Charge Profiles Research Articles

88-OR: Targeted Drug Delivery to Human ß-Cells Using Novel Nanocapsule Delivery Vehicle for T1D Treatment

In type 1 diabetes (T1D), autoreactive immune cells destroy insulin secreting β-cells in pancreatic islets. Islet transplantation shows promise in restoring glucose homeostasis without exogenous insulin; however, long-term graft survival remains a critical barrier to the success of this treatment. Therapies aimed to protect or proliferate endogenous β-cells have off target affects and require targeted delivery to improve efficacy. We have developed a nanocapsule (NC) delivery system to specifically target and deliver cargo to human β-cells. We hypothesize NCs will selectively be taken up by human β-cells and deliver therapeutic cargo. NCs were synthesized with a water in oil emulsion evaporation technique. NCs were coated via ionic interactions with ectonucleoside triphosphate diphosphohydrolase 3 (ENTPD3) antibody, a human β-cell specific marker or Exendin-4 conjugated to hyaluronic acid (HA-Ex4). NC size, size distribution, charge, stability, and drug release profiles were determined. NCs loaded with pentamidine (PTM) or Cy5 were cultured for 24-168h with human iPSC-derived β-cells (sBC) or injected into the tail vein of NOD-SCID mice. Confocal microscopy confirmed delivery of cargo to β-cells and pancreatic islets, viability, and cytotoxicity. NCs were 271 ± 7nm in size with excellent size homogeneity (polydispersity index 0.06 ± 0.03, n=3). NCs displayed a sustained release of cargo for >45 days (n=5). In vitro, we observed no cytotoxicity of NCs up to 168h (n=3) and a significant increase in β-cell death with PTM loaded ENTPD3 coated NCs compared to controls at 24 (p<0.001, n=4) and 72h (p<0.01, n=4). sBCs treated with PTM loaded ENTPD3 coated NCs had more insulin+ dead cells (88 ± 4%) than controls (p<0.01, n=4). ENTPD3 or HA-Ex4 NCs were internalized into sBCs in vitro and pancreatic islets in vivo respectively. Our data shows long term stability and in vivo targeting of NCs to β-cells and supports use of our NCs for targeted delivery of therapeutics to human β-cells to treat T1D. Disclosure J.Collins: None. K.Holcomb: None. A.Ocampo: None. A.Shilleh: None. H.A.Russ: Advisory Panel; Sigilon Therapeutics, Inc., Consultant; Prellis, Minutia, Eli Lilly and Company. N.L.Farnsworth: None. Funding JDRF (1-INO-2022-1231-S-B); National Institutes of Health (P30-DK116073)

A PV variability tolerant generic multifunctional control strategy for battery energy storage systems in solar PV plants

This paper proposes a multifunctional control strategy for battery energy storage systems (BESSs) in solar photovoltaic (PV) plants to avoid the unacceptable PV-power ramp-rate caused by PV variability. In addition to the PV variability tolerant ramp-rate control, the proposed multifunctional BESS control strategy is capable of maintaining a user-specified charging profile to store excess PV power while providing backup power support and charge maintenance, by accommodating diverse control functions time to time. Four control functions, namely, Rest (RST), Surplus Energy Storage (STR), Back-up Power Support (SPT) and Charge Maintenance (CMT) functions, are proposed in this article. Besides, extendibility of the proposed multifunctional strategy is presented by adding two action strategies – one with the STR function and another with the SPT function. Validation of the proposed control strategy is conducted by using real historical data from a utility-scale solar PV plant located in Queensland, Australia. Numerical analyses show that the strategy can successfully keep the PV ramp-rate within specified limit along with the user specified charge profile. Further, exploiting the real-field data, the proposed strategy is demonstrated through a real-time co-simulation study conducted in a MATLAB interfaced RSCAD-RTDS platform that can be used as Digital Twin (DT) for the PV plant.

