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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Material Design Strategies for Recovery of Critical Resources from Water

Population growth, urbanization, and decarbonization efforts are collectively straining the supply of limited resources that are necessary to produce batteries, electronics, chemicals, fertilizers, and other important products. Securing the supply chains of these critical resources via the development of separation technologies for their recovery represents a major global challenge to ensure stability and security. Surface water, groundwater, and wastewater are emerging as potential new sources to bolster these supply chains. Recently, a variety of material-based technologies have been developed and employed for separations and resource recovery in water. Judicious selection and design of these materials to tune their properties for targeting specific solutes is central to realizing the potential of water as a source for critical resources. Here, the materials that are developed for membranes, sorbents, catalysts, electrodes, and interfacial solar steam generators that demonstrate promise for applications in critical resource recovery are reviewed. In addition, a critical perspective is offered on the grand challenges and key research directions that need to be addressed to improve their practical viability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer

Abstract. With the increasing level of offshore wind energy investment, it is correspondingly important to be able to accurately characterize the wind resource in terms of energy potential as well as operating conditions affecting wind plant performance, maintenance, and lifespan. Accurate resource assessment at a particular site supports investment decisions. Following construction, accurate wind forecasts are needed to support efficient power markets and integration of wind power with the electrical grid. To optimize the design of wind turbines, it is necessary to accurately describe the environmental characteristics, such as precipitation and waves, that erode turbine surfaces and generate structural loads as a complicated response to the combined impact of shear, atmospheric turbulence, and wave stresses. Despite recent considerable progress both in improvements to numerical weather prediction models and in coupling these models to turbulent flows within wind plants, major challenges remain, especially in the offshore environment. Accurately simulating the interactions among winds, waves, wakes, and their structural interactions with offshore wind turbines requires accounting for spatial (and associated temporal) scales from O(1 m) to O(100 km). Computing capabilities for the foreseeable future will not be able to resolve all of these scales simultaneously, necessitating continuing improvement in subgrid-scale parameterizations within highly nonlinear models. In addition, observations to constrain and validate these models, especially in the rotor-swept area of turbines over the ocean, remains largely absent. Thus, gaining sufficient understanding of the physics of atmospheric flow within and around wind plants remains one of the grand challenges of wind energy, particularly in the offshore environment. This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. Such phenomena include horizontal temperature gradients that lead to strong vertical stratification; consequent features such as low-level jets and internal boundary layers; highly nonstationary conditions, which occur with both extratropical storms (e.g., nor'easters) and tropical storms; air–sea interaction, including deformation of conventional wind profiles by the wave boundary layer; and precipitation with its contributions to leading-edge erosion of wind turbine blades. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.

17 WIND ENERGY↗
DOE OSTI2020

Opportunities and Challenges from Artificial Intelligence and Machine Learning for the Advancement of Science, Technology, and the Office of Science Missions

In February 2019, the President signed Executive Order 13859, Maintaining American Leadership in Artificial Intelligence. This order launched the American Artificial Intelligence Initiative, a concerted effort to promote and protect AI technology and innovation in the United States. The Initiative implements a government-wide strategy in collaboration and engagement with the private sector, academia, the public, and like-minded international partners. Among other actions, key directives in the Initiative called for Federal agencies to: Prioritize AI research and development investments, Enhance access to high-quality cyberinfrastructure and data, Ensure that the US maintains an international leadership role in the development of technical standards for AI, and Provide education and training opportunities to prepare the American workforce for the new era of AI. The mission of the Department of Energy (DOE) is to ensure America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. In terms of Science and Innovation, the DOE’s mission is to maintain a vibrant US effort in science and engineering as a cornerstone of our economic prosperity with clear leadership in strategic areas. From July to October in 2019, the Argonne, Oak Ridge, and Berkeley National Laboratories hosted a series of four AI for Science Town Hall meetings in Chicago, Oak Ridge, Berkeley, and Washington DC. The four meetings were attended by over 1300 scientists from the 17 DOE Labs, 39 companies, and over 90 universities. The goal of the Town Hall series was ‘to examine scientific opportunities in the areas of artificial intelligence, Big Data, and high-performance computing (HPC) in the next decade, and to capture the big ideas, grand challenges, and next steps to realizing these.’ The discussions at the meetings were captured in the final report of the AI for Science Town Hall meetings.

