharge current magnitude produces a downward-sloping analog waveform.

Li, Shaorui↗

Humidity-Dependent Electrostatic Charge Decay on Dielectric Surface in Enclosed Volumes

Electrostatic surface charge decay is investigated to determine loss mechanisms, the effect of humidity, enclosure size, and material. This work focuses on charging dielectric and metal surfaces close to the electrical breakdown threshold in atmospheric air under humid and dry conditions. After initial charging to a maximum potential of roughly 30 kV, the associated surface charge is allowed to decay because of recombining with ions from the natural background, resulting in decay times ranging from minutes to hours to days. Spheres with a radius of 50 mm consisting of varying materials (PTFE and metal as referenced later) are charged and tested at relative humidity levels, RH, of 10%, 35%, and 64%. It was found that the ion-ion pair production rate and the enclosure size affected the measured charge decay rate. The impact of air convection on charge decay in the open air (no enclosure) is discussed. The humidity increased the rate of charge decay on the metal and dielectric spheres. For example, in the first 25 minutes after charging, the total charge on the PTFE sphere decreased to 66%or 50% from its initial value in the 10% and 35% RH tests, respectively. An equivalent generation rate is found for the ions in the enclosure, with 10 and 24 ion pairs cm −3 s −1 being generated at a 5% and 49% relative humidity, respectively.

42 ENGINEERING↗

GSE Yearly Load Profiles for Each Airport Under Six Charging Scenarios

This dataset contains GSE yearly load profiles for each airport under six charging scenarios: (1) charging when the battery state of charge is insufficient for the next service using 40-kW chargers (S1); (2) charging when the battery state of charge is insufficient for the next service using 20-kW chargers (S2); (3) charging starts immediately after each GSE completes a service task using 40-kW chargers (S3); (4) charging starts immediately after each GSE completes a service task using 20-kW chargers (S4); (5) charging during off-peak hours using 40-kW chargers (S5); and (6) charging during off-peak hours using 20-kW chargers (S6). ![image](gse_load_profile_sample_day.png) GSE load profile of a sample day across different airport categories under charging scenario 1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

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↗

Statistical Estimation of EV Driver Charging Behavior and Influential Factors

INL received data collected via telematics from battery electric vehicles (BEVs), and these vehicles were owned by retail customers who had entered into a telematics user agreement. The goal of analyzing these data was to develop mathematical models to characterize how different sets of BEV drivers use charging infrastructure at home and away from home (i.e., public charging) and quantify how various factors influence BEV drivers’ decision to charge and use available infrastructure. The data used in this analysis are unique because they provide real world BEV driving and charging behavior at the individual driving and parking event level. In this study we seek to leverage this data to quantify BEV charging and driving metrics to help inform models that predict quantities like the specific times when loads are imposed on the electrical grid due to BEV charging. Most models that have been developed to predict electrical grid load due to BEV charging, use simulations of BEV driving events and rely on assumptions such as every vehicle charges every night. Using a statistical modelling framework, we seek to investigate BEV charging behavior and quantitatively assess these common assumptions of BEV charging behavior.

33 - ADVANCED PROPULSION SYSTEMS↗

Cost of convenience in long-dwell public electric vehicle charging

This paper presents a comprehensive methodology for quantifying trade offs between the cost of charging at public Level-2 charging stations and the inconvenience of using those stations. The paper also includes a methodology for generating synthetic travel itineraries of tens of thousands of drivers and for sizing and placing charging infrastructure to support those itineraries. Inconvenience is quantified by a weighted sum of the time a driver spends traveling between their intended destination and the charging station; weights are derived from the activity interrupted by the driver’s need to move their car. We demonstrate a trade off between cost of charging and inconvenience by varying how far away from their destination drivers are willing to charge. Our results demonstrate the importance of access to stations and suggest that other methods for increasing access, such as increasing the spatial density of stations, could significantly impact charging cost and inconvenience. Moreover, average energy cost may be reduced by introducing managed charging, which also affects inconvenience. The framework presented here can be used to evaluate the overlapping effects of both access and charge management. Furthermore, the framework can be easily extended to include additional factors such as capital costs, enabling thorough evaluation and planning of regional Level-2 charging networks.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. Further, the results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Depot Charging Schedule Optimization for Medium- and Heavy-Duty Battery-Electric Trucks

Charge management, which lowers charging costs for fleets and prevents straining the electrical grid, is critical to the successful deployment of medium- and heavy-duty battery-electric trucks (MHD BETs). This study introduces an energy demand and cost management framework that optimizes depot charging for MHD BETs by combining an energy consumption machine learning model and a linear program optimization model. The framework considers key factors impacting real-world MHD BET operations, including vehicle and charger configurations, duty cycles, use cases, geographic and climate conditions, operation schedules, and utilities’ time-of-use (TOU) rates and demand charges. The framework was applied to a hypothetical fleet of 100 MHD BETs in California under three different utilities for 365 days, with results compared to unmanaged charging. The optimized charging solution avoided more than 90% of on-peak charging, reduced fleet charging peak load by 64–75%, and lowered fleet energy variable costs by 54–64%. This study concluded that the proposed charge management framework significantly reduces energy costs and peak loads for MHD BET fleets while making recommendations for fleet electrification infrastructure planning and the design of utility TOU rates and demand charges.