An adaptive virtual capacitive droop for hybrid energy storage system in DC microgrid

Hybrid energy storage system (HESS) is an integral part of DC microgrid as it improves power quality and helps maintain balance between energy supply and demand. The battery and supercapacitor of HESS differ in terms of power density and dynamic response and appropriate control strategies are required to share power among these storage elements. This paper presents an adaptive virtual capacitive droop for supercapacitor in HESS. A switched-controlled capacitor (SCC) is used in series with a supercapacitor to change capacitance droop coefficient which affects the power absorbed and released by the storage element. The SCC control uses state of charge (SoC) balancing mechanism to improve charge profile by reducing the peak and settling time. Moreover, SCC is fully soft switched to reduce switching losses. A detailed design of controller is discussed for HESS. Compared to the conventional supercapacitor control where the SoC balancing is ensured in secondary control, the proposed scheme improves SoC profile of supercapacitor and ensures that it rapidly contributes power during transients of the microgrid. Simulations performed in PSCAD/EMTDC highlight the superior performance of this control over the conventional scheme.

Accreting neutron stars: composition of the upper layers of the inner crust

Abstract We model the nuclear evolution of an accreted matter as it sinks toward the stellar center, in order to find its composition and equation of state. To this aim, we developed a simplified reaction network that allows for redistribution of free neutrons in the inner crust to satisfy the recently suggested neutron hydrostatic and diffusion equilibrium condition. We analyse the main reaction pathways for the three representative thermonuclear ash compositions: Superburst, Kepler, and Extreme rp. In contrast to the previous results, which neglect redistribution of free (unbound) neutrons in the inner crust, the most significant reactions in our calculations are neutron captures and electron emissions. The pycnonuclear fusion plays some role only for Kepler ashes. For the direct application of our results in astrophysical codes we present profiles of the average charge, 〈Z〉, impurity parameter, Qimp and equation of state for a set of models, parametrized by the pressure at the outer-inner crust interface. Typically, for Superburst ashes Qimp ≈ 1 − 4, while for Kepler ashes Qimp decreases from ≈23 at the outer-inner crust interface to ≈5 at the end of our simulation (the corresponding density equals ρdc ≈ 2 × 1012 g cm−3). At the same time, for Extreme rp ashes Qimp remains large ≈30 − 35 in the considered inner crust region. Our results are important for modeling the thermal relaxation of transiently accreting neutron stars after the end of the outburst.

PEA Signal Simulation Using Multiple Viscoelastic Relaxation Model for Determination of Acoustic Attenuation and Velocity Dispersion

Acoustic attenuation in polymer insulators prevents the accurate determination of space charge profiles measured by pulsed electroacoustic (PEA) measurements. A PEA signal simulation is developed on the basis of a multiple viscoelastic relaxation model, which can determine acoustic attenuation and sound velocity dispersion in polymer insulators. To implement the multiple relaxation model, we use an analogy between the viscoelastic and dielectric relaxations. The Kelvin–Voigt model is used as a single relaxation model, and the Cole–Cole model is used as a multiple relaxation model. The simulation based on the Cole–Cole model as a multiple relaxation model can accurately reproduce measured PEA signals. The distortion of a PEA measured space charge profile due to acoustic attenuation and velocity dispersion is also discussed. The charge profile calculated using the multiple relaxation model is in good agreement with the peak value, width, and tail shape obtained in experiments.

Doping Density Extraction of Plasma Treated Metal Oxide Thin Film Diodes by Capacitance–Voltage Analysis

AbstractHigh quality thin film p‐n junction diodes with high rectification ratios and low ideality factors have been fabricated from metal oxides, such as amorphous oxide semiconductors (AOSs), and characterized. Plasma treatment of interfaces has been demonstrated to improve devices made from AOSs, using current–voltage (I–V) measurements. However, capacitance–voltage (C–V) measurements of the devices have been scarcely reported in the literature. Therefore, the focus of this work is characterization of cuprous oxide (Cu2O)/amorphous zinc‐tin oxide (a‐ZTO) thin film heterojunction diodes using C–V analysis. Performance differences of plasma‐treated and untreated diodes that are difficult to observe in I–V analysis are more prominent in C–V analysis. Moreover, C–V analysis allows extraction of charge density profiles, which is a measure of the defect state density that led to intrinsic doping. The variation of doping densities of the untreated diode across the full range of applied reverse bias is shown to be up to 2 orders of magnitude, while those of the treated diodes are within a factor of 10 only. Junction charge profiles, interfacial charge depletion, and accumulation that are key features of rectifying diodes are shown to be clearly distinct between untreated, nitrogen‐treated, and oxygen‐treated diodes, thus explaining why oxygen‐treated diodes are superior.

