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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Systematic Study on the Effects of Solvating Solvents and Additives in Localized High‐Concentration Electrolytes over Electrochemical Performance of Lithium‐Ion Batteries

Abstract Localized high‐concentration electrolytes (LHCEs) based on five different types of solvents were systematically studied and compared in lithium (Li)‐ion batteries (LIBs). The unique solvation structure of LHCEs promotes the participation of Li salt in forming solid electrolyte interphase (SEI) on graphite (Gr) anode, which enables solvents previously considered incompatible with Gr to achieve reversible lithiation/delithiation. However, the long cyclability of LIBs is still subject to the intrinsic properties of the solvent species in LHCEs. Such issue can be readily resolved by introducing a small amount of additive into LHCEs. The synergetic decompositions of Li salt, solvating solvent and additive yield effective SEIs and cathode electrolyte interphases (CEIs) in most of the studied LHCEs. This study reveals that both the structure and the composition of solvation sheaths in LHCEs have significant effect on SEI and CEI, and consequently, the cycle life of energetically dense LIBs.

Jia, Hao↗
DOE OSTI2020

An Inorganic-Rich Solid Electrolyte Interphase for Advanced Lithium-Metal Batteries in Carbonate Electrolytes

In carbonate electrolytes, the organic-inorganic solid electrolyte interphase (SEI) formed on the lithium (Li) metal anode surface is strongly bonded to Li and experiences the same volume change as Li, thus it undergoes continuous cracking/reformation during plating/stripping cycles. Here we report, an inorganic-rich SEI is designed on a Li metal surface to reduce its bonding energy with Li metal by dissolving 4 M concentrated LiNO 3 in dimethyl sulfoxide (DMSO) as an additive for a fluoroethylene carbonate (FEC) based electrolyte. Due to the aggregate structure of NO 3 - ions and its participation in the primary Li + solvation sheath, abundant Li 2 O, Li 3 N, and LiN x O y grains are formed in the resulting SEI, in addition to the uniform LiF distribution from the reduction of PF 6 - ions. The inorganic-rich SEI’s weak bonding (high interface energy) to Li can effectively promote Li diffusion along the SEI/Li interface and prevent Li dendrite penetration into the SEI. As a result, our designed carbonate electrolyte enables a Li anode to achieve a high Li plating/stripping CE of 99.55% (1 mA cm -2 , 1.0 mAh cm -2 ) and the electrolyte also enables a Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC811) full cell (2.5 mAh cm -2 ) to retain 75%of its initial capacity after 200 cycles with an outstanding CE of 99.83%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Advanced Low-Flammable Electrolytes for Stable Operation of High-Voltage Lithium-Ion Batteries

Despite being an effective flame retardant, trimethyl phosphate (TMP a ) is generally considered as an unqualified solvent for fabricating electrolytes used in graphite (Gr) based lithium ion batteries as it readily leads to Gr exfoliation and cell failure. In this work, by adopting the unique solvation structure of localized high-concentration electrolyte (LHCE) to TMP a and tuning the composition of the solvation sheath via electrolyte additive, excellent electrochemical performance can be achieved with TMPa based electrolytes in Gr||LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells. After 500 charge/discharge cycles within the voltage range of 2.5-4.4 V, the batteries containing TMPa based LHCEs with proper additive can achieve a capacity retention of 85.4%, being significantly higher than cells using a LiPF 6 -organocarbonates baseline electrolyte (75.2%). Meanwhile, due to the flame retarding effect of TMP a , TMP a based LHCEs exhibit significantly reduced flammability compared with the conventional LiPF 6 -organocarbonates electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Tailoring Na⁺ Chelation Dynamics for Expedient Sulfur Redox Kinetics in Low‐Temperature Sodium–Sulfur Batteries

