Search NASA⌕ Search

SEARCH · Search NASA

Results for “charge selectivity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Methodologies for Design, Characterization and Testing of Electrolytes that Enable Extreme Fast Charging of Lithium-ion Cells

Selection, testing and validation of electrolyte candidates for Li-ion cells are discussed, based on a 10-minute target for extreme fast charge (XFC). A combination of modeling and laboratory measurements create a timely and synergistic approach to identifying candidate electrolyte formulations. Multi-solvent systems provide a balanced set of properties, wherein lower molecular-weight solvents offer reduced viscosity, increased species diffusivity, and mitigation of concentration polarization at high charge rates. Carefully selected formulations can exhibit peak conductivity and usable conductivity range of two to three times that of the baseline EC-EMC (3:7, wt.) + LiPF 6 . Candidates are also chosen based on stability and longevity within the cell environment. Lab testing coincides with property predictions from the Advanced Electrolyte Model (AEM) and a macro-scale cell model. Furthermore, cell testing utilized coin and pouch cells having NMC532 or NMC811 cathodes with graphite electrodes. Results indicate combinations of low-molecular weight solvents are key for fast-charge electrolytes as they extend the useful conductivity range to both low and higher salt concentrations, and possess higher self-diffusivities compared to conventional solvents. This reduces impacts from concentration polarization. The choice of electrolyte also influences the tendency for lithium metal deposition at the anode, as showcased by experimental and modeling results herein.

25 ENERGY STORAGE↗
DOE OSTI2021

C3PU:Real-Time Predictive Charge Control Software for Battery Management Systems (Code for Charge Control and Predictive Unit) [SWR-21-48]

C3PU sets up a model predictive control formulation for the optimal charging control of battery packs and can be deployed for real-time operation on an embedded microprocessor. C3PU uses electrochemical and thermal models of battery packs to predict the charging trajectories of the battery pack over a time horizon under different operating conditions. It then selects the optimal charging trajectory such that a pre-defined objective is minimized, which in the present state of the code is to minimize the charging duration of the battery pack. The optimal charging trajectory is obtained by solving an underlying mathematical problem. However, C3PU is flexible to incorporate other charging objectives. The underlying battery models can be swapped as well, as long as they follow certain mathematical properties. Mathematically, optimal control problems (in this case, optimally controlling the charging current of the battery pack) are computationally expensive. C3PU implements advanced numerical techniques, namely pseudo-spectral optimization, to reduce the computational burden of the underlying problem to solve. This allows for the problem to be solved in real-time in an embedded system. Once the optimal charging trajectory is computed over a time horizon, C3PU can package such data and send it out via appropriate communication protocols.

Mishra, Partha↗
DOE OSTI2025

Dopant Sensitive Electrolytic Etching of Germanium with High Selectivity

Abstract The enhanced charge carrier mobility and photon absorption compared to silicon make germanium attractive for next-generation photo diodes. However, the complex oxidation behavior of germanium challenges dopant-dependent selective etching that is desired for the fabrication of backside imaging architectures. This report demonstrates electrolytic wet etching of p-doped germanium which proceeds up to 17,500x faster than etching of intrinsic germanium. Homoepitaxially grown layers of germanium were electrolytically etched in potassium hydroxide over a range of biases. Intermittent acquisition of cyclic voltammetry spectra during etching has suppressed the formation of electric double layers, maintained appreciable etch rates, and allowed for in operando process control. The observed etch rates scaled with dopant concentration. An effective etch rate of germanium removal of 2.100±0.044 µm/min was accomplished for a boron dopant concentration of 6E18cm-3. For nominally intrinsic germanium, however, an effective etch rate of only 0.00012±0.00011 µm/min was observed. A series of systematic electrolytic etch experiments have revealed the transfer of 4 electrons per germanium atom removed.

