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The novelty of this study includes correlating stress with the complex structural transformation and volume changes in sodium-ion battery cathodes.
LiMnxFe1−xPO4 (LMFP) is a promising high-voltage, thermally stable, and earth-abundant cathode material, yet its practical application is limited by interphase instability and Mn dissolution. In this work, we systematically evaluate LiMn0.6Fe0.4PO4/graphite pouch cells using three electrolyte formulations including control carbonate electrolyte, control + 2 wt% vinylene carbonate (VC), and control + 2 wt% VC + 1 wt% 1,3,2-dioxathiolane 2,2-dioxide (DTD), to establish how electrolyte composition governs interphase chemistry and long-term degradation. Electrochemical testing shows that both additives are preferentially reduced prior to ethylene carbonate (EC) during cell formation, generating robust cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI) layers that suppress gas evolution and raise the first-cycle coulombic efficiency to 89.3%. Additionally, the dual-additive electrolyte delivers the most stable performance, retaining over 85% capacity after 600 cycles while minimizing impedance growth under long-term cycling at C/3 and 40 °C. Soft X-ray absorption spectroscopy confirms that VC + DTD effectively suppresses electrolyte oxidation at the cathode surface, and micro-X-ray fluorescence shows substantially reduced Mn dissolution and deposition on the graphite anode. Density functional theory simulations further provided insights into the structural and energetic influences of alkoxide species on the cathode surface, proposing a Mn2+ extraction mechanism. The combined experimental and computational findings establish a mechanistic link between electrolyte composition and interphase evolution, highlighting the effectiveness of electrolyte engineering for extending the operational lifetime of LMFP-based lithium-ion batteries.
Our lab has been engaged in using glycerol to replace water in the synthesis of metal oxides, especially those for use in Li-ion battery. Glycerol is a byproduct from biodiesel production. The U.S. biodiesel manufacturers generate about 1 billion pounds of glycerol yearly, which needs to be utilized for producing value added products. By using glycerol as a solvent, we found that it can replace water to prepare many metal oxide powders. The materials synthesis processes have the potential to significantly reduce manufacturing cost and alleviate the environmental issues with aqueous processes. In this talk, I will present some of our work in materials synthesis using glycerol as a solvent. In particular, I will introduce the work on making active cathode materials for the Li-ion battery.
Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.
The operational instability of perovskite solar cells (PSCs) is understood to mainly originate from the migration of ionic species (or charged defects) under a potential gradient. Compositional engineering of the “A” site cation of the ABX3 perovskite structure has been shown to be an effective route to improve the stability of PSCs. Here, the effect of size-mismatch-induced lattice distortions on the ion migration energetics and operational stability of PSCs is investigated. It is determined that the size mismatch of the mixed “A” site composition films and devices leads to a steric effect to impede the migration pathways of ions to increase the activation energy of ion migration, which is demonstrated through multiple theoretical and experimental evidence. Consequently, the mixed composition devices exhibit significantly improved thermal stability under continuous heating at 85 °C and operational stability under continuous 1 sun illumination, with an extrapolated lifetime of 2011 h, compared to the 222 h of the reference device.
Photoelectrochemical (PEC) water-splitting systems have the unique ability to produce renewable hydrogen directly from sunlight, independent of the electrical grid. These systems are therefore appealing technological options for resilient long-term energy storage. Ion selective membranes, such as monopolar and bipolar membranes, are a vital component of PEC water-splitting systems. These membranes allow for ionic conduction between the cathode and anode chambers, separation of products, and improved catalyst environments for reactions. In order to measure key properties and to study the performance of these ion exchange membranes, it is imperative to develop a robust testing protocol that can be used across the field. This paper introduces two standard electrochemical cells designed to directly measure ion transport properties in monopolar and bipolar membranes. The first electrochemical cell uses commercially available Pt disk electrodes to preform electrochemical impedance spectroscopy (EIS) and reliably measure through-plane conductivity of monopolar membranes. The second electrochemical cell uses four-point measurements with Luggin capillaries and a series of membrane configurations to perform current density-voltage and Faradaic efficiency (FE) measurements for water dissociation (WD) reactions on bipolar membranes. The cell designs and techniques laid out below allow for accurate measurement of ion transport parameters in ion exchange membranes, direct comparison of membranes being developed across the field, and in turn, greater advancements in ion exchange membranes and PEC water-splitting systems.
