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At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2022

A modified model parametrization algorithm for solving a special type of heat and mass transfer systems

A new method for solving nonlinear heat and mass transfer design tasks was considered. Systems using the Number of Transfer Units (NTU) method are a special type of mathematical model of heat and mass exchangers. It was observed, that the NTU models in a form of differential-algebraic equations (DAEs) cannot be directly solved with higher values of NTU. The requirements for consistent initial conditions, as well as numerical limitations of DAEs solvers, result, that the solution to the considered design problems that cannot be obtained by a classical direct shooting procedure. To overcome the presented difficulties, the αDAE model optimization algorithm was adjusted for solving NTU-based models. The new approach consists of 3 main steps: 1) task discretization by a multiple-shooting approach, 2) design an appropriate function $f_{NTU}$(α) to effectively influence the variability of the state variables described by dynamical relations, 3) the iterative numerical optimization algorithm for the new parametrized system. Moreover, computations can be performed by a chosen numerical optimization approach, which can be communicated with an available outer procedure for solving differential-algebraic equations. The presented algorithm was implemented and applied to solve the design task with the NTU model of a counter-flow exchanger. Here, the new approach was used to modify the system dynamics to influence the difficulty of the considered problem. Finally, the presented method enabled failure-free numerical computations for the higher values of the NTU parameter.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Thiol- and Disulfide-Functionalized Polycyclooctene: Metathesis Polymerization, Degradation, and Reformation

The enormous global production and use of polymers and plastics, combined with slower and less efficient disposal and recycling methods, have led to a worldwide growth in plastic waste. Here, we describe an approach that builds degradability into macromolecular polyolefins through the design of telechelic oligomers with reactive functional groups that enables control over polymer deconstruction and reconstruction. Our work exploits disulfide-containing polymers that have emerged as promising cyclable materials due to their dynamic reversibility (bond formation and cleavage) driven by redox chemistry under mild conditions. Specifically, we describe the synthesis of a telechelic α,ω-dithiopolycyclooctene (PCOE) by ring-opening metathesis polymerization using a dithioacetate chain transfer agent, followed by deprotection to convert the chain-end thioacetates to thiols. This process was studied towards control over the degree of oxidation to yield disulfide-containing PCOE, followed by an evaluation of reductive degradation and oxidative repolymerization. Overall, this approach facilitates the production of disulfide-containing unsaturated polyolefins and the integration of degradable and reformable moieties into soluble, processable, metathesis-derived polymers.

Lee, Kyoungwon↗

DOE OSTI2025

Manipulating the Second Coordination Shell of Single-Atom Fe for Enhanced Fenton Reaction

While current methods use oxidizable metals as electron donors to effectively reduce Fe 3+ , they suffer from the irreversible oxidation of these metals, ultimately compromising the catalyst’s longevity. To address this challenge, we engineered the second coordination shell of a single-atom Fe center by doping boron (B) onto a graphene-based support (Fe 1 /B-graphene) and utilized H 2 O 2 as the electron source for efficient Fe 2+ regeneration. Experimental results, supported by theoretical calculations, revealed that the Fe–O–B motif functions like a micro galvanic cell, with intermediary O atoms facilitating electron transfer between electrodes. Specifically, electrons consumed during H 2 O 2 activation at Fe 1 sites (positive electrode) are replenished by electrons extracted from H 2 O 2 at B atoms (negative electrode), where the activation energy for H 2 O 2 oxidation is significantly lower than that at Fe 1 sites. This study offers inspirational insights into the design of Fenton catalysts through precise regulation of the second coordination shell, demonstrating the potential of tailoring the outer coordination environment of single-atom catalysts to enhance catalytic performance across various reactions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Bidirectional Suzuki Catalyst Transfer Polymerization of Poly( p -phenylene)

