Ti 3 C 2 T x MXene-Reduced Graphene Oxide Composite Electrodes for Stretchable Supercapacitors
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catalysis (heterogeneous)↗
SEARCH · Engineering Papers
Results for “Charging Behavior”
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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Exploring nonequilibrium phases of photo-doped Mott insulators with generalized Gibbs ensembles
Many experiments show that strong excitations of correlated quantum materials can cause non-thermal phases without equilibrium analogues. Understanding the origin and properties of these nonequilibrium states has been challenging due to the limitations of theoretical methods for nonequilibrium strongly correlated systems. In this work, we introduce a generalized Gibbs ensemble description that enables a systematic analysis of the long-time behavior of photo-doped states in Mott insulators based on equilibrium methods. We demonstrate the power of the method by mapping out the nonequilibrium phase diagram of the one-dimensional extended Hubbard model, which features η -pairing and charge density wave phases in a wide photo-doping range. We furthermore clarify that the peculiar kinematics of photo-doped carriers, and the interaction between them, play an essential role in the formation of these non-thermal phases. Our results establish a new path for the systematic analysis of nonequilibrium strongly correlated systems.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Self-sorting in supramolecular assemblies
Supramolecular self-assembly enables living organisms to form highly functional hierarchical structures with individual components self-organized across multiple length scales. This has inspired work on multicomponent supramolecular materials to understand factors behind co-assembly versus self-sorting of molecules. We report here on a supramolecular system comprised of negatively charged peptide amphiphile (PA) molecules, in which only a tiny fraction of the molecules (0.7 mol%) were covalently conjugated to one of two different fluorophores, half to fluorescein isothiocyanate (FTIC) and the other half to tetramethylrhodamine (TAMRA). Confocal microscopy of the system revealed self-sorting of the two different fluorescent PA molecules, where TAMRA PA is concentrated in micron-scale domains while FITC PA remains dispersed throughout the sample. From Förster resonance energy transfer and fluorescence recovery experiments, we conclude that conjugation of the negatively charged FITC to PA significantly disrupts its co-assembly with the 99.3 mol% of unlabeled molecules, which are responsible for formation of micron-scale domains. Conversely, conjugation of the zwitterionic TAMRA causes no such disruption. Interestingly, this dissimilar behavior between FITC and TAMRA PA causes them to self-sort at large length scales in the supramolecular system, mediated not by specific interactions among the individual fluorophores but instead by their different propensities to co-assemble with the majority component. We also found that greater ionic strength in the aqueous environment of the system promotes mixing by lowering the electrostatic barriers involved in self-sorting. Furthermore, our results demonstrate great thermodynamic subtlety in the driving forces that mediate self-sorting versus co-assembly in supramolecular peptide assemblies.
36 MATERIALS SCIENCE↗
Towards molecular simulations that are transparent, reproducible, usable by others, and extensible (TRUE)
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Anomalous proximitized transport in metal/quantum magnet heterostructure Bi 2 Ir 2 O 7 /Yb 2 Ti 2 O 7
Fluctuations of quantum spins play a crucial role in the emergence of exotic magnetic phases and excitations. The lack of the charge degree of freedom in insulating quantum magnets, however, precludes such fluctuations from mediating electronic transport. Here, we show that the quantum fluctuations of a localized frustrated magnet induce strong proximitized charge transport of the conduction electrons in a synthetic heterostructure comprising an epitaxial Bi 2 Ir 2 O 7 ultrathin film on a single crystal of Yb 2 Ti 2 O 7 . The proximity effects are evidenced by the scaling behavior of the Bi 2 Ir 2 O 7 resistance in correspondence with the dynamic scaling of the dynamic spincorrelation function of Yb 2 Ti 2 O 7 , which is a result of quantum fluctuations near a multiphase quantum critical point. The proximitized transport in Bi 2 Ir 2 O 7 can be effectively tuned by a magnetic field through suppressing the quantum spin fluctuations (QSFs) as well as inducing transitions via magnetic anisotropy in Yb 2 Ti 2 O 7 . In this study, we establish a pathway for harnessing QSFs in magnetic insulators with electric transport, offering exciting prospects for potential applications in the realm of quantum spintronics.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Protein-Nanoparticle Interactions Govern the Interfacial Behavior of Polymeric Nanogels: Study of Protein Corona Formation at the Air/Water Interface
Biomedical applications of nanoparticles require a fundamental understanding of their interactions and behavior with biological interfaces. Protein corona formation can alter the morphology and properties of nanomaterials, and knowledge of the interfacial behavior of the complexes, using in situ analytical techniques, will impact the development of nanocarriers to maximize uptake and permeability at cellular interfaces. In this study we evaluate the interactions of acrylamide-based nanogels, with neutral, positive, and negative charges, with serum-abundant proteins albumin, fibrinogen, and immunoglobulin G. The formation of a protein corona complex between positively charged nanoparticles and albumin is characterized by dynamic light scattering, circular dichroism, and surface tensiometry; we use neutron reflectometry to resolve the complex structure at the air/water interface and demonstrate the effect of increased protein concentration on the interface. Surface tensiometry data suggest that the structure of the proteins can impact the interfacial properties of the complex formed. These results contribute to the understanding of the factors that influence the bio-nano interface, which will help to design nanomaterials with improved properties for applications in drug delivery.