42 ENGINEERING↗
DOE OSTI2023

Task 2.3: Continuous Counter-Current Chromatography

This task in the Separations Consortium focuses on the development of counter-current chromatography (CCC), which is an advanced liquid-liquid chromatography method. Today, CCC is primarily practiced in batch mode operation, but continuous operation will be required for at-scale deployment in a biorefinery setting. In this task, we are developing a continuous CCC process in collaboration with a company that builds CCC units. This work will be demonstrated on the biorefining challenge of lignin valorization. Specifically, we demonstrate use of continuous CCC for both monomer-monomer and monomer-oligomer separations in multiple lignin streams of relevance to the biorefining industry. Breakthroughs in this area would be useful for BETO goals in both sustainable aviation fuel and biochemicals production, including directly contributing to BETO's 2030 lignin valorization goal. Our approach includes developing new computational modeling approaches to optimize both batch and continuous CCC processes, experimental work to determine optimal solvent systems for multiple lignin streams sourced from BETO-funded projects and industrial collaborators, and techno-economic analysis and life cycle assessment to identify the most impactful areas to ultimately enable this approach in the biorefinery. This task overall will enable high-resolution, multi-component, continuous separations at scale, demonstrated on a grand challenge biorefining problem.

BIOMASS FUELS↗
DOE OSTI2024

The Wind Turbine Rotors of the Future: A Research Agenda from the Big Adaptive Rotor Project

This white paper outlines a roadmap to inform future research efforts around the wind turbine rotors of the future. The document is authored by researchers that have been working on the Big Adaptive Rotor (BAR) and related initiatives at the National Renewable Energy Laboratory and Sandia National Laboratories. The Wind Energy Technologies Office of the U.S. Department of Energy has been funding BAR since 2018. The learnings from BAR have been documented in dozens of publications. This new paper identifies unresolved critical challenges in wind turbine rotor technology and structures them in four large topic areas: 1. Predictive and validated numerical tools. 2. Design methods and standards. 3. Improvements in manufacturing. 4. Technological innovations. Although wind turbines have not changed in their core architecture, with the market almost entirely dominated by three-bladed upwind rotors, a vast amount of research has allowed to introduce technological innovations resulting in a reduction in levelized cost of energy that made wind competitive with all traditional sources of electricity. Focusing on the rotor, blades will keep following the trend of mass and stiffness reduction, will adopt segmentation, and will keep growing in length, both land-based and offshore. To support this continuous innovation, this white paper argues that research efforts in rotor technology at the national labs are best directed to the first three topic areas and to low technology-readiness-levels (1-3) innovations, leaving the task of implementing higher-TRL (4-9) technological innovations to industry stakeholders. This research roadmap is also well aligned with the upcoming roadmap defined during the International Energy Agency 109th Topical Expert Meeting on the Grand Challenges of Wind Energy.

17 WIND ENERGY↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fe-N 4 O-C Nanoplates Covalently Bonding on Graphene for Efficient CO 2 Electroreduction and Zn-CO 2 Batteries

Electrochemical carbon dioxide (CO 2 ) reduction into value-added products holds great promise in moving toward carbon neutrality but remains a grand challenge due to lack of efficient electrocatalysts. Herein, the nucleophilic substitution reaction is elaborately harnessed to synthesize carbon nanoplates with a Fe-N 4 O configuration anchored onto graphene substrate (Fe-N 4 O-C/Gr) through covalent linkages. Density functional theory calculations demonstrate the unique configuration of Fe-N 4 O with one oxygen (O) atom in the axial direction not only suppresses the competing hydrogen evolution reaction, but also facilitates the desorption of *CO intermediate compared with the commonly planar single-atomic Fe sites. The Fe-N 4 O-C/Gr shows excellent performance in the electroreduction of CO 2 into carbon monoxide (CO) with an impressive Faradaic efficiency of 98.3% at -0.7 V versus reversible hydrogen electrode (RHE) and a high turnover frequency of 3511 h -1 . Furthermore, as a cathode catalyst in an aqueous zinc (Zn)-CO 2 battery, the Fe-N 4 O-C/Gr achieves a high CO Faradaic efficiency (≈91%) at a discharge current density of 3 mA cm -2 and long-term stability over 74 h. Here this work opens up a new route to simultaneously modulate the geometric and electronic structure of single-atomic catalysts toward efficient CO 2 conversion.

