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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Selectively extracting lithium from single and mixed cathode materials

With the burgeoning reliance on lithium-ion batteries for sustainable energy solutions and electric transportation, the environmental and resource management associated with battery disposal are increasingly critical. Addressing these challenges necessitates innovative recycling techniques that recover valuable battery components, particularly lithium. This research introduces a universal, eco-friendly approach tailored for the efficient selective extraction of lithium from both single and mixed cathode materials, achieving impressive selective leaching efficiencies of lithium (99.51 % for LFP, 90 % for NMC, and 97.24 % for mixed cathode). Surprisingly, leaching efficiency of lithium from NMC can be significantly improved by introducing LFP since LFP can remove the dense transition-metal salts on the surface of NMC. The extracted lithium is recovered as lithium carbonate with battery-grade purity. This study also highlights the reuse of formic acid and the adoption of oxygen as an oxidizing agent to prevent wastewater production. Therefore, this method provides a robust foundation for sustainable lithium battery recycling.

economically and environmentally feasible↗
DOE OSTI2024

Recycled graphite enabled superior performance for lithium ion batteries

Recycling graphite attracts growing attention since cumulative amount of spent Li-ion batteries and the shortage of graphite supply chain. Although various recycling methods have been reported, the recycled graphite cannot reach the strict commercial standards of purity, scalability, efficiency, and capacity, preventing it from battery manufacturing. Herein, the important roles of defects and functional groups on the graphite surface are deeply studied, and a closed-loop graphite recycling process with the surface recovery and modification for the graphite from the end-of-life batteries is demonstrated. The recovered graphite delivers a purity of over 99.9 % and an average initial coulombic efficiency of 91.5 %. Compared with commercial graphite in industrial standard battery testing parameters, full cells with recovered graphite possess enhanced rate reversibility, doubled cycle life, over 10 % higher capacity along with half anode material cost. In conclusion, these impressive results not only underscore the transformative potential of surface reconstruction and modification in graphite recycling, but also present economic feasibility and sustainable pathway for significantly improving battery performance and addressing global resource challenges via integration with the hydrometallurgical recycling process.

25 ENERGY STORAGE↗
DOE OSTI2025

Low-temperature access to active iron and iron/nickel nitrides as potential electrocatalysts for the oxygen evolution reaction

Low-temperature, scalable routes to transition metal nitride (TMN) nanoparticles are desirable for a wide range of applications, yet their synthesis typically requires high temperatures (>350 °C) and reactive gas environments (e.g., NH 3 or H 2 /N 2 ). Here, we report a colloidal synthesis of mono- and bimetallic TMN nanoparticles using preformed metal carbonyl clusters as precursors and urea or diethylenetriamine (DETA) as nitrogen sources. This strategy enables access to size-controlled, phase-pure ε-Fe 3 N x and Fe y Ni 3−y N nanoparticles at temperatures below 300 °C, without the need for flowing reactive gas atmospheres. By systematically varying nitrogen precursor, reaction temperature, and cluster identity, we achieve tunable nitrogen stoichiometry (x) and phase selectivity between N-rich and N-poor TMNs. Structural and magnetic characterization confirms clean decomposition of the precursors and phase formation consistent with controlled nitridation at the nanoscale. Preliminary electrochemical measurements in alkaline media demonstrate that these materials exhibit oxygen evolution reaction (OER) overpotentials comparable to RuO 2 , highlighting their viability for future electrocatalytic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗
DOE OSTI2026

Investigation of Flux Spreading in a Light-Trapping, Planar-Cavity Receiver for Enclosed Solar Particle Heating