Heat Generation during the First Activation Cycle of Li-Ion Batteries with Li- and Mn-Rich Layered Oxides Measured by Isothermal Micro-Calorimetry

Using isothermal micro-calorimetry, we investigate the heat generation of lithium- and manganese-rich layered oxides (LMR-NCMs) during the first cycle in which LMR-NCM exhibits a pronounced voltage hysteresis leading to a low energy efficiency (≈73%). In the first charge, LMR-NCM shows a unique voltage plateau at ≈4.5 V where irreversible structural rearrangements lead to an activation of the material as well as a large voltage hysteresis. We found that only a fraction of the lost electrical work (≈43%) is converted into waste heat. Thereby, the heat flow profile of the first charge is unique and shows considerable heat generation during the voltage plateau. With complementary electrochemical methods, contributions of conventional sources of heat, i.e., because of polarization and entropy, are determined. However, they do not cause the considerable generation of heat during the voltage plateau. Our results therefore suggest that the structural rearrangements during activation lead to a significant generation of heat. In window-opening experiments, we demonstrate that the activation is a gradual process and that the heat generated during the first discharge is directly linked to the extent of activation during the preceding charge. We also investigate the effect of the degree of overlithiation on the heat generated during activation.

Composition dependent charge retention in amorphous HfxAl1−xOy dielectric layers

Charge trapping properties in dielectric materials serve as a ground principle in data storage devices called NAND flash. High-density nonvolatile storage requires deep trapping centers and localized trapped charge distribution. Current NAND flash technology relies on Si3N4 during the development history, and further development requires a higher dielectric constant material with compatible deep trapping centers and localized trapped charge profiles. In this work, charge trapping properties of HfxAl1−xOy dielectric layers with various compositions are investigated by modeling retention characteristics with trap energy and μτ product, where the former represents the trapping center depth and the latter represents the trapped charge profiles. Comparing the conventional Si3N4, HfxAl1−xOy dielectric layer with a low Hf content may improve long-term charge retention in NAND flash, while a localized trapped charge profile needs improvement to be compatible with Si3N4.

Analysis of Space Charge Signal Spatial Resolution Determined with PEA Method in Flat Samples including Attenuation Effects

The constant development of the electrical engineering sector, especially in the transmission of electrical energy under high-voltage direct current (HVDC), requires research on new insulation materials and investigations of physical phenomena under ultrahigh electrical fields in solid dielectrics. One of the current problematic issues is the formation of space charge in HV insulation systems, which affects the operational electrical field distribution and can lead to faster insulation degradation. There are several problems that have to be considered before every space charge measurement, such as the attenuation and dispersion of sound waves in tested dielectric materials, reflections at the interfaces, and the spatial resolution of the measured charge profile. The spatial resolution is one of the most important technical factors of the PEA measurement stand. The spatial resolution, as it is assumed, depends on several factors, such as the width of the pulser and the pulse rise time, the thickness of the piezoelectric sensor, and the dispersion of the tested material. The article presents the laboratory measurement results of the impact of pulser parameters, such as pulse width and rise time, and sensor thickness on the equivalent thickness of the measured net charge layer corresponding to the resolution of the method. The dispersion in the tested LDPE material is also presented and analysed. The results show that with an increase in the pulser rise time, a higher resolution of the pea method can be achieved.