Sodium–sulfur (Na–S) batteries have attracted considerable attention due to their high theoretical energy density and the abundant natural availability of sodium and sulfur. However, sluggish kinetics of sulfur conversion, slow Na⁺ transport, and interfacial instability at low temperatures pose significant challenges for their operation and limit their practical application. Herein, three solvents with well-designed molecular configurations are examined. We systematically investigate the impact of chelation effect on the desolvation behavior, sulfur conversion process, ion dynamics, and Na⁺ plating/stripping behavior. Compared with conventional linear ether solvents, the incorporation of methyl groups not only weaken the chelation capability and tailors the inner solvation sheath, but also reduces the energy barrier for Na⁺ transport, thus promoting enhanced sulfur conversion kinetics under low temperature conditions. This work elucidates the relationship among solvent molecules, Na⁺ desolvation behavior, and sulfur reaction kinetics, and offers a strategy for rational design of electrolytes for low-temperature metal–sulfur batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Self‐Standing Carbon Nanofibers@Carbon Felt Electrodes to Boost Electrolyzer Productivity: Application to the Electro‐Manufacturing of trans ‐3‐Hexenedioic Acid and Adipic Acid

The industrial implementation of electrosynthesis for chemical manufacturing remains constrained by the limited surface area of conventional electrodes. Herein, this challenge is addressed by designing a carbon nanofiber@carbon felt (CNF@CF) electrode platform that combines the high conductivity, flexibility, and ease of handling of commercial carbon felts (CF) with the large surface area and tunable surface chemistry of carbon nanofibers (CNFs). CNFs are deliberately grown onto the CF scaffold to form a sword-in-sheath structure, where entangled nanofibers wrap the felt macrofibers to provide excellent mechanical stability and electrical conductivity without binders. CNF@CF is evaluated both as an electrode and as a catalyst support for the electrochemical hydrogenation of cis,cis-muconic acid (ccMA), a biobased platform molecule key to the production of performance polyamides and renewable Nylon 6,6. As a noncatalytic electrode for the partial hydrogenation to trans-3-hexenedioic acid, CNF@CF achieves a threefold increase in both cumulative productivity and Faradaic efficiency (FE) compared to bare CF. A similar boost in catalytic activity and energy efficiency is observed using Pd/CNF@CF for the hydrogenation of ccMA to adipic acid. These results highlight the opportunities of the CNF@CF platform for electro-organic synthesis and sustainable chemical manufacturing.

electrochemical hydrogenation↗
DOE OSTI2020

Measurement of temperature of a dusty plasma from its configuration

A new concept called “configurational temperature” is introduced in the context of dusty plasma, where the temperature of the dust particles submerged in the plasma can be measured directly from the positional information of the individual dust particles and the interaction potential between the dust grains. This method does not require the velocity information of individual particles, which is a key parameter to measure the dust temperature in the conventional method. The technique is initially tested using two-dimensional (2D) OpenMP parallel molecular dynamics and Monte Carlo simulation and then compared with the temperature evaluated from experimental data. The experiment have been carried out in the Dusty Plasma Experimental (DPEx) device, where a 2D stationary plasma crystal of melamine formaldehyde particles is formed in the cathode sheath of a DC glow discharge argon plasma. The kinetic temperature of the dust is calculated using the standard particle image velocimetry technique at different pressures. An extended simulation result for the three-dimensional case is also presented, which can be employed for the temperature measurement of a three-dimensional dust crystal in laboratory devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A GPU ‐Accelerated 3D Unstructured Mesh Based Particle Tracking Code for Multi‐Species Impurity Transport Simulation in Fusion Tokamaks

ABSTRACT This paper presents the multi‐species global impurity transport capability developed in a GPU‐accelerated fully 3D unstructured mesh‐based code, GITRm, to simultaneously track multiple impurity species and handle interactions of these impurities with mixed‐material surfaces. Different computational approaches to model particle‐surface interaction or surface response have been developed and compared. Sheath electric field is taken into account by employing a fast distance‐to‐boundary calculation, which is carried out in parallel on distributed or partitioned meshes on multiple GPUs without the need for any inter‐process communication during the simulation. Several example cases, including two for the DIII‐D tokamak, that is, one with the SAS‐V divertor and the other with the collector probes, are used to demonstrate the utility of the current multi‐species capability. For the DIII‐D probe case, the capability of GITRm to resolve the spatial distribution of particles in localized regions, such as diagnostic probes, within non‐axisymmetric tokamak geometries is demonstrated. These simulations involve up to 320 million particles and utilize up to 48 GPUs.