Traldi, Federico (ORCID:0000000161251012)↗
Effect of NO on DME-Methanol HCCI Experimental Observations
Methanol is an attractive fuel for the maritime sector due to its wide availability. Its direct use as a fuel, however, is accompanied by challenges such as high latent heat of vaporization and low cetane number. A potential solution to overcome the ignition properties of methanol could be through on-board generation of dimethyl ether (DME) via catalytic dehydration of methanol. The resulting mixture from dehydration can be mixed in with the intake air to generate a homogenous charge compression ignition (HCCI) preburn for subsequent direct injection (DI) and successful ignition methanol at diesel–like timescales. However, if the preburn species are treated separately from the complete methanol MCCI approach the preburn heat release rate (HRR) phasing and behavior do not replicate the preburn behavior of the complete approach. Thus, the presence of the main methanol mixing controlled compression ignition (MCCI) combustion event influences the DME/methanol preburn kinetics. Specifically, it was found that trapped residual temperature alone was insufficient alone to be responsible for the observed differences, and that trace species concentrations of NO in the trapped residual gas also influenced DME/methanol kinetics increasing low temperature heat release (LTHR) magnitude and advancing high temperature heat release (HTHR) phasing. NO is not present in HCCI combustion of neat DME or DME/methanol blends nor is elevated gas temperature in the trapped residuals; both of which result in failure to accurately predict the HCCI combustion of DME/methanol blends when coupled with subsequent DI methanol MCCI. This work experimentally explores the effect of trapped residual temperature and NO on DME and DME/methanol HCCI combustion.
Jatana, Gurneesh [ORNL] (ORCID:0000000288903225)↗
Symmetry-resolved entanglement entropy, spectra & boundary conformal field theory
We perform a comprehensive analysis of the symmetry-resolved (SR) entanglement entropy (EE) for one single interval in the ground state of a 1 + 1D conformal field theory (CFT), that is invariant under an arbitrary finite or compact Lie group, G. We utilize the boundary CFT approach to study the total EE, which enables us to find the universal leading order behavior of the SREE and its first correction, which explicitly depends on the irreducible representation under consideration and breaks the equipartition of entanglement. We present two distinct schemes to carry out these computations. The first relies on the evaluation of the charged moments of the reduced density matrix. This involves studying the action of the defect-line, that generates the symmetry, on the boundary states of the theory. This perspective also paves the way for discussing the infeasibility of studying symmetry resolution when an anomalous symmetry is present. The second scheme draws a parallel between the SREE and the partition function of an orbifold CFT. This approach allows for the direct computation of the SREE without the need to use charged moments. From this standpoint, the infeasibility of defining the symmetry-resolved EE for an anomalous symmetry arises from the obstruction to gauging. Finally, we derive the symmetry-resolved entanglement spectra for a CFT invariant under a finite symmetry group. We revisit a similar problem for CFT with compact Lie group, explicitly deriving an improved formula for U(1) resolved entanglement spectra. Using the Tauberian formalism, we can estimate the aforementioned EE spectra rigorously by proving an optimal lower and upper bound on the same. In the abelian case, we perform numerical checks on the bound and find perfect agreement.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Selective Pb 2+ removal and electrochemical regeneration of fresh and recycled FeOOH
Heavy metal pollution is a key environmental problem. Selectively extracting heavy metals could accomplish water purification and resource recycling simultaneously. Adsorption is a promising approach with a facile process, adaptability for the broad concentration of feed water, and high selectivity. However, the adsorption method faces challenges in synthesizing high-performance sorbents and regenerating adsorbents effectively. FeOOH is an environmentally friendly sorbent with low-cost production on a large scale. Nevertheless, the selectivity behavior and regeneration of FeOOH are seldom studied. Therefore, we investigated the selectivity of FeOOH in a mixed solution of Co 2+ , Ni 2+ , and Pb 2+ and proposed to enhance the capacity of FeOOH and regenerate it by using external charges. Without charge, the FeOOH electrode shows a Pb 2+ uptake capacity of 20 mg/g. After applying a voltage of –0.2/+0.8 V, the uptake capacity increases to a maximum of 42 mg/g and the desorption ratio is 70%–80%. In 35 cycles, FeOOH shows a superior selectivity towards Pb 2+ compared with Co 2+ and Ni 2+ , with a purity of 97% ± 3% in the extracts. The high selectivity is attributed to the lower activation energy for Pb 2+ sorption. The capacity retentions at the 5 th and the 35 th cycles are ca. 80% and ca. 50%, respectively, comparable to the chemical regeneration method. With industrially exhausted granular ferric hydroxide as the electrode material, the system exhibits a Pb 2+ uptake capacity of 37.4 mg/g with high selectivity. Our work demonstrates the feasibility of regenerating FeOOH by charge and provides a new approach for recycling and upcycling FeOOH sorbent.
36 MATERIALS SCIENCE↗
A first principles framework to predict the transient performance of latent heat thermal energy storage
Thermal energy storage (TES) is increasingly recognized as an essential component of efficient Combined Heat and Power (CHP), Concentrated Solar Power (CSP), Heating Ventilation and Air Conditioning (HVAC), and refrigeration as it reduces peak demand while helping to manage intermittent availability of energy (e.g., from solar or wind). Latent Heat Thermal Energy Storage (LHTES) is a viable option because of its high energy storage density. Parametric analysis of LHTES in terms of dimensionless numbers is highly desired as a tool to model LHTES systems. One approach is to develop a model equation so as to minimize the error between the model and data obtained from experiments or simulations. While this approach can produce an accurate correlation applicable within the range of data used for its creation, it does not provide physical understanding of the rate-limiting process controlling the transient behavior of the device. In this paper we present an alternative approach whereby the potential rate-limiting processes are identified from first principles and then the key process is determined as a function of time as a LHTES device is charged. For example, in a simple geometry, the melt-fraction can be expected to vary linearly in time if the heat transfer rate is limited by natural convection of the phase changing material and we show it scales with the PCM Grashof number as $Gr^1_p$ and PCM Prandtl number as $Pr_p^{(1/3)}$. On the other hand, if surface area of solid PCM limits the heat transfer rate, the melt fraction increases asymptotically to reach full melting. The existence of these linear and asymptotic regions and the $Gr^1_pP r^{1/3}_p$ shape of the melt fraction curve is verified using our database of 64 simulations. Of practical importance in designing LHTES devices is the melt fraction at which the heat transfer rate ceases to be limited by convection, after which the heat storage rate deteriorates. For our geometry, this is found to be about 90%. This test case of our methodology shows the value of our approach, that predicting heat storage rate based on the rate-limiting physical phenomenon as a function of time is an effective approach to modeling LHTES devices.
25 ENERGY STORAGE↗
Hydrogen station in situ back-to-back fueling data for design and modeling
Hydrogen technologies are rapidly spreading, with significant attention to the mobility sector requiring a robust and widespread fueling infrastructure. Hydrogen stations are indeed fundamental to transitioning from pilot projects towards large-scale implementation in many countries. Operating under extreme conditions, the new stations need more informed designs and equipment to meet the growing demand and their more frequent utilization. Via a set of experimental research activities and investigated scenarios carried out at the Cal State LA Hydrogen Research and Fueling Facility, here this paper shares a novel and comprehensive set of data collected over a period of one year on fueling events frequency and refueling process station behaviors. A performance evaluation of the station is presented under different load scenarios in severe conditions during "back-to-back fuelings", with monitoring of fundamental parameters for infrastructure sizing, including dynamic cooling response, pressure levels, thermodynamics, and the state of charge of the vehicle. The presented data analysis could surely contribute as closer-to-reality inputs for a variety of station performance modeling tools.