Suzuki catalyst transfer polymerization (SCTP) has emerged as an effective method for accessing length-controlled π-conjugated poly(p-phenylene). Regio-controlled functional group sequencing along the backbone and the chain ends of synthetic polymers remains a challenge for the successful integration of organic semiconductors in sensors and electronic devices. Here, we report a bidirectional SCTP system based on dinuclear palladium(II) initiators. Functional groups transferred during the initiation and termination steps unlock independently addressable synthetic handles at the polymer core and respective chain ends. These functional groups open opportunities for late-stage regio-controlled and chemoselective derivatizations. Control over key polymer parameters, including molecular weight (M n ), dispersity ( Đ = M w /M n ), degree of polymerization ( DP ), termination efficiency, and functional group interconversion, is corroborated by size exclusion chromatography (SEC) and NMR spectroscopy. The modular design of SCTP initiators, in combination with commercially available terminating groups, represents a highly flexible toolbox for late-stage polymer conjugation, e.g., chemoselective anchoring groups for integration with functional electronics or bioorthogonal conjugation for molecular sensing.

Aldehydes↗

DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

DOE OSTI2020

Ultra-Light Hybrid Composite Door Design, Manufacturing and Demonstration

New Corporate Average Fuel Economy regulations require improved fuel efficiency of the future vehicle fleet. Weight reduction is key to achieving these targets. Replacing metallic body and chassis components with carbon fiber-reinforced composites offers the most weight reduction potential at up to 70%. Introduction of the BMW i3 and i8 in 2014 required mass production processes to meet 20,000+ units per year. Preforming with High Pressure Resin Transfer Molding has been implemented and meets rate, cost, and performance requirements. We will advance these technologies to develop an ultra-light driver’s side door for the vehicle with production rates of 40,000 units annually per plant in Detroit, Michigan. This project sought to employ a comprehensive systems approach for designing, manufacturing, and demonstrating an ultra-light hybrid composite automotive door. Composite structural components are integrated with other functional systems to reduce part count and full-system weight by a minimum of 42.5%. The approach will be demonstrated on a driver’s- side front door and will consider all fit, functional, safety, and cost requirements. These concepts will be evaluated using structural and crash simulations and linked to a manufacturing feasibility study, resulting in producible designs of an integrated door system. A cost model will evaluate part of the cost for the various designs and will ensure the cost target of less than $5 per pound of weight saved is met. Hybrid composites consisting of carbon, glass, and metal components will be included in our trade-off studies to satisfy these cost and performance goals.

02 PETROLEUM↗

DOE OSTI2025

From Obsolete to Optimal (ATR Demineralized Water System)

My project was migrating a Human-Machine Interface (HMI) and Programmable Logic Controller (PLC) program from legacy software to a modern platform, enhancing operational efficiency and eliminating unsupported, obsolete equipment. Initially, I used a migration tool to transfer the programs to the new software, then manually updated variables to align with the new PLC. I optimized the PLC code by leveraging new scaling features in the I/O cards, removing over 45 obsolete rungs, and enhancing clarity with functional tag aliases. Next, I modernized the HMI's visuals with an updated color scheme and 3D buttons. I developed multiple interface versions iteratively refining them based on operator feedback. I also designed and created a dedicated "Rounds" screen incorporating insights from a previous intern’s project to streamline daily rounds. To improve clarity, consistency, and efficiency I redesigned the entire interface. Adding visual indicators to enhance operational awareness: red is used for values outside normal specifications, green for normal operating modes, yellow for manual mode, and grey for offline units. Additionally, I added a dynamic visual representation of tank levels, creating PLC logic to show the level in inches as well as inches and feet. I then incorporated a navigation sidebar to facilitate efficient screen transitions. Risk of human error was mitigated by defining narrow input ranges for tank level shutoff and password protecting setpoint changes. I also fixed issues with datatypes that caused inaccuracies in the original code. Overall, this comprehensive upgrade significantly enhanced the HMI's functionality, user experience, and operational reliability.