Aromatic acids, such as p-coumaric acid, are valuable chemical intermediates that are used in the specialty chemical industries because they are precursors to phenylpropanoid compounds. The separation of p-coumaric acid from fermentation broths is a critical step in the biochemical production process and more broadly the circular carbon economy. Electrodeionization (EDI) has been applied toward separations of low-carbon chain acids, but purifying p-coumaric acid has been challenging due to fouling and irreversible binding with ion-exchange membranes and resins. Here, we report a new membrane wafer assembly (MWA) consisting of laminated ion exchange membranes to porous ionomer-binder resin wafers for EDI. The MWAs in an EDI stack showed a 7-fold increase in p-coumaric acid capture while also using 70% less specific energy consumption when benchmarked against state-of-the-art resin wafer EDI modules. The more efficient p-coumaric acid recovery was ascribed to (i) the 38% reduction in interfacial transport resistance between the membrane and resin wafer and (ii) using imidazolium anion exchange membranes and ionomer binders in the MWA. MD simulations revealed enhanced transport rates for p-coumarate in imidazolium ionomers through π–π interactions. As a result, adopting the new MWA significantly reduced the amount of ion-exchange membranes in EDI and may lead to drastic capital cost savings.
A novel data interpretation process that utilizes comprehensive particle-in-cell (PIC) simulations is developed for the new retarding field energy analyzer (RFEA) currently being constructed at DIII-D for the lower divertor using the Divertor Material Evaluation System. Furthermore, this probe is expected to survive a heat load of up to 100 MW/m 2 for up to 5 s and reliably measure the main ion temperature (T i ) on the divertor target ranging from 10 to 200 eV. These extreme conditions posed significant engineering limitations on the probe geometry, thus extensive validation work has been performed. The conventional fitting method for the RFEA I–V characteristics is based on a simplified 1-D model without considering the ion space charge inside the probe cavity and may not be sufficient for probes designed for the DIII-D divertor environment. In this article, a more realistic description of the particle propagation process within the RFEA cavity is achieved by including both 3-D geometric effects and ion space charge in the PIC simulations, and the capability to reconstruct the ion energy distribution functions is demonstrated with reasonable consistency.
Solid-state batteries (SSBs) are promising candidates for energy storage systems—specifically for automotive applications—owing to their higher energy density and supreme safety. SSBs currently must improve area-specific cathode loadings as well as the electro-chemo-mechanical stability at high voltages. Composite cathodes in SSBs are comprised of active material, ion and electronic conductors, binders, and electronic conducting materials. In addition to experimental limitations with engineering thick cathode architectures, low utilization and chemomechanical degradation of the cathodes limit the performance of composite cathodes. Composite cathodes must optimize several parameters simultaneously to achieve high performances that include loading, electrochemically active surface area, mechanical resilience, and porosity. This chapter summarizes the current state-of-the-art applications with regard to composite cathodes for SSBs and provides insights into cathode architectures using geometric packing models. Tailoring ion and electron transport pathways within the electrode while mitigating operational stresses is crucial for achieving energy-dense cathode structres for SSBs.
Quantum control of the many-body wavefunction is a central challenge in quantum materials research, as it could yield a precise control knob to manipulate emergent phenomena. Floquet engineering, the coherent dressing of quantum states with periodic non-resonant optical fields, has become an important strategy for quantum control. Most applications to solid-state systems have targeted weakly interacting or single-ion states, leaving the manipulation of many-body wavefunctions largely unexplored. Here, in this work, we use Floquet engineering to achieve quantum control of a strongly correlated Hubbard exciton in the one-dimensional Mott insulator Sr 2 CuO 3 . A nonresonant midinfrared optical field coherently dresses the exciton wavefunction, driving its rotation between bright and dark states. We use resonant third-harmonic generation to quantify ultrafast π/2 rotations on the Bloch sphere spanned by these exciton states. Our work advances the quest towards programmable control of correlated states and exciton-based quantum sensing.