Song, Shuhan↗

Strategies for Enhancing Battery Life Under Fast Charging: Insights from NMC-Based Cell Cycling

Fast charging improves the usability of consumer electronics and electric vehicles (EVs) by reducing range anxiety and downtime but accelerates battery degradation and raises safety concerns. Optimizing operational conditions during fast-charging is critical to mitigating aging and ensuring safety. This study evaluated multilayer Gr/NMC811 cells under various conditions, including depths of discharge (DODs of 68%, 84%, and 100%), upper charge cutoff voltages (4.1–4.2 V), and post-charge rest periods (2–30 min), using a 20 min fast charging protocol for up to 500 cycles (up to 150,000 miles of EV use assuming 3.3 mi/kWh vehicle level energy efficiency). Surprisingly, higher DODs under fast charging improved battery life and performance compared to lower DODs. Reducing the upper charge cut-off voltage helped mitigate degradation. A brief 2 min rest period after charging further reduced aging effects. The primary aging modes were loss of lithium inventory and cathode active material. Although minor lithium plating was observed within 500 cycles, it did not affect performance significantly. These findings suggest that, with optimized conditions, cells can sustain hundreds of fast charge cycles—equivalent to over 100,000 miles of EV use—without significant adverse effects on performance or longevity.

25 - ENERGY STORAGE↗

Understanding EV Charging Pain Points Through Deep Learning Analysis

Current and potential electric vehicle (EV) owners express concerns about the charging infrastructure, mentioning non-functional chargers, prolonged charging times, inconvenient charger locations, long wait times, and high costs as major barriers. Addressing these issues often requires analyzing actual vehicle charging data, which is typically proprietary and inconsistent due to diverse standards and protocols. To understand and improve the EV charging experience, customer reviews are typically used to identify common customer pain points (CPPs). However, there is not a comprehensive method to map customer reviews to a standardized set of CPPs. In collaboration with the National Charging Experience (ChargeX) Consortium, this study bridges these gaps by proposing a Systematic Categorization and Analysis of Large-scale EV-charging Reviews (SCALER) framework. SCALER is an integrated, deep learning framework that segments, actively labels, analyzes, and classifies EV charging customer reviews into six CPP categories. To test its effectiveness, we used SCALER to analyze over 72,000 reviews from customers charging various EV models on different networks across the United States. SCALER achieves a classification accuracy of 92.5%, with an F1 score exceeding 85.7%. By demonstrating real-world applications of SCALER, we enhance the industry’s ability to understand and address CPPs to improve the EV charging experience.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

High spatial resolution charge sensing of quantum Hall states

Charge distribution offers a unique fingerprint of important properties of electronic systems, including dielectric response, charge ordering, and charge fractionalization. Here, we develop an architecture for charge sensing in two-dimensional electronic systems in a strong magnetic field. We probe local change of the chemical potential in a proximitized detector layer using scanning tunneling microscopy, allowing us to infer the chemical potential and the charge profile in the sample. Our technique has both high energy (<0.3 meV) and spatial (<10 nm) resolution exceeding that of previous studies by an order of magnitude. We apply our technique to study the chemical potential of quantum Hall liquids in monolayer graphene under high magnetic fields and their responses to charge impurities. The chemical potential measurement provides a local probe of the thermodynamic gap of quantum Hall ferromagnets and fractional quantum Hall states. The screening charge profile reveals spatially oscillatory response of the quantum Hall liquids to charge impurities and is consistent with the composite Fermi liquid picture close to the half-filling. Our technique also paves the way to map moiré potentials, probe Wigner crystals, and investigate fractional charges in quantum Hall and Chern insulators.

charge sensing↗

A Misalignment Tolerant Magnetic Coupler Design and Implementation for Wireless Charging of Unmanned Aerial Vehicles (UAVs)

Wireless power transfer technology is getting more attention these days as a part of expanded battery charging infrastructure and network at a wide range of power levels. Charging Unmanned aerial vehicles (UAVs) is one wireless charging application, and charging their batteries can be challenging because they have short flight times and are frequently charged. For wireless charging of UAVs, the misalignment performance of the magnetic coupler pads is critical because landing on a charging pad at a perfectly aligned position is difficult and can be time-consuming. Different coil shapes and system structures have been proposed in the literature to overcome this challenge. A new design with a high misalignment tolerance is needed; therefore, to fill this gap, a wireless power transfer system has been designed for a 250 W UAV battery charging system with a new magnetic coupler design. A 3D model of the proposed design was created, and finite element simulations were performed. To prove the proposed design, the magnetic coupler prototypes were developed, and experimental results are presented herein. The misalignment tolerance of the proposed system was observed for various rotational positions of the secondary coil, from 0° to 360°. The results demonstrate that DC–DC efficiency varies between 80% and 85% within full 360° rotation of the receiver coil. This result enables the proposed system to address the misalignment problem for wireless charging of UAVs.