08 HYDROGEN↗
Battery aging mode identification across NMC compositions and designs using machine learning
A comprehensive understanding of lithium-ion battery (LiB) lifespan is the key to designing durable batteries and optimizing use protocols. Although battery lifetime prediction methods are flourishing, diagnosis of the root causes of aging and degradation have not yet been well developed nor studied for a broad mixture of designs and use cases. Here, we create a machine-learning (ML)-based framework that distinguishes aging modes using multiple electrochemical signatures recorded cycle-by-cycle. The predominant aging behaviors include a combination of loss of active materials in cathode (LAMPE) and a loss of Li inventory (LLI) in Li plating or solid electrolyte interphase (SEI) formation, manifested from 44 batteries representing two cathode chemistries, two electrode loadings, and five charging rates. Here, the aging mode classification accuracy is 86% using features within the first 50 cycles and increases to 88% beyond 225 cycles. The same features can quantify the percentage of end-of-life LAMPE with only 4.3% of error.
25 ENERGY STORAGE↗
Faradaic efficiency in protonic-ceramic electrolysis cells
Abstract Proton-conducting ceramics (e.g. doped barium zirconates or cerates) are typically mixed ionic-electronic conductors (MIECs). The electronic conduction, typically in the form of positively charged small polarons or electron holes, leads to ‘electronic leakage.’ In an ideal steam-electrolysis cell, one gas-phase H 2 molecule is produced from every two electrons delivered from an external power source. In other words, such ideal behavior achieves 100% faradaic efficiency. However, the electronic flux associated with MIEC membranes contributes to reduced faradaic efficiency. The present paper develops a model that predicts the behavior of faradaic efficiency as a function of electrolysis-cell operating conditions. Although the model framework is more general, the paper focuses on the behavior of a cell based upon a BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3 − δ (BCZYYb) membrane. The study predicts the effects of operating conditions, including temperature, pressure, and gas compositions.
Zhu, Huayang↗
Mitigation of nitrogen vacancy photoluminescence quenching from material integration for quantum sensing
The nitrogen-vacancy (NV) color center in diamond has demonstrated great promise in a wide range of quantum sensing. Recently, there have been a series of proposals and experiments using NV centers to detect spin noise of quantum materials near the diamond surface. This is a rich complex area of study with novel nano-magnetism and electronic behavior, that the NV center would be ideal for sensing. However, due to the electronic properties of the NV itself and its host material, getting high quality NV centers within nanometers of such systems is challenging. Band bending caused by space charges formed at the metal-semiconductor interface force the NV center into its insensitive charge states. Here, we investigate optimizing this interface by depositing thin metal films and thin insulating layers on a series of NV ensembles at different depths to characterize the impact of metal films on different ensemble depths. We find an improvement of coherence and dephasing times we attribute to ionization of other paramagnetic defects. The insulating layer of alumina between the metal and diamond provide improved photoluminescence and higher sensitivity in all modes of sensing as compared to direct contact with the metal, providing as much as a factor of 2 increase in sensitivity, decrease of integration time by a factor of 4, for NV T 1 relaxometry measurements.
36 MATERIALS SCIENCE↗
Excitation spectra of quantum matter without quasiparticles. II. Random t - J models
Here, we present numerical solutions of the spectral functions of large dimension t -J models with random nearest neighbor exchange and global SU(M) spin rotation symmetry. The solutions are obtained from the saddle-point equations of the large dimension limit, followed by the large M limit. The same saddle point equations also apply to the model with all-to-all and random hopping and exchange. Such a t -J model realizes a deconfined critical state proposed as a model for the optimally doped cuprates. The large M theory involves Green’s functions for fractionalized spinons and holons carrying emergent U(1) gauge charges, obeying relations similar to those of the Sachdev-Ye-Kitaev (SYK) models. The low frequency spectral functions are compared with an analytic analysis of the operator scaling dimensions with good agreement. We also compute the low frequency and temperature behavior of experimentally observable gauge-invariant observables: the electron Green’s function, the local spin susceptibility and the optical conductivity, along with the temperature dependence of the d.c. resistivity. The time reparameterization soft mode (equivalent to the boundary graviton in holographically dual models of two-dimensional quantum gravity) makes important contributions to all observables and provides a linear-in-temperature contribution to the d.c. resistivity.