25 ENERGY STORAGE↗
DOE OSTI2024

Fast Photoactuation Driven by Supramolecular Polymers Integrated into Covalent Networks

Abstract The design of robotic soft matter capable of emulating the complex movements of living organisms such as mechanical actuation, shape transformation, and autonomous translation remains a grand challenge in soft materials science. Functionalized hydrogels are excellent candidates for such materials since they can operate in water and are highly responsive to their environment, but their response times can be slow. This work investigates fast photoactuation of hybrid bonding hydrogels composed of peptide amphiphile (PA) supramolecular nanofibers bonded covalently to merocyanine‐based (MCH + ) photoresponsive networks. By incorporating ionizable acrylic acid (AA) co‐monomers in these networks, photoactuation at nearly neutral pH is observed, which in turn enables a new mechanism to accelerate the response by triggering the bundling of supramolecular nanofibers by rapid proton exchange reactions. Furthermore, this rapid response and its consequent large shape transformations lead to hydrogels capable of spontaneously tracking external light sources inspired by pedicellariae, defensive organs present in echinoderms like the starfish and the sea urchin. This work suggests that hybrid bonding polymers (HBPs), which leverage the interplay between supramolecular assemblies and covalent networks, offer novel strategies to design rapidly actuating soft robotic materials.

Cezan, S. Doruk↗
DOE OSTI2020

Single Cobalt Sites Dispersed in Hierarchically Porous Nanofiber Networks for Durable and High-Power PGM-Free Cathodes in Fuel Cells

Increasing catalytic activity and durability of atomically dispersed metal–nitrogen–carbon (M–N–C) catalysts for the oxygen reduction reaction (ORR) cathode in proton-exchange-membrane fuel cells remains a grand challenge. In this study, a high-power and durable Co–N–C nanofiber catalyst synthesized through electrospinning cobalt-doped zeolitic imidazolate frameworks into selected polyacrylonitrile and poly(vinylpyrrolidone) polymers is reported. The distinct porous fibrous morphology and hierarchical structures play a vital role in boosting electrode performance by exposing more accessible active sites, providing facile electron conductivity, and facilitating the mass transport of reactant. The enhanced intrinsic activity is attributed to the extra graphitic N dopants surrounding the CoN 4 moieties. The highly graphitized carbon matrix in the catalyst is beneficial for enhancing the carbon corrosion resistance, thereby promoting catalyst stability. The unique nanoscale X-ray computed tomography verifies the well-distributed ionomer coverage throughout the fibrous carbon network in the catalyst. The membrane electrode assembly achieves a power density of 0.40 W cm –2 in a practical H 2 /air cell (1.0 bar) and demonstrates significantly enhanced durability under accelerated stability tests. The combination of the intrinsic activity and stability of single Co sites, along with unique catalyst architecture, provide new insight into designing efficient PGM-free electrodes with improved performance and durability.

25 ENERGY STORAGE↗
DOE OSTI2021

A General Strategy to Immobilize Single‐Atom Catalysts in Metal–Organic Frameworks for Enhanced Photocatalysis

Abstract Single‐atom catalysts (SACs) are witnessing rapid development due to their high activity and selectivity toward diverse reactions. However, it remains a grand challenge in the general synthesis of SACs, particularly featuring an identical chemical microenvironment and on the same support. Herein, a universal synthetic protocol is developed to immobilize SACs in metal–organic frameworks (MOFs). Significantly, by means of SnO 2 as a mediator or adaptor, not only different single‐atom metal sites, such as Pt, Cu, and Ni, etc., can be installed, but also the MOF supports can be changed (for example, UiO‐66‐NH 2 , PCN‐222, and DUT‐67) to afford M 1 /SnO 2 /MOF architecture. Taking UiO‐66‐NH 2 as a representative, the Pt 1 /SnO 2 /MOF exhibits approximately five times higher activity toward photocatalytic H 2 production than the corresponding Pt nanoparticles (≈2.5 nm) stabilized by SnO 2 /UiO‐66‐NH 2 . Remarkably, despite featuring identical parameters in the chemical microenvironment and support in M 1 /SnO 2 /UiO‐66‐NH 2 , the Pt 1 catalyst possesses a hydrogen evolution rate of 2167 µmol g –1 h –1 , superior to the Cu 1 and Ni 1 counterparts, which is attributed to the differentiated hydrogen binding free energies, as supported by density‐functional theory (DFT) calculations. This is thought to be the first report on a universal approach toward the stabilization of SACs with identical chemical microenvironment on an identical support.