UAVs↗

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗

Unsupervised Detection of SOC Spoofing in OCPP 2.0.1 EV Charging Communication Protocol Using One-Class SVM

The electric vehicles (EVs) market keeps growing globally; thus, it is critical to secure the EV charging communication protocols in order to guarantee reliable and fair charging operations among the customers. The Open Charge Point Protocol (OCPP) 2.0.1 supports the communication between the Electric Vehicle Supply Equipment (EVSE) and Charging Station Management Systems (CSMSs); therefore, it becomes vulnerable to several types of attacks, which aim to jeopardize smart charging, billing, and energy management. Specifically, OCPP 2.0.1 allows the self-reporting of the State of Charge (SOC) values, which makes it vulnerable to spoofing-based cyberattacks, which target manipulating the scheduling priorities, distorting the load forecasts, and extending the charging sessions in an unfair manner. In this paper, we try to address this type of attack by providing a comprehensive analysis of the SOC spoofing attacks and introducing a novel unsupervised detection framework based on the One-Class Support Vector Machine (OCSVM) algorithm. Specifically, two types of attack scenarios are analyzed (i.e., priority manipulation and session extension) by deriving engineered features that capture the nonlinear relationships under normal charging behavior. Detailed simulation-based results are derived by utilizing the DESL-EPFL Level 3 EV charging dataset. Our results demonstrate high F1-score and recall in identifying spoofed SOC values and that the proposed OCSVM model demonstrates superior performance compared to alternative clustering and deep-learning based detectors.

EV charging↗

Charging, aggregation, and electrostatic dispersion of radioactive and nonradioactive particles in the atmosphere

Electrostatic dispersion can significantly impact the microphysical behavior of charged particles and ions until reaching zero space charge. However, although radioactive particles can be strongly charged in air, the influence of electrostatic dispersion has been neglected in understanding their behavior. This study is aimed at investigating the time evolution of the charge and size distributions of radioactive and nonradioactive particles in air and developing simple approaches for applications. With processes involving charging, aggregation, and electrostatic dispersion, a comprehensive population balance model (PBM) has been developed to examine particle charge/size distribution dynamics. It is shown that compared to nonradioactive particles, the charge and size distributions of radioactive particles may evolve differently with time because radioactivity and electrostatic dispersion can significantly affect the charging and aggregation kinetics of the particles. It is found that, after the Fukushima accident, background aerosols in the pathway of radioactive plumes might be highly charged due to ionizing radiation, suggesting that radiation fields may strongly influence in situ measurements of charged atmospheric particles. The comprehensive PBM is simplified, and then the verification and application of the simplified PBMs are discussed. This study provides useful insight into how radioactivity can affect the dynamic behavior of particles in atmospheric systems including radiation sources.

54 ENVIRONMENTAL SCIENCES↗

Revealing Parallel Inter‐ and Intra‐Ligand Charge Transfer Dynamics in [Ru(L) 2 (dppz)] 2+ Molecular Lightswitch with N K‐Edge X‐Ray Absorption Spectroscopy

In photoactive metal complexes the localization of photoexcited charges dictates the site of chemical reactivity, but few studies measure the charge redistribution in these systems with spatial precision. Herein, we track the inter- and intra-ligand charge transfer processes that underpin light-driven charge separation in the well-studied “molecular lightswitch” [Ru(bpy) 2 dppz] 2+ (aqueous [Ruthenium II (2,2′-bipyridine)2(dipyrido[3,2-a:2′,3′-c]phenazine)] 2+ [Cl − ] 2 ) by probing the electronic structure of ligand nitrogen atoms in real-time using ultrafast X-ray absorption spectroscopy and first principles calculations. We confirm the localization of excited electron density on the phenazine N atoms of dppz and we newly identify two parallel electron transfer pathways to populate this state. Sub-70 fs electron transfer to the phenazine portion of dppz is observed and attributed to intra-ligand electron transfer following Ru-to-dppz metal-to-ligand charge transfer (MLCT) excitation. This fast charge transfer was not reported in prior ultrafast studies. The slower (ca. 2 ps) charge transfer reported extensively in time-resolved optical absorption and emission studies is reassigned here to inter-ligand electron “hopping” between nearly isoenergetic ligand moieties following Ru-to-bpy MLCT excitation. In conclusion, the results demonstrate much faster charge separation than previously identified in this well-studied system, highlighting how extended azaacene ligand motifs promote the competitive charge transfer processes needed to drive light-driven electron transfer chemistry.

Donor-acceptor systems↗