Concentrating solar thermal power (CSP) technology development has recently focused on increasing the operating temperatures to accommodate high efficiency power cycles and thermochemical processes. Inert solid particles as heat transfer media enable solar receivers to operate above 700 degrees Celsius resulting in increased system thermal efficiency compared to the conventional molten salt based CSP system. An open-cavity falling-particle solar receiver that can efficiently heat particles by direct heating from concentrated solar radiation faces challenges with large particle losses from wind and unable to support thermochemical reactions. A light-trapping, planar cavity reiver (LTPCR) where particles are indirectly heated can significantly minimize the particle losses during the operation, support thermochemical reactions, and offer scalability potential. The LTPCR features an array of vertical planar receiver/absorber panels arranged within a cavity configuration. Concentrated solar radiation from heliostats is focused onto the receiver walls, where heat is indirectly transferred to solid particles flowing inside the receiver channels. Heat transfer occurs through direct contact between the receiver panel walls and particles, and can be enhanced by fluidizing particles with air. This fluidization increases particle-wall contact and extends particle residence time, maximizing heat transfer efficiency. The unique vertical planar receiver structure originated from a near-blackbody tubular light absorber, effectively distributing the incoming solar beam spread across the panel walls and trapping light. This flux spreading effect, driven by cosine projection, converts high incident solar flux into a lower, more uniform heat flux on the panel walls. This redistribution enhances heat transfer efficiency between particle-wall or reaction gases-wall, while preventing localized overheating of the receiver panel. Indirect planar cavity solar receivers completely separate solid particles from the ambient environment that can greatly reduce the thermal losses in heated particles resulting in high efficiency at high temperatures above 700 degrees Celsius. This design ensures no particle losses to the environment during the operation while open-cavity designs can experience significant particle losses from wind. An experimental investigation was conducted to observe flux spreading on the receiver panel wall. A lab-scale prototype planar receiver, fabricated using Haynes 230 alloy, was tested under direct concentrated solar radiation using the high-flux solar furnace (HFSF) facility at NREL. The experiment was performed under normal peak radiative heat fluxes ranging from 800 to 1900 kW/m2. A temperature distribution on the panel wall was measured using a thermal imaging camera (FLIR A 6600). To prevent overheating at the receiver front tip, prism-shaped heat shields (Zircar UNIFROM C1) were placed in front of the receiver, and their influence on flux spreading was also studied. Absorbed flux distribution on the panel wall was modeled using SolTrace. The total solar power and flux distributions delivered from HFSF were determined based on the heliostat mirror optical properties, direct normal irradiance (DNI) on the on-sun testing days, peak flux measurement during the on-sun testing, and shutter/attenuator settings Due to the large incident angles of the solar beam on the panel wall, the angular optical properties of Haynes 230 alloy and Zircar heat shields were incorporated into the model. This flux distribution model was then integrated into a computational fluid dynamics (CFD) simulation to predict the receiver panel wall temperature, which was compared with the experimental measurements. Both prediction and measurements identified a temperature hotspot at the backside of the panel, indicating that the incident solar beam can fully reach to the rear of the receiver. The heat shields positioned at the front of the receiver effectively reduced the excessive temperature rise at the receiver front tip. Overall, the temperature was well distributed over the panel wall, with a minor hotspot at the back of the receiver. The model slightly overpredicted the temperature, possibly due to discrepancies in optical properties of the panel and an underprediction of thermal loss in the receiver. The advancement of the particle LTPCR offers a viable alternative to open-cavity receivers by addressing particle loss issues. Additionally, it presents a pathway for enabling solar thermochemical processes, extending CSP technology beyond power generation to fuel and chemical production.

14 SOLAR ENERGY↗
DOE OSTI2024

Computing with a Chemical Reservoir

Contemporary computation is expensive, with large language models and artificial intelligence becoming more common in daily life. However, high-performance computing is reaching the limits in speed and energy expenditure, and domain science requires ever-increasing computational capacity, with simulations and data analysis pipelines ever-growing in complexity. As we progress towards post-exascale computation, with the associated high energy costs, new methods of energy-conscious computation are required. Novel analog and hybrid digital-analog systems can overcome these challenges, and chemical reactions offer a promising avenue. Computers based on chemistry can provide compact desktop devices with immense computational power. These devices are readily scalable by considering greater reaction systems or vessels, meeting the high-performance requirements for scientific workflows. In this article, we present ChemComp, a compilation pipeline for the conversion of ordinary differential equations into implementable chemical reactions. We then demonstrate the solving capabilities of ChemComp by emulating a potential chemical reservoir device. We leverage the multi-layer intermediate representation (MLIR) compiler framework to implement an expressive chemical reaction abstraction and propose a path for chemical reaction networks (CRNs) to represent mathematical problems effectively. Combined, we demonstrate a potential workflow that can harness chemistry’s computing power to create energy-efficient, high-performance computation systems for contemporary computing needs.

artificial intelligence↗
DOE OSTI2026

A photochargeable semiconductor for highly efficient dehydrogenative coupling of amines

The development of materials with high photocatalytic efficiency is essential for sustainable chemical transformations. Here, in this work, we introduce photochargeable zinc indium sulfide nanocrystals with notable charge storage capacity, enabling highly efficient photocatalytic dehydrogenative coupling of amines. Combined with a nickel cocatalyst, the nanocrystals deliver diamines and hydrogen at rates exceeding 120 mmol per gram of photocatalyst per hour, with > 95% selectivity and an apparent quantum efficiency of up to 39.4% under ambient conditions. The system exhibits excellent scalability, demonstrated by a reaction on a 20-g scale, and broad versatility in promoting amino acid ester coupling and polymerization reactions with concurrent hydrogen evolution. Mechanistic studies attribute the photocharging capability of zinc indium sulfide nanocrystals to in situ-generated trap states such as sulfur vacancies, which extend hydrogen production into the dark catalytic cycle and enhance the overall charge utilization efficiency. These findings position photochargeable semiconductors as promising platforms for a wide range of photocatalytic applications.