47 - OTHER INSTRUMENTATION↗

DOE OSTI2022

Thioester synthesis by a designed nickel enzyme models prebiotic energy conversion

The formation of carbon–carbon bonds from prebiotic precursors such as carbon dioxide represents the foundation of all primordial life processes. In extant organisms, this reaction is carried out by the carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS) enzyme, which performs the cornerstone reaction in the ancient Wood–Ljungdahl metabolic pathway to synthesize the key biological metabolite, acetyl-CoA. Despite its significance, a fundamental understanding of this transformation is lacking, hampering efforts to harness analogous chemistry. To address these knowledge gaps, we have designed an artificial metalloenzyme within the azurin protein scaffold as a structural, functional, and mechanistic model of ACS. We demonstrate the intermediacy of the Ni I species and requirement for ordered substrate binding in the bioorganometallic carbon–carbon bond-forming reaction from the one-carbon ACS substrates. The electronic and geometric structures of the nickel-acetyl intermediate have been characterized using time-resolved optical, electron paramagnetic resonance, and X-ray absorption spectroscopy in conjunction with quantum chemical calculations. Moreover, we demonstrate that the nickel-acetyl species is chemically competent for selective acyl transfer upon thiol addition to biosynthesize an activated thioester. Drawing an analogy to the native enzyme, a mechanism for thioester generation by this ACS model has been proposed. The fundamental insight into the enzymatic process provided by this rudimentary ACS model has implications for the evolution of primitive ACS-like proteins. Ultimately, these findings offer strategies for development of highly active catalysts for sustainable generation of liquid fuels from one-carbon substrates, with potential for broad applications across diverse fields ranging from energy storage to environmental remediation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Plankton energy flows using a global size-structured and trait-based model

Plankton community models are critical tools for understanding the processes that shape marine plankton communities, how plankton communities impact biogeochemical cycles, and the feedbacks between community structure and function. Here, using the flexible Marine Biogeochemistry Library (MARBL), we present the Size-based Plankton ECological TRAits (MARBL-SPECTRA) model, which is designed to represent a diverse plankton community while remaining computationally tractable. MARBL-SPECTRA is composed of nine phytoplankton and six zooplankton size classes represented using allometric scaling relationships for physiological traits and interactions within multiple functional types. MARBL-SPECTRA is embedded within the global ocean component of the Community Earth System Model (CESM) and simulates large-scale, emergent patterns in phytoplankton growth limitation, plankton phenology, plankton generation time, and trophic transfer efficiency. The model qualitatively reproduces observed global patterns of surface nutrients, chlorophyll biomass, net primary production, and the biogeographies of a range of plankton size classes. In addition, the model simulates how predator:prey dynamics and trophic efficiency vary across gradients in total ecosystem productivity. Shorter food chains that export proportionally more carbon from the surface to the ocean interior occur in productive, eutrophic regions, whereas in oligotrophic regions, the food chains are relatively long and export less organic matter from the surface. The union of functional type modeling with size-resolved, trait-based modeling approaches allows MARBL-SPECTRA to capture both large-scale elemental cycles and the structure of planktonic food webs affecting trophic transfer efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Towards a High Fidelity Training Environment for Autonomous Cyber Defense Agents

Cyber defenders are overwhelmed by the frequency and scale of attacks against their networks. This problem will only be exacerbated as attackers leverage AI to automate their workflows. Autonomous cyber defense capabilities could aid defenders by automating operations and adapting dynamically to novel threats. However, existing training environments fall short in areas such as generalization, explainability, scalability, and transferability, making it intractable to train agents that will be effective in real networks. In this paper we take an important step towards creating autonomous cyber defense agents — we present a high fidelity training environment called Cyberwheel that includes both simulation and emulation capabilities. Cyberwheel simplifies customization of the training network and easily allows redefining the agent’s reward function, observation space, and action space to support rapid experimentation of novel approaches to agent design. It also provides visibility into agent behaviors necessary for agent evaluation and sufficient documentation / examples to lower the barrier to entry. As an example use case of Cyberwheel, we present initial results training an autonomous agent to deploy cyber deception strategies in simulation.

Oesch, T↗

DOE OSTI2022

Finite Element Modeling of Electrochemical Polishing of Niobium in Hydrofluoric-Sulfuric Acid Electrolyte

Niobium (Nb) used in superconducting radio-frequency cavities requires smooth surface to achieve optimal performance. In this work, a finite element model that coupled electrochemistry, heat transfer, and fluid dynamics was developed to investigate the electrochemical polishing mechanisms of Nb, using experimentally measured polarization results of coupon samples as validations. The current and potential distribution, oxide growth kinetics of Nb in a complex cavity geometry was investigated as a function of temperature and coolant flow. A low temperature coolant with intermediate flow rate was found to reduce surface current and ensure oxide uniformity. These results could shed light on the design of future particle accelerators.