Nath, Dhyanjyoti D. [Scientific Computation Resear↗
DOE OSTI2024

Applying Machine‐Learning Methods to Laser Acceleration of Protons: Lessons Learned From Synthetic Data

ABSTRACT In this study, we consider three different machine‐learning methods—a three‐hidden‐layer neural network, support vector regression, and Gaussian process regression—and compare how well they can learn from a synthetic data set for proton acceleration in the Target Normal Sheath Acceleration regime. The synthetic data set was generated from a previously published theoretical model by Fuchs et al. 2005 that we modified. Once trained, these machine‐learning methods can assist with efforts to maximize the peak proton energy, or with the more general problem of configuring the laser system to produce a proton energy spectrum with desired characteristics. In our study, we focus on both the accuracy of the machine‐learning methods and the performance on one GPU including memory consumption. Although it is arguably the least sophisticated machine‐learning model we considered, support vector regression performed very well in our tests.

Desai, Ronak↗
DOE OSTI2020

Shade signals alter the expression of circadian clock genes in newly-formed bioenergy sorghum internodes

Stem internodes of bioenergy sorghum inbred R.07020 are longer at high plant density (shade) than at low plant density (control). Initially, the youngest newly-formed subapical stem internodes of shade-treated and control plants are comparable in length. However, full-length internodes of shade-treated plants are three times longer than the internodes of the control plants. To identify the early molecular events associated with internode elongation in response to shade, we analyzed the transcriptome of the newly-formed internodes of shade-treated and control plants sampled between 4 and 6 hr after the start of the light period (14 hr light/10 hr dark). Sorghum genes homologous to the Arabidopsis shade marker genes ATHB2 and PIL1 were not differentially expressed. The results indicate that shade signals promote internode elongation indirectly because sorghum internodes are not illuminated and grow while enclosed with leaf sheaths. Sorghum genes homologous to the Arabidopsis morning-phased circadian clock genes LHY, RVE, and LNK were downregulated and evening-phased genes such as TOC1, PRR5, and GI were upregulated in young internodes in response to shade. We hypothesize that a change in the function or patterns of expression of the circadian clock genes is the earliest molecular event associated with internode elongation in response to shade in bioenergy sorghum. Increased expression of CycD1, which promotes cell division, and decreased expression of cell wall-loosening and MBF1-like genes, which promote cell expansion, suggest that shade signals promote internode elongation in bioenergy sorghum in part through increasing cell number by delaying transition from cell division to cell expansion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Metabolomics of related C3 and C4 Flaveria species indicate differences in the operation of photorespiration under fluctuating light

C 3 photosynthesis can be complemented with a C 4 carbon concentrating mechanism (CCM) to minimize photorespiratory losses. C 4 photosynthesis is often more efficient than C 3 under steady-state conditions. However, the C 4 CCM depends on inter-cellular metabolite concentration gradients, which must increase following increases in light intensity and could decrease rates of C 4 photosynthesis under fluctuating light. Additionally, incomplete flux through photorespiration could prove beneficial to C 4 assimilation during light induction of the CCM. Here, we compare metabolic profiles in the closely related C 3 Flaveria robusta and C 4 Flaveria bidentis during a light transient from low to high light to determine if these non-steady state accumulation patterns provide insight to the induction of the metabolite gradients needed to drive C 4 intermediate transport and if there is incomplete cycling of photorespiratory intermediates. In these C 3 and C 4 species, metabolite steady-state pool sizes suggest that C 4 transport acids maintain concentration gradients across the bundle sheath and mesophyll cell types under these light fluctuations. However, there was incomplete flux through photorespiration in the C 4 F. bidentis, which could reduce photorespiratory CO 2 loss via glycine decarboxylation and help maintain higher rates of assimilation during following induction periods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Regulation of dhurrin pathway gene expression during Sorghum bicolor development