nanoscale devices↗
DOE OSTI2025

Faceted NiO(111) nanosheets: morphological and catalytic evolution for the oxygen evolution reaction

The renaissance of the energy system through the use of green hydrogen by water electrolysis lies behind the development of abundant, active, and scalable catalysts for the oxygen evolution reaction (OER). A fundumental understanding of the surface properties for these materials is of vital importance in producing viable heterogenous catalysts. In this feature article, we summarize several years of collaborative work on a uniquely faceted NiO(111) nanosheet possessing hexagonal holes with a focus on understanding how the evolution of the catalyst surface and bulk composition effects OER performance. The importance of surface faceting, morphological evolution, and metal combination by different doping strategies are all analyzed and summarized to further improve the material's performance. Furthermore, microwave and supercritical synthesis processes are utilized to understand how varying wet-chemical techniques effect the formation of the NiO(111) nanosheet and activity of the material. We discuss our chosen strategies and the difficulties encountered with optimizing a catalyst surface for the OER.

08 HYDROGEN↗
DOE OSTI2026

Theoretical Insights into Reaction-Induced Transformation and Tuning of Catalytic Behavior in Heterogenous Catalysis

Reaction-induced transformations in heterogenous catalysis represent diverse phenomena that challenge traditional views of static catalyst surfaces. From surface adsorbate dynamics, atomic rearrangements, to composition and phase transitions, these processes reveal the profound differences between idealized model systems under ultrahigh vacuum and the complex, evolving interfaces that govern real catalytic behaviors under reaction conditions. Here, this perspective reviews recent theoretical efforts to provide atomic-level mechanistic insights into significant reaction-induced transformations and their impact on catalytic activity and selectivity. It underscores the need for an integrated framework that combines predictive simulations with operando characterization to uncover active sites and mechanisms under realistic operating conditions. Achieving this requires accelerating existing simulations to fully capture diverse reaction-induced surface dynamics, enabling scalable and accurate modeling of catalysts as condition-dependent, dynamically evolving systems. Such approaches are critical to bridge the gap between theory and practice, offering a pathway to more impactful and predictive catalyst design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

The Influence of Residual Copper Catalyst on the Polymer-to-Ceramic Conversion of a Click-Derived Polycarbosilane

Preceramic polymers (PCPs) are a key class of materials for the preparation of advanced ceramic components. Following conventional polymer processing and subsequent pyrolysis, polymer-derived ceramic (PDC) fibers, monoliths, and composites offer novel engineering opportunities for aerospace applications. Despite the rapidly emerging commercial applications of PDCs, many basic scientific questions remain regarding the structural transformation of the polymer to the final ceramic and how processing variables affect PDC materials properties. PCPs prepared using a mild and scalable copper (Cu) catalyzed azide/alkyne “click” reaction have been demonstrated as a unique class of material that can bind with transition metals, ultimately producing ultrahigh temperature ceramics (UHTCs) upon pyrolysis. Unexpectedly, it was found that the removal of residual Cu catalyst from a model click-derived polycarbosilane PCP significantly reduced the ceramic yield during pyrolysis. Herein, we report the influence of Cu impurities on polycarbosilane-derived SiC ceramics and present a mechanistic understanding of the unintended role of Cu in the polymer-to-ceramic conversion process. Synchrotron-based scattering and spectroscopy methods were implemented to track the evolution of different atomic species and local structures as well as the influence of Cu toward atomic-scale structures in the final ceramics. It was determined that Cu impurities catalyze the formation of silicon carbide through the formation of an intermediate molten copper/copper silicide, ultimately increasing the ceramic yield. Overall, this contribution highlights the need to carefully assess the interplay between the chemistries needed for PCP synthesis and their potential influence on final PDCs following processing.