Wood, Joseph G.↗
DOE OSTI2024

Reconstruction and Selection of Neutrino Interactions in MicroBooNE using Deep Convolutional Neural Networks

In this document, we describe a new reconstruction workflow developed for the MicroBooNE experiment. It features the use of Deep Convolutional Neural Networks trained to recognize key structures within the data sufficient for the 3D reconstruction of neutrino interactions within the detector. As a test of the reconstruction utility, the products of the reconstruction workflow are used to select inclusive charged-current (CC) $\nu_e$ and $\nu_\mu$ interactions in both simulated and real MicroBooNE data. In simulation, our $\nu_e$ and $\nu_\mu$ selections achieve an efficiency of 57% and 68\%, respectively, with a purity of 91% and 96%, respectively. We find that these selections are competitive with the inclusive selections used for the most recent MicroBooNE LEE searches. In particular, the CC-$\nu_e$ inclusive selection efficiency improves by over 20% while also improving sample purity. As a first step in quantifying potential bias, the data and Monte Carlo expectati ons are compared for both selections using the MicroBooNE open data. Within statistical and systematic uncertainties, both the electron and muon CC-inclusive event samples agree. A comparison of the real data events chosen by our work and another reconstruction framework shows that the two analyses each identify a sizeable fraction of events the other does not. This suggests that future analyses integrating the strengths of each could lead to combined gains. This work demonstrates, for the first time on real LArTPC data, state-of-the-art neutrino interaction reconstruction centered around deep learning algorithms.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Exchange Coupling Determines Metal-Dependent Efficiency for Iron- and Cobalt-Catalyzed Photochemical CO 2 Reduction

Catalysts promoting multielectron charge delocalization offer selectivity for the CO 2 reduction reaction (CO 2 RR) over the competing hydrogen evolution reaction. Here, we show metal–ligand exchange coupling as an example of charge delocalization that can determine the efficiency for photocatalytic CO 2 RR. A comparative evaluation of iron and cobalt complexes supported by the redox-active ligand tpyPY2Me establishes that the two-electron reduction of [Co(tpyPY2Me)] 2+ ([Co] 2+ ) occurs at potentials 770 mV more negative than the [Fe(tpyPY2Me)] 2+ ([Fe] 2+ ) analogue by maximizing the exchange coupling in the latter compound. The positive shift in the reduction potential promoted by metal–ligand exchange coupling drives [Fe] 2+ to be among the most active and selective molecular catalysts for photochemical CO 2 RR reported to date, maintaining up to 99% CO product selectivity with total turnover numbers (TONs) and initial turnover frequencies exceeding 30,000 and 900 min –1 , respectively. In contrast, [Co] 2+ shows much lower CO 2 RR activity, reaching only ca. 600 TON at 83% CO product selectivity under similar conditions accompanied by rapid catalyst decomposition. Further, the spin density plots of the two-electron reduced [Co] 0 complex implicate a paramagnetic open-shell doublet ground state compared to the diamagnetic open-shell singlet ground state of reduced [Fe] 0 , rationalizing the observed negative shift in two-electron reduction potentials from the [M] 2+ species and lowered CO 2 RR efficiency for the cobalt complex relative to its iron congener. This work emphasizes the contributions of multielectron metal–ligand exchange coupling in promoting effective CO 2 RR and provides a starting point for the broader incorporation of this strategy in catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Nanostructured polyelectrolytes for ion-selective membranes

Nanostructured polyelectrolyte bilayers deposited by Layer-by-Layer deposition on nanoporous membranes can be selectively crosslinked to modify the polyelectrolyte charge density and control ionic selectivity independent of ionic conductivity. For example, the polyelectrolyte bilayer can comprise a cationic polymer layer, such as poly(ethyleneimine), and an anionic polymer layer, such as poly(acrylic acid). Increasing the number of bilayers increases the cation selectivity when the poly(ethyleneimine) layer is crosslinked with glutaraldehyde. Crosslinking the membranes also increases the chemical and mechanical strength of the polyelectrolyte films. This controllable and inexpensive method can be used to create ion-selective and mechanically robust membranes on porous supports for a wide range of applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Interfacial electroneutrality controls transport of asymmetric salts through charge-patterned mosaic membranes

Membranes that selectively enhance target solute permeation while rejecting competing species are essential for precision separations. This study introduces charge-patterned mosaic membranes (CMMs) that selectively transport divalent asymmetric salts by leveraging a net-neutral membrane–solution interface. This mechanism, dictated by the charge ratio of positive and negative domains on the membrane surface and the balance of cations and anions in the salt, is supported by analytical, numerical, and experimental results. Analytical solutions identified cationic domain coverages (f + ) of 33%, 50%, and 66% as optimal for the selective transport of +2:−1 salts, +1:−1 salts, and +1:−2 salts, respectively, under conditions where the pattern size (L) is significantly larger than the Debye length. Numerical simulations and experiments using CMMs with alternating charged-stripes inkjet-printed onto nanostructure copolymer substrates confirmed these findings. By varying stripe widths to control f + , pressure-driven filtration experiments demonstrated selective enrichment of MgCl 2 and K 2 SO 4 at the predicted f + values, with deviations from these values leading to salt rejection. These results highlight the pivotal role of a net-neutral interface in enabling asymmetric salt enrichment. This study positions CMMs as a versatile platform for tuning ion selectivity, addressing challenges in resource recovery, water treatment, and precision separations.