36 MATERIALS SCIENCE↗
Deciphering competing elementary steps to correlate electrocatalyst chemical state with activity
The overpotential in multielectron transfer heterogeneous electrocatalysis fundamentally arises from thermodynamic and kinetic disparities among elementary steps; however, deciphering coupled and competing steps has long remained a challenge. Here, we establish an electrochemical deconvolution paradigm based on key processes in electrocatalytic reactions, such as charge accumulation, electron/proton transfer, and intermediate evolution, to resolve competing elementary steps. Taking the oxygen evolution reaction as a prototypical reaction, we design a model catalyst featuring a precise isolated cation-anion vacancy pair and track the previously elusive electrochemical behavior of lattice oxygen by disentangling interference from adsorbed oxygen intermediates. Mechanistically, the lattice oxygen oxidation pathway originates from the spontaneous, nonelectrochemical deprotonation of replenished water molecules coordinated to unsaturated cation sites. Alternating current techniques further reveal that although lattice oxygen oxidation requires a higher potential than metal oxidation, it exhibits faster kinetics, providing insight into its superior catalytic activity. These findings establish a direct experimental correlation between the initial chemical state and the catalytic activity and prove surface-confined lattice oxygen cycling. Furthermore, expanding conventional potential-current analysis into a multidimensional framework enables disentanglement of thermodynamic and kinetic contributions of key elementary steps, thereby guiding the rational optimization of various complex multielectron transfer reactions.
OER↗
A Sheaf Theoretical Approach to Uncertainty Quantification of Heterogeneous Geolocation Information
Integration of multiple, heterogeneous sensors is a challenging problem across a range of applications. Prominent among these are multi-target tracking, where one must combine observations from different sensor types in a meaningful and efficient way to track multiple targets. Because different sensors have differing error models, we seek a theoretically justified quantification of the agreement among ensembles of sensors, both overall for a sensor collection, and also at a fine-grained level specifying pairwise and multi-way interactions among sensors. We demonstrate that the theory of mathematical sheaves provides a unified answer to this need, supporting both quantitative and qualitative data. Furthermore, the theory provides algorithms to globalize data across the network of deployed sensors, and to diagnose issues when the data do not globalize cleanly. We demonstrate and illustrate the utility of sheaf-based tracking models based on experimental data of a wild population of black bears in Asheville, North Carolina. A measurement model involving four sensors deployed among the bears and the team of scientists charged with tracking their location is deployed. This provides a sheaf-based integration model which is small enough to fully interpret, but of sufficient complexity to demonstrate the sheaf’s ability to recover a holistic picture of the locations and behaviors of both individual bears and the bear-human tracking system. A statistical approach was developed in parallel for comparison, a dynamic linear model which was estimated using a Kalman filter. This approach also recovered bear and human locations and sensor accuracies. When the observations are normalized into a common coordinate system, the structure of the dynamic linear observation model recapitulates the structure of the sheaf model, demonstrating the canonicity of the sheaf-based approach. However, when the observations are not so normalized, the sheaf model still remains valid.
97 MATHEMATICS AND COMPUTING↗
Multimodal X-ray Microscopy: The Kinetics of Cu in CdTe Absorbers
The behavior of solar cells is very often limited by inhomogeneously distributed nanoscale defects. This is the case throughout the entire lifecycle of the solar cell, from the distribution of elements and defects during solar cell growth as well as the charge-collection and recombination during operation, to degradation and failure mechanisms due to impurity diffusion, crack formation, and irradiation- and heat-induced cell damage This has been known for a while in the field of crystalline silicon, but inhomogeneities are far more abundant in polycrystalline materials, and are the limiting factor in thin-film solar cells where grain sizes are often on the order of the diffusion length. We showed that the high penetration of hard X-rays combined with the high sensitivity to elemental distribution, structure, and spatial resolution offers a unique avenue for highly correlative studies at the nanoscale. We presented results on Cu-doped CdTe, where carrier collection is directly correlated to the kinetics of Cu inside the absorber and the particular Cu-phases at the ZnTe/CdTe interface. We complemented the results with modeling using PVRD-FASP and PyCDTS, where the X-ray beam induced profile can be reproduced by the equilibrium defect concentrations proposed by the solvers.
Bertoni, Mariana↗