Modeling charge cloud dynamics in cross strip semiconductor detectors

When a γ-ray interacts in a semiconductor detector, the resulting electron–hole charge clouds drift towards their respective electrodes for signal collection. These charge clouds will expand over time due to both thermal diffusion and mutual electrostatic repulsion. Solutions to the resulting charge profiles are well understood for the limiting cases accounting for only diffusion and only repulsion, but the general solution including both effects can only be solved numerically. Previous attempts to model these effects have taken into account the broadening of the charge profile due to both effects, but have simplified the shape of the profile by assuming Gaussian distributions. However, the detailed charge profile can have important impacts on charge sharing in multi-electrode strip detectors. In this work, we derive an analytical approximation to the general solution, including both diffusion and repulsion, that closely replicates both the width and the detailed shape of the charge profiles. This analytical solution simplifies the modeling of charge clouds in semiconductor strip detectors.

Evaluation of space charge distribution under a divergent electric field by combining experiment and simulation

Under divergent electric fields, space charge is locally accumulated and controls the initiation and evolution of insulation degradation phenomena, such as electrical trees and partial discharge. The space charge profiles provide crucial information for evaluating the insulation performance. However, the existing space charge measurement methods are not directly applicable under divergent electric fields. In this paper, a method combining experiment and simulation is proposed to evaluate the space charge distribution around a needle electrode. An experimental system is established, and the acoustic waves are measured with a hydrophone placed on the symmetric axis. In order to obtain the space charge distribution, the space charge injection process is simulated using the bipolar charge transport model to reduce the freedom of the distribution. Then, calculations are made for the acoustic waves produced by the simulated space charge distributions. Using the signals without the contribution of internal charge, a correspondence between the experiment and simulation is established. For each experimental signal, the matched calculated signal is obtained using the zero-crossing time as a reference. A perfect match between them is presented after the amplitude compensation, which indicates that the space charge distribution in the experiment is identical to that in the simulation model.

An All-1.8-V-Switch Hybrid Buck–Boost Converter for Li-Battery-Operated PMICs Achieving 95.63% Peak Efficiency Using a 288-m DCR Inductor

In this article, a hybrid step-up/down converter is presented with improved efficiency, smaller form factor, and enhanced reliability for Li-ion-battery-operated power management integrated circuits. Utilizing a hybrid structure with one inductor and two flying capacitors, the dual-path buck–boost (DPBB) converter reduces the average inductor current, switch currents, and the required blocking voltage for the power switches. To support a mid-3-V output from a Li-ion battery, the converter can be realized using 1.8-V rated devices, solely. In addition, the DPBB facilitates a continuous input and output current delivery, thus improving the reliability of the converter significantly. Besides, leveraging the Li-ion battery charge profile, the topology provides an optimal performance during downconversion, in which the converter operates for most of its usage time. With reduced inductor current and smaller voltage rated switches, a more compact inductor with a large dc resistance (DCR) can be used to maintain similar efficiency, which, in turn, helps reduce the converter board space and associated manufacturing cost. Fabricated in a 180-nm BCD technology, the prototype achieves a peak efficiency of 95.63% even for a large 288-m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Omega$</tex-math></inline-formula> inductor DCR with an output ripple below 20 mV for a load current up to 700 mA.

Dynamic tradable credit scheme for multimodal urban networks

A Tradable Credit Scheme (TCS) is a demand management policy aiming for more sustainable travel behavior. The regulator defines the total credit cap and the credit distribution; it also determines the credit charges for each travel alternative at different times of the day, which modifies the perceived users’ costs. The credit price is determined by trading of credits between travelers. Defining the credit scheme at the urban level and estimating its impacts on user travel decisions and the network congestion dynamics is challenging. We propose a framework wherein travelers change their departure times and choose between solo car driving, Public Transportation (PT), and carpooling to complete their trips under a dynamic TCS, meaning the credit charge is time-dependent. A multimodal macroscopic traffic simulator based on a generalized bathtub model captures the congestion dynamics for the different transport modes. Additionally, we consider different values of time, trip lengths, and desired arrival times for the demand profile.The proposed TCS minimizes the total travel cost, (the sum of all travelers’ travel costs) and the carbon emissions by solving an optimization problem through an iterative method, including an inner loop that updates the users’ choices and credit price under the stochastic user equilibrium principle; and an outer loop that updates the credit charge profile. The methodology is implemented and applied to a realistic test case in Lyon (France). The dynamic TCS profiles result in 36% fewer carbon emissions than static TCS for a total travel cost reduction of 19%. Besides, 94% of the travelers benefit from the TCS as their user costs decrease in the case study. The final results are compared with a more advanced simulation framework, which is too computationally expensive to find the optimal TCS. The proposed TCS is effective with refined traffic dynamics representation.