additive manufacturing↗
DOE OSTI2024

Univariate Prediction of Hammett Parameters and Select Relative Reaction Rates Using Loewdin Atomic Charges

Loewdin charges from density functional theory calculations were used here to obtain general, univariate linear correlations for the prediction of experimental Hammett parameters and relative reaction rates. While previous studies have established that Hirshfeld and CM5 charges perform strongly as univariate predictors, the near-ubiquitous Loewdin charges have not yet been evaluated. To this end, we assess the predictive capability of Loewdin charges for three chemical systems. First, we show that Loewdin charges outperform Hirshfeld and CM5 charges for Hammett parameter prediction. Second, we see that Loewdin charges generally perform comparably to Hirshfeld charges for predicting the relative rates of olefin cleavage by photoexcited nitroarenes. The single case of poor correlation, between relative rates and the Loewdin charges on nitrogen sites, is ameliorated when considering the net charge on the NO 2 group. Third, we show that Loewdin, Hirshfeld, and CM5 charges all perform very well for generating correlations for relative reaction rates for C–H activation of 9-(4-X-phenyl)-9H-fluorene substrates by a transition metal catalyst. The equations generated throughout the study enable the prediction of Hammett parameters and relative reaction rates. Finally, these tools can accelerate synthetic and experimental studies by enabling the in silico prediction of uncharacterized chemical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

EVs@Scale: NextGen Profiles EVSE Characterization 2025

As part of the U.S. DOE EVs@Scale consortium, the Next-Generation Profiles (NextGen Profiles [NGP]) project presents analysis and results from the characterization of high-power conductive and wireless charging infrastructure. High Power Charging equipment is capable of recharging electric vehicle traction batteries at power levels of 200KW and above. Electric Vehicle Service Equipment (EVSE) characterization involves testing over a wide range of DC charging currents and voltages during nominal and off-nominal conditions. This testing allows for a better understanding of the impact that high-power charging will have on the electric grid. A common set of standard test plans, procedures, and data requirements were applied to the characterization in this document with minor updates and improvements. This report covers all conductive characterization activities performed between October 2024 and September 2025 on the Delta Electronics 350KW Electric Vehicle Charging System, consisting of power cabinet model EIDN-U350KTA01 and dispenser model EIDD-U350SSUUAEG-350.Key Findings include: Output regulation, Efficiency and power factor, Load management, Grid Resilience, Smart Charge Management (SCM) performance, Thermal control system performance, Multi-port simultaneous charging performance, and Selected performance comparisons with other EVSEs characterized in the NextGen Profiles project. Hot and cold temperature testing was not conducted on the Delta 350KW due to laboratory limitations. Future research could include continued testing the Delta hardware under off-nominal temperature conditions including multi-port/multi-session simultaneous charge testing, in addition to collecting data on other high-power conductive chargers to augment.

25 ENERGY STORAGE↗
DOE OSTI2022

Nanoscale Measurements of Charge Transfer at Cocatalyst/Semiconductor Interfaces in BiVO 4 Particle Photocatalysts

Semiconductor photocatalyst particles convert solar energy to fuels like H 2 . The particles are often assumed to provide crystalline-facet-dependent electron-hole separation. A common strategy is to deposit HER electrocatalyst on electron-selective facets and OER electrocatalyst on hole-selective facets. A precise understanding of how charge-carrier-selective contacts emerges and how they rationally designed, however, is missing. Using a combination of ex-situ and in-situ conducting-AFM experiments and new ionomer/catalyst-semiconductor test structures, we show how heterogeneity in charge-carrier selectivity can be measured at the nanoscale. We discover that the presence of interface water/electrolyte is critical to induce hole selectivity between the CoO x water-oxidation catalyst and the BiVO 4 light absorber. pH-dependent measurements suggest that negative surface charge on the semiconductor is central to inducing hole selectivity. Furthermore, the work also demonstrates a new approach to control local pH and introduce water using thin-film ionomers compatible with conductive-AFM measurements.