Si nanoparticles (SiNPs) are recognized as a promising anode material for next-generation high-energy lithium-ion batteries. However, due to the more stringent requirements resulting from severe volume change, the solid-electrolyte interphase (SEI) on SiNPs plays a critical role in determining their cycling performance. Engineering the interface for higher stability has become an effective yet challenging approach to accommodate the deterioration of the silicon anode from the repeated lithiation/delithiation process. Herein, we report a novel approach of engineering a covalently bonded organic monolayer of ethylene carbonates onto the surface of the SiNPs that can help form a sturdy SEI. Finally, this molecule-level surface modification provides an effective approach to enable high-energy lithium-ion batteries with Si anodes.
High-mass-loading cathodes are crucial for achieving high energy density in all-solid-state batteries from the lab scale to industry. However, as mass-loading increases, electrochemical performance is significantly compromised due to sluggish kinetics. In this work, operando neutron imaging is deployed on a high-mass-loading NMC 811 cathode of 33 mg/cm 2 (5.0 mAh/cm 2 ) and directly visualizes the lithiation prioritization of the cathode active material (CAM) from the solid electrolyte membrane side to the current collector side. In addition to the tortuosity, another key limitation on ion transfer in the cathode arises from the mismatch between the uniform distribution of the solid electrolyte (catholyte) in the conventional composite cathode and the non-uniform Li + flux generated by the faradaic reaction of CAMs. Therefore, we engineer a gradient in the catholyte concentration to match the Li + flux distribution as a means of eliminating the ion transfer obstacle. This approach demonstrates enhanced rate performance, even with high-mass-loading cathodes. A LiCoO 2 composite cathode with 100 mg/cm 2 high-mass-loading exhibits an areal capacity of 10.4 mAh/cm 2 at a current density of 2.25 mA/cm 2 . This work provides insight into the ion-transport limitation in thick cathodes and demonstrates an effective gradient design to overcome the kinetic barrier and achieve high battery performance.
We propose employing a quantum heat engine as a sensitive probe for thermal baths. In particular, we study a single-atom Otto engine operating in an open thermodynamic cycle. Owing to its cyclic nature, the engine is capable of translating small temperature differences between two baths into a macroscopic oscillation in a flywheel. We present analytical and numerical modeling of the quantum dynamics of the engine and estimate it to be capable of detecting temperature differences as small as 2 μK. This sensitivity can be further improved by utilizing quantum resources such as squeezing of the ion motion. The proposed scheme does not require quantum state initialization and is able to detect small temperature differences in a wide range of base temperatures.
Lithium ion batteries (LIBs) are encouraging electrochemical devices with remarkable properties including a high energy/power density, fast charging capability, and low self-discharge rate. Further increase in energy density as well as safe usage is needed for next-generation LIBs in electric transportation vehicles. Solid-state electrolytes (SSEs) are very promising for high-performance LIBs since they enable improved safety along with increased energy density compared to flammable liquid organic electrolytes. However, utilizing SSEs with a Li metal anode is very challenging due to the possibility of undesired side reactions and the formation of an unstable solid-electrolyte interphase. Therefore, it is critical to enhance the stability of SSEs against the Li anode. One feasible approach is to form a thin and conductive interlayer between the Li anode and solid-state electrolyte. Atomic layer deposition (ALD) is a unique technique for conformal coating of complex 3D structures with finely controlled film thickness (at the atomic scale). ALD coating on the surface of SSEs can be adopted for engineering solid-electrolyte interfaces with desired attributes and improved stability. In this review paper, we have discussed recent progress in implementing the ALD technique for depositing thin layers on various SSE configurations including lithium phosphorus oxynitride (LiPON), garnets, oxides, perovskites, sulphides, Li 3 BO 3 –Li 2 CO 3 (LBCO), and sodium super ionic conductors (NASICON). We have also highlighted the major areas for future research and development in the field. We believe that this review will be very helpful for directing future research on implementing ALD for synthesizing stable and high-performance SSEs with an engineered solid-electrolyte interface for next-generation electrochemical devices (e.g., Li-ion batteries, supercapacitors, and flow batteries).