SRF accelerator cavity↗

DOE OSTI2024

Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with significantly curved x-ray optics

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. The current capabilities and possibility for improvements in X-ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. In the case of Fizeau interferometry, metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for measuring slightly curved X-ray optics. However, for even moderately curved aspherical X-ray mirrors the flat-reference calibration is not sufficiently accurate and stitching Fizeau interferometer-based surface metrology is used to mitigate the problem. But still, the retrace and aberration errors, as well as the limited spatial resolution, described with the instrument transfer function (ITF), can be transferred into the optical surface topography of X-ray mirrors obtained in stitching metrology. For ITF calibration, we have developed an original technique, based on test standards structured as two-dimensional (2D) highly-randomized (HR) binary pseudo-random arrays (BPRAs). The technique employs the unique properties of the HR BPRA patterns in the spatial frequency domain., i.e. the inherent 2D power spectral density of the HR BPRA pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. Here, we explore technological, metrological, and analytical aspects essential for calibration of the retrace and aberration errors of Fizeau interferometers using different types of tilted test samples, including a super-polished reference mirror for the re-trace calibration and the uniformly redundant array (URA) BPRA standards for the geometrical distortion (aberration) calibration. While the first method was previously demonstrated by researchers at DIAMOND Light Source, a method based on the URA BPRA is described and demonstrated here for the first time. We outline the design and fabrication process used in fabrication of URA BPRA test standards, and present the results of application of the URA BPRA standards demonstrating the high efficacy of our approach to geometrical distortion calibration of Fizeau interferometers. We also discuss the possible sources of unexpected peculiarities of the systematic errors, including an astigmatic character of the retrace error, observed with Fizeau interferometers at the Advanced Light Source X-Ray Optics Laboratory.

Munechika, Keiko↗

DOE OSTI2024

An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems

Deep Reinforcement Learning (DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers (RBCs), but it still lacks scalability and generalisation due to the necessity of using tailored models for the training process. Transfer Learning (TL) is a potential solution to address this limitation. However, existing TL applications in building control have been mostly tested among buildings with similar features, not addressing the need to scale up advanced control in real-world scenarios with diverse energy systems. This paper assesses the performance of an online heterogeneous TL strategy, comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and Python. The study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage (TES). The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems, different building envelope features, occupancy schedule and boundary conditions (e.g., weather and price signal). The TL approach incorporates model slicing, imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target buildings. Results show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL controllers. Moreover, online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to RBC. Conversely, online TL achieves worse performance compared to offline DRL in either transductive or inductive settings. However, offline Deep Reinforcement Learning (DRL) agents should be trained at least for 15 episodes to reach the same level of performance as the online TL. Therefore, the proposed online TL methodology is effective, completely model-free and it can be directly implemented in real buildings with satisfying performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗

DOE OSTI2020

Air-transfer production method for large-area picosecond photodetectors

We have designed and prototyped the process steps for the batch production of large-area micro-channel-plate photomultipliers (MCPPMT) using the “air-transfer” assembly process developed with single LAPPD TM modules. Results are presented addressing the challenges of designing a robust package that can transmit large numbers of electrical signals for pad or strip readout from inside the vacuum tube and of hermetically sealing the large-perimeter window–body interface. We have also synthesized a photocathode in a large-area low-aspect-ratio volume and have shown that the micro-channel plates recover their functionality after cathode synthesis. These steps inform a design for a multi-module batch facility employing dual nested low-vacuum and ultra-high-vacuum systems in a small-footprint. The facility design provides full access to multiple MCP-PMT modules prior to hermetic pinch-off for leak-checking and real-time photocathode optimization.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗

DOE OSTI2022

Kinetics and Reactor Modeling of VFA Ketonization for Sustainable Aviation Fuel Production