14 SOLAR ENERGY↗
DOE OSTI2023

Data-Driven Validation of NOvA's Convolutional Neural Network for Electron (Anti)Neutrino Selection

NOvA is a long-baseline neutrino oscillation experiment, designed to make measurements of several oscillation parameters using muon neutrino disappearance and electron neutrino appearance. It consists of two functionally equivalent detectors and utilizes the Fermilab NuMI neutrino beam. NOvA uses a convolutional neural network for particle identification of electron neutrino events with a validation process that includes several data-driven techniques. These Muon Removed studies ensure that our classifier performs the same on data as it does on simulation. In particular, Muon Removed Electron-Added studies involve selecting muon neutrino charged current events from both data and simulation and replacing the muon with a simulated electron of similar energy. For Muon Removed Bremsstrahlung and Muon Removed Decay-in-Flight studies, we remove muonic hits from cosmic muons that have either experienced Bremsstrahlung radiation or decayed in flight, producing samples of pure electromagnetic showers. Each of these electron neutrino-like samples are then evaluated by our classifier to obtain selection efficiencies. Our most recent analysis showed good agreement in the electron selection efficiency between data and simulation using these techniques. Furthermore, these cross-checks can be extended to corrections to our predicted electron neutrino signal. The impact of one such set of corrections on the overall analysis results were also evaluated in thesis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Enhancing charge ratio sensitivity to hadronization effects via jet selections on resolved SoftDrop splitting

The study of quantum chromodynamics (QCD) at ultrarelativistic energies can be performed in a controlled environment through lepton-hadron deep inelastic scatterings. In such collisions, the high-energy partonic emissions that follow from the ejected hard partons are accurately described by perturbative QCD. However, the lower energy scales at which quarks and gluons experience color confinement, i.e., hadronization mechanism, fall outside the validity regions for perturbative calculations, requiring phenomenological models tuned to data to describe it. As such, hadronization physics cannot be currently derived from first principles alone. Monte Carlo event generators are useful tools to describe these processes as they simulate both the perturbative and the nonperturbative interactions, with model-dependent energy scales that control parton dynamics. This work employs jets—experimental reconstructions of final-state particles likely to have a common partonic origin—to inspect this transition further. Although originally proposed to circumvent hadronization effects, we show that jets can be utilized as probes of nonperturbative phenomena via their substructure. The charge correlation ratio was recently shown to be sensitive to hadronization effects. Our work further improves this sensitivity to nonperturbative scales by introducing a new selection based on the relative placement of the within the clustering tree, defined as the unclustering that resolves the jet’s leading charged particles. Published by the American Physical Society 2025

Apolinário, Liliana (ORCID:0000000335009681)↗
DOE OSTI2021

Correlations of azimuthal anisotropy Fourier harmonics with subevent cumulants in p Pb collisions at s N N = 8.16 TeV

Event-by-event long-range correlations of azimuthal anisotropy Fourier coefficients ($v_n$) in 8.16 TeV p Pb data, collected by the CMS experiment at the CERN Large Hadron Collider, are extracted using a subevent four-particle cumulant technique applied to very low multiplicity events. Each combination of four charged particles is selected from either two, three, or four distinct subevent regions of a pseudorapidity range from -2.4 to 2.4 of the CMS tracker, and with transverse momentum between 0.3 and 3.0 GeV. Using the subevent cumulant technique, correlations between $v_n$ of different orders are measured as functions of particle multiplicity and compared to the standard cumulant method without subevents over a wide event multiplicity range. At high multiplicities, the $v_2$ and $v_3$ coefficients exhibit an anticorrelation; this behavior is observed consistently using various methods. The $v_2$ and $v_4$ correlation strength is found to depend on the number of subevents used in the calculation. As the event multiplicity decreases, the results from different subevent methods diverge because of different contributions of noncollective or few-particle correlations. Correlations extracted with the four-subevent method exhibit a tendency to diminish monotonically toward the lowest multiplicity region (about 20 charged tracks) investigated. These findings extend previous studies to a significantly lower event multiplicity range and establish the evidence for the onset of long-range collective multiparticle correlations in small system collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Application of Wireless Charging at Seaports for Range Extension of Drayage Battery Electric Trucks