Nitrogen vacancy (NV)-containing nanodiamonds are widely used in quantum sensing applications due to their high sensitivity to magnetic fields, relatively low cost, and ability to be initialized, manipulated, and read out at room temperature. Quantum sensing techniques such as optically detected magnetic resonance (ODMR) and spin relaxometry have exploited the sensitivity of the NV nanodiamonds to magnetic fields to detect a range of analytes, such as pH, metal ions, and biomolecules. However, diversifying the sensing targets accessible by NV diamond quantum sensors typically requires careful engineering of the diamond surface chemistry with stimuli-responsive functional groups. Here, a simple protocol for coating NV nanodiamonds with the zeolitic imidazole framework 8 (ZIF-8), a widely used metal-organic framework, is presented. ZIF-8 is a highly porous material that has been used as a selective sensor for gasses, metal ions, and other analytes. The material is well-characterized by x-ray diffraction, transmission electron microscopy, scanning electron microscopy, x-ray photoelectron spectroscopy, and luminescence spectroscopy. Encapsulation of NV nanodiamonds with a porous scaffold such as ZIF-8 provides a promising method for improving the selectivity for the quantum sensing of various analytes. Importantly, the ZIF-8 coating does not impact the luminescence properties of the NV diamond, which is a key readout in ODMR and spin relaxometry sensing approaches. Indeed, the ODMR spectra with and without the ZIF-8 shell is nearly identical. Moreover, the ZIF-8 coating increases the longitudinal spin relaxation time of the NV nanodiamond by a factor of 4 relative to aggregated diamond, a desirable outcome for spin relaxation-based quantum sensing. Metal-organic framework composites with nanodiamonds thus are an exciting strategy for enhancing NV nanodiamond performance in applications such as quantum sensing and quantum-enhanced nuclear magnetic resonance spectroscopy.
For two-dimensional (2D) layered semiconductors, control over atomic defects and understanding of their electronic and optical functionality represent major challenges towards developing a mature semiconductor technology using such materials. Here, we correlate generation, optical spectroscopy, atomic resolution imaging, and ab initio theory of chalcogen vacancies in monolayer MoS 2 . Chalcogen vacancies are selectively generated by in-vacuo annealing, but also focused ion beam exposure. The defect generation rate, atomic imaging and the optical signatures support this claim. We discriminate the narrow linewidth photoluminescence signatures of vacancies, resulting predominantly from localized defect orbitals, from broad luminescence features in the same spectral range, resulting from adsorbates. Vacancies can be patterned with a precision below 10 nm by ion beams, show single photon emission, and open the possibility for advanced defect engineering of 2D semiconductors at the ultimate scale.
Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years. Furthermore, both large parameter spaces and high sampling variability necessitate a large number of experiments. As such, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.
This Final Technical Report summarizes work completed under Award Number DEEE0009833, titled "Low-cost, Highly Efficient and Fast Thermally Pressed Scalable Carbon-based Planar Perovskite Solar Cells." The project addressed the central technical problem that carbon-electrode perovskite solar cells (C-PSCs) can reduce electrode costs and improve environmental durability, but they have historically lagged noble-metalcontact devices due to poor carbon/perovskite contact, high carbon-electrode resistance, imperfect hole extraction, and insufficient operational stability. The Statement of Project Objectives (SOPO), therefore, required systematic engineering of thermally pressed carbon-based planar perovskite solar cells by improving the carbon/perovskite interface quality, improving carbon-electrode conductivity, and further increasing device stability. The work advanced understanding of carbon-based perovskite photovoltaics by connecting device performance to three coupled mechanisms: interfacial recombination at the perovskite/hole-transport-layer/carbon stack; lateral and vertical transport losses in carbon contacts; and instability driven by moisture, heat, illumination, ion migration, and slow/variable manufacturing steps.