Plant defence models evaluate the costs and benefits of resource investments at different stages in the life cycle. Poor understanding of the molecular regulation of defence deployment and remobilization hampers accuracy of the predictions. Cyanogenic glucosides, such as dhurrin are phytoanticipins that release hydrogen cyanide upon bio-activation. In this study, RNA-seq was used to investigate the expression of genes involved in the biosynthesis, bio-activation and recycling of dhurrin in Sorghum bicolor . Genes involved in dhurrin biosynthesis were highly expressed in all young developing vegetative tissues (leaves, leaf sheath, roots, stems), tiller buds and imbibing seeds and showed gene specific peaks of expression in leaves during diel cycles. Genes involved in dhurrin bio-activation were expressed early in organ development with organ-specific expression patterns. Genes involved in recycling were expressed at similar levels in the different organ during development, although post-floral initiation when nutrients are remobilized for grain filling, expression of GSTL1 decreased > tenfold in leaves and NITB2 increased > tenfold in stems. Results are consistent with the establishment of a pre-emptive defence in young tissues and regulated recycling related to organ senescence and increased demand for nitrogen during grain filling. This detailed characterization of the transcriptional regulation of dhurrin biosynthesis, bioactivation and remobilization genes during organ and plant development will aid elucidation of gene regulatory networks and signalling pathways that modulate gene expression and dhurrin levels. In-depth knowledge of dhurrin metabolism could improve the yield, nitrogen use efficiency and stress resilience of Sorghum .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part II: Enforcing the Lorenz Gauge Condition

In a previous paper Christlieb et al. (A particle-in-cell method for plasmas with a generalized momentum formulation, part I: Model formulation, 2024), we developed a new particle-in-cell (PIC) method for the relativistic Vlasov–Maxwell system in which the electromagnetic fields and the equations of motion for the particles were cast in terms of scalar and vector potentials through a Hamiltonian formulation. This new method evolved the potentials under the Lorenz gauge using integral equation methods. New methods to construct spatial derivatives of the potentials that converge at the same rates as the fields were also presented. The new particle method was compared against standard explicit discretizations, including the well-known FDTD-PIC method, for a range of applications involving sheaths and particle beams. Here, this paper extends this new class of methods by focusing on the enforcement the Lorenz gauge condition in both exact and approximate forms using co-located meshes. A time-consistency property of the proposed field solver for the vector potential form of Maxwell’s equations is established, which is shown to preserve the equivalence between the semi-discrete Lorenz gauge condition and the analogous semi-discrete continuity equation. Using this property, we present three methods to enforce a semi-discrete gauge condition. The first method introduces an update for the continuity equation that is consistent with the discretization of the Lorenz gauge condition. Both the finite difference and spectral implementations satisfy this discrete gauge condition to machine precision. The second approach we propose enforces a semi-discrete continuity equation using the boundary integral solution to the field equations. The potential benefit of this approach is that it eliminates spatial derivatives that appear on the particle data, namely the current density, which is often calculated by linear combinations of low-order spline basis functions. This method is ideally suited to boundary integral equation methods that invert multi-dimensional operators without dimensional splitting techniques and will be the subject of future work. The third approach introduces a gauge correcting method that makes direct use of the gauge condition to modify the scalar potential and uses local maps for both the charge and current densities. This results in a gauge error, as the maps do not enforce the continuity equation. The vector potential coming from the current density is taken to be exact, and using the Lorenz gauge, we compute a correction to the scalar potential that makes the two potentials satisfy the gauge condition. This method also enforces the gauge condition to machine precision. We demonstrate two of the proposed methods in the context of periodic domains. Problems defined on bounded domains, including those with complex geometric features remain an ongoing effort. However, this work shows that it is possible to design computationally efficient methods that can effectively enforce the Lorenz gauge condition in a non-staggered PIC formulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part I: Model Formulation