Even though heavy-duty battery electric trucks (BETs) have become commercially available, their range limitation still hinders widespread adoption. Drayage has been regarded as a suitable application for early BETs due to typically having limited daily mileage. However, drayage operation can vary widely and some form of range extension may still be needed for BETs operating in this application. Here, in this paper, wireless charging at port terminals is proposed for this purpose. Potential wireless charging zones at port terminals are identified, and efficacy of wireless charging to extend BET range in drayage operation is verified by simulating the activity of 20 BETs from a drayage operator serving the ports of Los Angeles and Long Beach, using a microscopic BET energy consumption model. Furthermore, an optimization problem is formulated for optimal wireless charging zone planning from the port authority's perspective, considering subsets of the identified zones, and charging power options to choose from, for different budget ranges. In this context, zone planning means determining which areas of the port terminals should be selected for installing wireless charging systems, and what level of charging power should be for each selected zone's system. For each budget range, the optimization problem is solved using genetic algorithm to determine an optimal zone plan that provides the maximum amount of energy through wireless charging per unit cost of installation. The results show that wireless charging can aid improving activity completion of the simulated fleet by 5%, and further optimizing the zone plan can achieve similar performance with lower cost.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Search for long-lived heavy neutral leptons in proton-proton collision events with a lepton-jet pair associated with a secondary vertex at $\sqrt{s}$ = 13 TeV

A search for long-lived heavy neutral leptons (HNLs) using proton-proton collision data corresponding to an integrated luminosity of 138 fb −1 collected at $\sqrt{s}$ = 13 TeV with the CMS detector at the CERN LHC is presented. Events are selected with a charged lepton originating from the primary vertex associated with the proton-proton interaction, as well as a second charged lepton and a hadronic jet associated with a secondary vertex that corresponds to the semileptonic decay of a long-lived HNL. No excess of events above the standard model expectation is observed. Exclusion limits at 95% confidence level are evaluated for HNLs that mix with electron and/or muon neutrinos. Limits are presented in the mass range of 1–16.5 GeV, with excluded square mixing parameter values reaching as low as 2 × 10 −7 . For masses above 11 GeV, the presented limits exceed all previous results in the semileptonic decay channel, and for some of the considered scenarios are the strongest to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Performance efficient macromolecular mechanics via sub-nanometer shape based coarse graining

Dimensionality reduction via coarse grain modeling is a valuable tool in biomolecular research. For large assemblies, ultra coarse models are often knowledge-based, relying on a priori information to parameterize models thus hindering general predictive capability. Here, we present substantial advances to the shape based coarse graining (SBCG) method, which we refer to as SBCG2. SBCG2 utilizes a revitalized formulation of the topology representing network which makes high-granularity modeling possible, preserving atomistic details that maintain assembly characteristics. Further, we present a method of granularity selection based on charge density Fourier Shell Correlation and have additionally developed a refinement method to optimize, adjust and validate high-granularity models. We demonstrate our approach with the conical HIV-1 capsid and heteromultimeric cofilin-2 bound actin filaments. Our approach is available in the Visual Molecular Dynamics (VMD) software suite, and employs a CHARMM-compatible Hamiltonian that enables high-performance simulation in the GPU-resident NAMD3 molecular dynamics engine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Using X-ray free-electron lasers for spectroscopy of molecular catalysts and metalloenzymes

The metal centers in metalloenzymes and molecular catalysts are responsible for the rearrangement of atoms and electrons during complex chemical reactions, and they enable selective pathways of charge and spin transfer, bond breaking/making and the formation of new molecules. Mapping the electronic structural changes at the metal sites during the reactions gives a unique mechanistic insight that has been difficult to obtain to date. The development of X-ray free-electron lasers (XFELs) enables powerful new probes of electronic structure dynamics to advance our understanding of metalloenzymes. The ultrashort, intense and tunable XFEL pulses enable X-ray spectroscopic studies of metalloenzymes, molecular catalysts and chemical reactions, under functional conditions and in real time. In this Technical Review, we describe the current state of the art of X-ray spectroscopy studies at XFELs and highlight some new techniques currently under development. With more XFEL facilities starting operation and more in the planning or construction phase, new capabilities are expected, including high repetition rate, better XFEL pulse control and advanced instrumentation. For the first time, it will be possible to make real-time molecular movies of metalloenzymes and catalysts in solution, while chemical reactions are taking place.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