Two-Dimensional Capillary Zone Electrophoresis-Mass Spectrometry: Intact mAb Charge Variant Separation Followed by Peptide Level Analysis Using In-Capillary Digestion.

Characterization of charge heterogeneity is an essential pillar for pharmaceutical development and quality control of therapeutic monoclonal antibodies (mAbs). The highly selective and commonly applied capillary zone electrophoresis (CZE) method containing high amounts of ε-aminocaproic acid (EACA) provides a detailed and robust charge heterogeneity profile of intact mAb variants. Nevertheless, the exact location of protein modifications within these charge profiles remains ambiguous. Electrospray ionization mass spectrometry (ESI-MS) is a promising tool for this purpose; however, EACA is incompatible with electrospray. In this context, we present a two-dimensional CZE-CZE-MS system to combine efficient charge variant separation of intact mAbs with subsequent peptide analysis after in-capillary digestion of selected charge variants. The first dimension is based on a generic CZE(EACA) method in a fused silica capillary. In the second dimension, a neutral-coated capillary is used for in-capillary reduction and digestion with Tris(2-carboxyethyl)phosphine (TCEP) and pepsin, followed by CZE separation and MS/MS-characterization of the resulting peptides. The setup is demonstrated using stressed and nonstressed mAbs where peaks of basic, main, and acidic variants were transferred in a heart-cut fashion, digested, and characterized on the peptide level. Sequence coverages of more than 90% were obtained for heavy chain (HC) and light chain (LC) for four different mAbs, including low-abundance variants (<2% of the main peak). Frequently observed modifications (deamidation, oxidation, etc.) could be detected and localized. This study demonstrates a proof-of-concept for identification and localization of protein modifications from CZE charge heterogeneity profiles and, in this way, is expected to support the development and quality control testing of protein pharmaceuticals.

Comparison of Pulsed Electroacoustic Measurements and AF-NUMIT3 Modeling of Polymers Irradiated with Monoenergetic Electrons

Successful spacecraft design and charging mitigation techniques require precise and accurate knowledge of charge deposition profiles. This paper compares models of charge deposition and transport using a venerable deep dielectric charging code, AF-NUMIT3, with direct measurements of charge profiles via pulsed electroacoustic (PEA) measurements. Eight different simulations were performed for comparison to PEA experiments of samples irradiated by 50 or 80 keV monoenergetic electrons in vacuum and at room temperature. Two materials, polyether-ether ketone (PEEK) and polytetrafluoroethylene (PTFE), were chosen for their very low conductivities so that minimal charge migration would occur between irradiation and PEA measurements. PEEK was found to have low acoustic attenuation, while PTFE has high acoustic attenuation through the sample thicknesses of 125 and for each material. The measurements were directly compared to AF-NUMIT3 simulations to validate aspects of the code and to investigate the importance of various simulation options, as well as to characterize the PEA instrumentation, measurement methods, and signal processing used. The measurement and simulation values for magnitude of charge deposition, penetration depth, and charge deposition spatial profiles are largely in agreement, though spatial and temporal distributions in incident electron flux and effects of radiation-induced conductivity (RIC) and delayed RIC during the deposition process complicate the process. This work provides an experimental validation of the AF-NUMIT3 deep dielectric charging code and insight into the accuracy and precision of the PEA method.

Trapping of Hot Carriers in the Forksheet FET Wall: A TCAD Study

We simulate the spatial profile of trapped charge in the forksheet FET wall under hot-carrier stress by calculating carrier distribution functions and using a non-radiative multiphonon model. We observe charge trapping above and below the horizontal projection of the sheet in the wall. We find the charge profile not to depend on the sheet width and the trapping in the forksheet FET wall to be significantly smaller than the trapping in the gate stack.