Here, this paper formulates a new particle-in-cell method for the Vlasov–Maxwell system. Under the Lorenz gauge condition, Maxwell’s equations for the electromagnetic fields can be written as a collection of scalar and vector wave equations. The use of potentials for the fields motivates the adoption of a Hamiltonian formulation for particles that employs the generalized (conjugate) momentum. A notable advantage offered by the Hamiltonian formulation is the elimination of time derivatives in the Lorenz gauge formulation that are required by the standard Newton–Lorentz treatment of the particles. This allows the fields to retain the full time-accuracy guaranteed by the field solver. The resulting updates for particles require only knowledge of the fields and their spatial derivatives. An analytical method for constructing these spatial derivatives is presented that exploits the underlying integral solution used in the field solver for the wave equations. Moreover, these derivatives are demonstrated to converge at the same rate as the fields in both time and space. The Method of Lines Transpose field solver we consider in this work is globally first-order accurate in time and high-order accurate in space (e.g., fourth- and fifth-order) and belongs to a larger class of methods which are unconditionally stable, can address geometry, and leverage $\mathcal {O}(N)$ fast summation methods for efficiency. We demonstrate the method on several well-established benchmark problems on bounded domains, including a plasma sheath as well as a relativistic particle beam. The efficacy of the proposed formulation is established by comparing with a second-order accurate finite-difference time-domain method that employs a leapfrog time advance for particles and a charge conserving map suitable for bounded domains. The new method shows mesh-independent numerical heating properties even in cases where the plasma Debye length is smaller than the grid spacing. This is an important feature of the new method for problems defined on bounded domains, because it permits the use of coarser grids in space in the representation of the fields. Such a capability has significant implications for the simulation of plasmas in bounded domains with complex geometry, where the ratio between the largest and smallest cells can vary significantly. The use of high-order spatial approximations in the new method also means that fewer grid points are required in order to achieve a fixed accuracy. Our results also suggest that the new method can be used with fewer simulation particles per cell compared to the benchmark explicit method, which permits further computational savings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

3D RNA nanocage for encapsulation and shielding of hydrophobic biomolecules to improve the in vivo biodistribution

Ribonucleic acid (RNA) nanotechnology platforms have the potential of harboring therapeutics for in vivo delivery in disease treatment. However, the nonspecific interaction between the harbored hydrophobic drugs and cells or other components before reaching the diseased site has been an obstacle in drug delivery. In this work, we report an encapsulation strategy to prevent such nonspecific hydrophobic interactions in vitro and in vivo based on a self-assembled three-dimensional (3D) RNA nanocage. By placing an RNA three-way junction (3WJ) in the cavity of the nanocage, the conjugated hydrophobic molecules were specifically positioned within the nanocage, preventing their exposure to the biological environment. The assembly of the nanocages was characterized by native polyacrylamide gel electrophoresis (PAGE), atomic force microscopy (AFM), and cryogenic electron microscopy (cryo-EM) imaging. The stealth effect of the nanocage for hydrophobic molecules in vitro was evaluated by gel electrophoresis, flow cytometry, and confocal microscopy. The in vivo sheathing effect of the nanocage for hydrophobic molecules was assessed by biodistribution profiling in mice. The RNA nanocages with hydrophobic biomolecules underwent faster clearance in liver and spleen in comparison to their counterparts. Therefore, this encapsulation strategy holds promise for in vivo delivery of hydrophobic drugs for disease treatment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗
DOE OSTI2020

On the competition between mixing rate and uniformity in a coaxial hydrodynamic focusing mixer