Sui, Jianfei↗
DOE OSTI2022

Magnetic Ordering in a High‐Spin Donor–Acceptor Conjugated Polymer

Abstract The development of open‐shell organic molecules that magnetically order at room temperature,which can be practically applied, remains a grand challenge in chemistry, physics, and materials science. Despite the exploration of vast chemical space, design paradigms for organic paramagnetic centers generally result in unpaired electron spins that are unstable or isotropic. Here, a high‐spin conjugated polymer is demonstrated, which is composed of alternating cyclopentadithiophene and benzo[1,2‐ c ;4,5‐ c ′]bis[1,2,5]thiadiazole heterocycles, in which macromolecular structure and topology coalesce to promote the spin center generation and intermolecular exchange coupling. Electron paramagnetic resonance (EPR) spectroscopy is consistent with spatially localized spins, while magnetic susceptibility measurements show clear anisotropic spin ordering and exchange interactions that persist at room temperature. The application of long‐range π‐correlations for spin center generation promotes remarkable stability. This work offers a fundamentally new approach to the implementation of this long‐sought‐after physical phenomenon within organic materials and the integration of manifold properties within emerging technologies.

Steelman, Michael E.↗
DOE OSTI2020

Fast-Charging and Ultrahigh-Capacity Lithium Metal Anode Enabled by Surface Alloying

Li metal anodes are going through a great revival but they still encounter grand challenges. One often neglected issue is that most reported Li metal anodes are only cyclable under relatively low current density (<5 mA cm -2 ) and small areal capacity (<5 mAh cm -2 ), which essentially limits their high-power applications and results in ineffective Li utilization (<1%). Herein, it is reported that surface alloyed Li metal anodes can enable reversible cycling with ultrafast rate and ultralarge areal capacity. Low-cost Si wafers are used and are chemically etched down to 20-30 mu m membranes. Simply laminating a Si membrane onto Li foil results in the formation of LixSi alloy film fused onto Li metal with mechanical robustness and high Li-ion conductivity. Symmetric cell measurements show that the surface alloyed Li anode has excellent cycling stability, even under high current density up to 25 mA cm -2 and unprecedented areal capacity up to 100 mAh cm -2 . Furthermore, the surface alloyed Li anode is paired with amorphous MoS 3 cathode and achieves remarkable full-cell performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-Entropy Metal Sulfide Nanoparticles Promise High-Performance Oxygen Evolution Reaction

Transition metal sulfide with a multi-elemental nature represents a class of promising catalysts for oxygen evolution reaction (OER) owing to its good catalytic activity. However, its synthesis remains a grand challenge due to the thermodynamic immiscibility of the constituent multimetallic elements in a sulfide structure. Herein, we for the first time report a high-entropy metal sulfide (HEMS, i.e., (CrMnFeCoNi)Sx) solid solution nanoparticles. Computational and X-ray photoelectron spectroscopy analysis suggest that the (CrMnFeCoNi)S x exhibits a synergistic effect among metal atoms that leads to desired electronic states to enhance OER activity. The (CrMnFeCoNi)Sx nanoparticles showed one of the best activities (low overpotential 295 mV at 100 mA cm -2 in 1 M KOH solution) and good durability (only slight polarization after 10 hours by chronopotentiometry) compared with the unary, binary, ternary, and quaternary sulfide counterparts. This work opens up a new synthesis paradigm for high-entropy compound nanoparticles for highly efficient electrocatalysis applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Data‐Driven Safety Risk Prediction of Lithium‐Ion Battery

Abstract Inevitable safety issues have pushed battery engineers to become more conservative in battery system design; however, battery‐involved accidents still frequently are reported in headlines. Identifying, understanding, and predicting safety risks have become priorities to further accelerate technology and industry development. However, diverse loading scenarios, significantly varied stress‐induced short circuit mechanisms, and highly coupled mechanical–electrochemical safety behaviors have remained grand challenges. Herein, the safety risk is termed as the probability of the mechanical triggering of an internal short circuit, to reflect the safety related behaviors of lithium‐ion batteries. Based on a mechanical model and experimental results, a sufficient dataset is generated consisting of strain states and their corresponding safety risks, covering both cylindrical and pouch cells, various states of charges, and loading conditions. Machine‐learning tools combined with the established finite element mechanical model are applied to predict the safety risks of the cells. The results achieve a high level of accuracy on the test data (the relative error of the average short circuit prediction deviation is less than 6.2%.). This work underpins the safety risk concept and highlights the promise of physics combined with data‐driven modeling methodology to predict the safety behaviors of energy storage systems.