Remote Condition Monitoring of HVDC Cable Insulation Using Deep Learning-Aided Space Charge Classification

The homo-charges accumulated inside the polymeric insulation of high voltage dc (HVdc) cables increase the electrical field beyond the uniform value, whereas the hetero-charges reduce it. Such uneven electrical field distribution is detrimental to HVdc cables’ longevity and thus, needs to be identified accurately. To this end, this article proposes a deep learning (DL) framework for the automated detection of space charges in HVdc cable insulation. The space charges inside the cross-linked polyethylene (XLPE) insulation samples were measured under varying electric fields (10–50 kV/mm) as well as at different temperatures (30 °C–70 °C) conditions. The obtained space charge profiles corresponding to no charge, hetero-charge, and homo-charge categories were fed to two benchmark convolutional neural network (CNN) models, i.e., AlexNet and VGGNet16, for automated feature extraction and classification purpose. The convolutional blocks of the two CNN models were sequentially fine-tuned using transfer learning (TL) to observe the variation in classification accuracies. The proposed approach delivers appreciably high classification accuracies irrespective of varying electric field and temperature conditions with reduced computational time toward distinguishing different categories of space charge accumulations compared to other CNN models. Hence, it can be potentially used for real-time HVdc insulation diagnostic purposes.

Ti, F Codoped Sodium Manganate of Layered P2-Na 0.7 MnO 2.05 Cathode for High Capacity and Long-Life Sodium-Ion Battery

Ti, F Codoped Sodium Manganate of Layered P2-Na _0.7 MnO _2.05 Cathode for High Capacity and Long-Life Sodium-Ion Battery

In-Operando Optical Spectroscopy of Field-Effect-Gated Al-Doped ZnO

Transparent conductive oxides (TCO) have the unique characteristics of combining optical transparency with high electrical conductivity; such a property makes them uniquely alluring for applications in visible and infrared photonics. One of their most interesting features is the large sensitivity of their optical response to the doping level. We performed the active electrical manipulation of the dielectric properties of aluminum-doped ZnO (AZO), a TCO-based on Earth-abundant elements. We actively tuned the optical and electric performances of AZO films by means of an applied voltage in a parallel-plate capacitor configuration, with SrTiO3 as the dielectric, and monitored the effect of charge injection/depletion by means of in-operando spectroscopic ellipsometry. Calculations of the optical response of the gated system allowed us to extract the spatially resolved variations in the dielectric function of the TCO and infer the injected/depleted charge profile at the interface.

Insights into human eNOS, nNOS and iNOS structures and medicinal indications from statistical analyses of their interactions with bound compounds.

83 Structures of human nNOS, 55 structures of human eNOS, 13 structures of iNOS, and about 126 reported NOS-bound compounds are summarized and analyzed. Structural and statistical analysis show that, at least one copy of each analyzed compound binds to the active site (the substrate arginine binding site) of human NOS. And binding features of the three isoforms show differences, but the binding preference of compounds is not in the way helpful for inhibitor design targeting nNOS and iNOS, or for activator design targeting eNOS. This research shows that there is a strong structural and functional similarity between oxygenase domains of human NOS isoforms, especially the architecture, residue composition, size, shape, and distribution profile of hydrophobicity, polarity and charge of the active site. The selectivity and efficacy of inhibitors over the rest of isoforms rely a lot on chance and randomness. Further increase of selectivity via rational improvement is uncertain, unpredictable and unreliable, therefore, to achieve high selectivity through targeting this site is complicated and requires combinative investigation. After analysis on the current two targeting sites in NOS, the highly conserved arginine binding pocket and H4B binding pocket, new potential drug-targeting sites are proposed based on structure and sequence profiling. This comprehensive analysis on the structure and interaction profiles of human NOS and bound compounds provides fresh insights for drug discovery and pharmacological research, and the new discovery here is practically applied to guide protein-structure based drug discovery.