Ketonization of volatile fatty acids (VFAs) produced via arrested methanogenesis of wet waste represents the only unit operation of wet waste upgrading to sustainable (net-zero or negative life cycle CO2 emissions) aviation fuel not currently in industrial practice. Ketone product yields of close to 100% have been obtained during gas-phase reactions of VFAs over oxide catalysts at the laboratory scale, but design of an industrial ketonization reactor requires understanding of the impacts of reactant and product partial pressures, deactivation, and heat and mass transport phenomena on observed ketonization rates. Our work leverages rigorous kinetic analysis of ketonization processes to inform reactor scale-up efforts through packed-bed reactor modeling. We first present results of a kinetic study of ketonization of a model VFA, hexanoic acid, over an industrial ZrO2 catalyst performed in a packed-bed microreactor in conditions free of significant heat or mass transfer gradients. Major findings of the analysis include: (i) hexanoic acid saturates all catalyst active sites at relatively low partial pressure (~10 kPa) and (ii) ketonization products 6-undecanone, water, and CO2 inhibit reaction rates. Kinetic data are used to fit a rate expression quantifying the functional dependence of ketonization rate on partial pressures of VFA reactants and ketone, water, and CO2 products. A packed-bed reactor model describing vapor-phase hexanoic acid ketonization over ZrO2 extrudate catalysts is developed based on the kinetic model. The effects of (i) bed- and pellet-scale mass- and heat-transfer limitations and (ii) axial pressure drop guide our development of recommendations for optimal sizing, temperature, and influent flow composition of an industrial-scale ketonization reactor. The quantitative understanding of VFA ketonization developed in this study represents an advance toward derisking the VFA ketonization step of wet waste upgrading to sustainable aviation fuel.

biojet↗

DOE OSTI2023

Electrolyte Reactivity on the MgV 2 O 4 Cathode Surface

Predictive understanding of the solvation-dependent reactivity and molecular interaction of electrolyte ions and solvent molecules on reactive electrodes has been a major challenge but is essential for addressing instabilities and surface passivation that occur at electrode-electrolyte interface (EEI) of multivalent Mg batteries. In this work, the isolated intrinsic reactivities of prominent chemical species present in magnesium bis(trifluoromethanesulfonimide) (Mg(TFSI) 2 ) in diglyme (G2) electrolytes, including ionic (TFSI - , [Mg(TFSI)] + , [Mg(TFSI):G2] + , [Mg(TFSI):2G2] + ) as well as neutral molecules (G2) on magnesium vanadate cathode (MgV 2 O 4 ) surface has been studied using a combination of first-principles calculations and multimodal analysis of well-defined cathode electrolyte interphase (CEI) layers. Here, our calculations show that non-solvated [Mg(TFSI)] + is the strongest adsorbing species on the MgV 2 O 4 surface compared to all other ions while fully solvated [Mg(TFSI):2G2] + are least favorable to decomposition. The cleavage of C-S bonds in TFSI - to form CF 3 - is predicted to be most desired pathway for all ionic species, which is followed by the cleavage of C-O bonds of G2 to yield CH 3 + or OCH 3 - species. The strong stabilization and electron transfer between ionic electrolyte species and MgV 2 O 4 is found to significantly favor these decomposition reactions on the surface compared to intrinsic gas phase dissociation. Experimentally, we used state-of-the-art ion soft landing to selectively deposit mass-selected TFSI - , [Mg(TFSI):G2] + and [Mg(TFSI):2G2] + on MgV 2 O 4 thin film to form well-defined electrolyte-MgV 2 O 4 interface. Analysis of soft-landed interphase using X-ray photoelectron, X-ray absorption near edge structure, electron energy-loss spectroscopies as well as transmission electron microscopy confirmed the presence of decomposition species (e.g., MgFx, carbonates) formed in the interfacial region and the higher amount of MgFx with [Mg(TFSI):G2] + , which corroborates the theoretical observation. Overall, we established the mechanistic pathway for the electrolyte-induced formation of passivating fluorides on MgV 2 O 4 cathode facilitated by the surface adsorption and charge transfer, which provided essential knowledge for rational design of stable electrolytes for multivalent cathodes.

Cathode-electrolyte interphase formation↗