Fast microfluidic mixers for use with line-of-sight integrating detection schemes pose unique challenges. Such detectors typically cannot discriminate signal from slow moving (e.g. near internal walls) and fast-moving portions of the fluid stream. This convolves reaction rate dynamics with fluid flow residence time dynamics. Further, the small cross sections of typical three-dimensional hydrodynamic focusing devices lead to lower detection signals. The current study focuses on achieving both small time scales of mixing and homogenous residence times. This is achieved by injecting sample through a center capillary and hydrodynamically focusing using a sheath flow within a tapered second capillary. The current design also features a third, larger coaxial capillary. The mixed stream flows into the large cross-section of this third capillary to decelerate and expand the stream by up to 14-fold to improve line-of-sight signal strength of reaction products. Hydrodynamic focusing, mixing, and expansion are studied using analytical and numerical models and also studied experimentally using a fluorescein-iodide quenching reaction. The experimentally validated models are used to explore trade-offs between mixing rate and uniformity. For the first time, this work presents detailed analysis of the Lagrangian time history of species transport during mixing inside coaxial capillaries to measure mixing nonuniformity. The mixing region enables order 100 μs mixing times and residence time widths of the same order (140 μs).

42 ENGINEERING↗
DOE OSTI2023

Imaging crossing fibers in mouse, pig, monkey, and human brain using small-angle X-ray scattering

Myelinated axons (nerve fibers) efficiently transmit signals throughout the brain via action potentials. Multiple methods that are sensitive to axon orientations, from microscopy to magnetic resonance imaging, aim to reconstruct the brain's structural connectome. As billions of nerve fibers traverse the brain with various possible geometries at each point, resolving fiber crossings is necessary to generate accurate structural connectivity maps. However, doing so with specificity is a challenging task because signals originating from oriented fibers can be influenced by brain (micro)structures unrelated to myelinated axons. X-ray scattering can specifically probe myelinated axons due to the periodicity of the myelin sheath, which yields distinct peaks in the scattering pattern. Here, in this work, we show that small-angle X-ray scattering (SAXS) can be used to detect myelinated, axon-specific fiber crossings. We first demonstrate the capability using strips of human corpus callosum to create artificial double- and triple-crossing fiber geometries, and we then apply the method in mouse, pig, vervet monkey, and human brains. We compare results to polarized light imaging (3D-PLI), tracer experiments, and to outputs from diffusion MRI that sometimes fails to detect crossings. Given its specificity, capability of 3-dimensional sampling and high resolution, SAXS could serve as a ground truth for validating fiber orientations derived using diffusion MRI as well as microscopy-based methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A simple centrifuge cell method for ex situ quantification of electrical conductivity of slurry electrode materials

We present the design, experimental procedure, and experimental evaluation of a system for fast, simple, and ex situ characterization of electrical conductivity of slurry electrode materials. The system uses a custom-designed electrochemical cell compatible with centrifugation in a swing-bucket centrifuge. The cell features cylindrical graphite electrodes that are partially sheathed so as to expose only 2 mm of the electrode surface to the bottom region of the packed particulate pellet. Also presented is a conduction model that provides a shape factor for estimating effective conductivity. We tested aqueous solutions of carbon black (CB), activated carbon (AC), and mixtures thereof. These particles were dispersed in 0.0 and 0.5 M NaCl solutions. Measurements show that the effective conductivity initially increases linearly with pellet mass and then saturates at higher masses. Notably, CB exhibited a fivefold increase in conductivity than AC at equal pellet masses. CB/AC mixtures at a fixed pellet mass were tested with CB mass fractions of 0 to 100%. Interestingly, the mixture conductivity was found to be a non-monotonic function of CB mass fraction, with a maximum conductivity at about 60 % CB mass fraction. At this maximum, the mixture conductivity is approximately 30 % higher than pure CB. NaCl concentration in the slurry solution had no effects on conductivity. These results highlight the interactions between slurry electrode composition and compaction, offering insights for optimizing slurry electrodes. Furthermore, the system and results may also be applicable to evaluation of particulate materials (including slurries) used for Li-ion batteries, capacitive deionization, fuel cells, and flow electrodes.

Capacitive deionization↗