Jia, Yikai↗
DOE OSTI2024

Sustainedly High-Rate Electroreduction of CO 2 to Multi-Carbon Products on Nickel Oxygenate/Copper Interfacial Catalysts

Copper (Cu) is the most attractive electrocatalyst for CO 2 reduction to multi-carbon (C 2+ ) products with high economic value in considerable amounts. However, the rational design of a structurally stable Cu-based catalyst that can achieve high activity and stability towards C 2+ products remain a grand challenge. Here, in this study, a highly stable nickel oxygenate/Cu electrocatalyst is developed with abundant NiOOH/Cu interfaces by in situ electrochemical reconstruction. The nickel oxygenate/Cu electrocatalyst achieves a superior Faradaic efficiency of 86.3 ± 3.0% and a record partial current density of 2085 A g -1 for C 2+ products with long-term stability. In situ experimental and theoretical studies demonstrates that the exceptional performance in generating C 2+ products is attributed to the presence of the NiOOH/Cu interfaces which increase *CO coverage, lower energy barrier for *CO coupling and stabilize *OCCO simultaneously. This work provides new insights into the rational design of electrocatalysts to achieve stable and efficient electrocatalytic CO 2 reduction capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Photochemically‐Driven CO 2 Release Using a Metastable‐State Photoacid for Energy Efficient Direct Air Capture

Abstract One of the grand challenges underlying current direct air capture (DAC) technologies relates to the intensive energy cost for sorbent regeneration and CO 2 release, making the massive scale (GtCO 2 /year) deployment required to have a positive impact on climate change economically unfeasible. This challenge underscores the critical need to develop new DAC processes with substantially reduced regeneration energies. Here, we report a photochemically‐driven approach for CO 2 release by exploiting the unique properties of an indazole metastable‐state photoacid (mPAH). Our measurements on simulated and amino acid‐based DAC systems revealed the potential of mPAH to be used for CO 2 release cycles by regulating pH changes and associated isomers driven by light. Upon irradiating with moderate intensity light, a ≈55 % and ≈68 % to ≈78 % conversion of total inorganic carbon to CO 2 was found for the simulated and amino acid‐based DAC systems, respectively. Our results confirm the feasibility of on‐demand CO 2 release under ambient conditions using light instead of heat, thereby providing an energy efficient pathway for the regeneration of DAC sorbents.

Premadasa, Uvinduni I.↗
DOE OSTI2023

Electron Delocalization Enables Sulfone-based Single-solvent Electrolyte for Lithium Metal Batteries

Li-metal batteries (LMB), although providing high energy density, face the grand challenge of identifying good electrolyte solvents for cycling. Common solvents are either only stable against lithium metal anode or only stable against LiNi x MnyCo 1-x-y O 2 (NMC) cathode. There is significant effort trying to increase the cathode stability for ether electrolytes, which are in general stable against lithium metal anode. In comparison, there is much less effort trying to increase the anode stability of electrolytes that are stable against NMC cathode. One example is the sulfone-based electrolyte. It has good cathode stability but is hindered from practical application because of (1) high viscosity and poor wetting capability and (2) poor anode stability. Here, we solve these issues by modifying the sulfone molecules using resonance and electron withdrawing effect. The viscosity is significantly reduced by delocalizing the electrons through introducing additional oxygen on the molecular backbone and applying appropriate fluorination. The resulting molecule 2,2,2-trifluoroethyl mesylate (TFEM) has decreased Lewis basicity and less reactivity toward Li + . In conclusion, the electrolyte based on TFEM as single solvent enables cycling of LMB under harsh conditions of low N/P ratio (21 mg/cm 2 NMC811 and 50 μm Li) with 90 % capacity retention after 160 cycles at C/3 discharge rate.

25 ENERGY STORAGE↗
DOE OSTI2023

Designing Heteroatom-Codoped Iron Metal–Organic Framework for Promotional Photoreduction of Carbon Dioxide to Ethylene

Rational engineering active sites and vantage defects of catalysts are promising but grand challenging task to enhance photoreduction CO 2 to high value-added C2 products. In this study, we designed an N,S-codoped Fe-based MIL-88B catalyst with well-defined bipyramidal hexagonal prism morphology via a facile and effective process, which was synthesized by addition of appropriate 1,2-benzisothiazolin-3-one (BIT) and acetic acid to the reaction solution. Under simulated solar irradiation, the designed catalyst exhibits high C 2 H 4 evolution yield of 17.7 μmol g -1 ∙h, which has been rarely achieved in photocatalytic CO 2 reduction process. The synergistic effect of Fe-N coordinated sites and reasonable defects in the N,S-codoped photocatalyst can accelerate the migration of photogenerated carriers, resulting in high electron density, and this in turn helps to facilitate the formation and dimerization of C-C coupling intermediates for C 2 H 4 effectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