Ponder, Jr., James F. [Air Force Research Laborato↗
DOE OSTI2026

Covalent Adaptable Networks: Reprocessable Cross-Linked Polymers

Thermoset polymers have desirable properties, such as excellent thermal and mechanical stability, but their covalent cross-links typically prevent repair or recycling. By enabling and controlling dynamic exchange reactions within polymer networks, their covalent bonds rearrange and allow the polymer to be reshaped. These viscoelastic polymer networks, now known as covalent adaptable networks (CANs), are an important frontier for improving plastic circularity, as well as for designing valuable stimuli-responsive materials. This Review describes the history of CANs, dating back to the early days of polymer science, and the evolution of their classification and nomenclature. A comprehensive survey of dynamic reactions and linkage chemistries is provided, as well as methods to characterize and reprocess CANs. Beyond straightforward reprocessing, many advanced applications of CANs and their composites are now emerging. Lastly, we provide perspective on how the development of new chemistries, strategies to control stimuli-responsive bond exchange and mechanical properties, and a deep understanding of exchange reactions will advance this field toward scalable, sustainable, and high-value materials.

Sun, Molly [Northwestern University, Evanston, IL ↗
DOE OSTI2025

Phase change material integrated core–shell catalyst for in situ thermal control in methanol synthesis from syngas

A model-guided core–shell catalyst design is presented for methanol synthesis, featuring a phase change material (PCM) core encapsulated by a Cu–Zn–Al 2 O 3 (CZA) catalytic shell. The PCM enables in situ thermal management by absorbing reaction heat at its melting point, mitigates the kinetic decline at high temperatures and therefore avoids low conversion, prevents hot spots, and stabilizes the reaction temperature. A two-dimensional axisymmetric, non-isothermal packed-bed reactor model (COMSOL 6.3) was developed for a 10 g system. Simulations evaluate three PCM candidates, that is, LiNO 3 , 9 wt% LiCl + 91 wt% LiNO 3 , and commercial H250, with melting points near 244–250°C. Results indicate that CO conversion can increase from 34.4% to 52.4%, and methanol production can improve by 69% compared to a conventional packed-bed reactor. Beyond methanol synthesis, the PCM-integrated core–shell concept provides a scalable approach for thermal control in exothermic reactions, improving reactor efficiency and safety.

core–shell catalyst↗
DOE OSTI2025

Locally Confined Polysulfide-Reactive Electrolytes for Shuttle-Free Sodium–Sulfur Batteries

Sodium-sulfur batteries promise high-energy-density and sustainable electrochemical energy storage but suffer from uncontrolled polysulfides dissolution and high sodium reactivity. These challenges fundamentally originate from poor electrolyte-electrode compatibility. Current electrolyte research inadequately addresses the trade-off between minimal polysulfides solvation and stabilizing sodium interfaces. Here, we present a locally-confined polysulfide-reactive electrolyte strategy that mediates the polysulfide dissolution dynamics and sodium stability by leveraging an electrophilic solvating species with a localized high-concentration electrolyte. This design enables shuttle-free cell operation by synergistically restricting the global solvating power of the electrolyte through intermolecular interactions and locally scavenging sparingly dissolved polysulfides via electrolyte electrophilicity. The precisely confined surface reaction facilitates a protective cathode-electrolyte interface, realizing a quasi-solid-state sulfur conversion in our liquid ether-based electrolyte, which crucially avoids crossover-induced catastrophic sodium-metal degradation. The proposed electrolyte demonstrates long-term cycling of high-mass-loading sulfur cathodes (> 3 mg S cm −2 with commercial carbon host and 70 wt% sulfur content), which afford 710 mA h g −1 over 400 cycles in coin cells and steady pouch cell operation over 180 cycles. Furthermore, this work establishes a scalable electrolyte design protocol that regulates the reaction chemistry of highly reactive electrodes, offering a pathway toward sustainable renewable energy storage.

25 ENERGY STORAGE↗
DOE OSTI2026

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

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

Harnessing photoenzymatic reactions for unnatural biosynthesis in microorganisms

Photoenzymatic catalysis enables new-to-nature transformations, but its scalability is limited by high enzyme loading, costly cofactors, and radical-induced instability. Here we report the integration of light-driven photoenzymatic reactions into the cellular metabolism of Escherichia coli, bridging flavin-based photobiocatalysis with biosynthesis. Using synthetic biology strategies, we engineered microbial cells to continuously produce olefin substrates and ene-reductase photoenzyme while regenerating cofactors directly from glucose. By externally supplying radical precursors or by introducing synthetic pathways for their in situ production, we enabled fermentation-based microbial photobiosynthesis, achieving high titers and demonstrating its feasibility for scale-up in bioreactor. This approach extends photobiocatalysis from in vitro applications to in vivo semi-biosynthesis and complete biosynthesis, revealing its full potential for integrating light-driven reactions into cellular metabolism.

Bioproducts↗
NASA NTRSDate not supplied

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗
DOE OSTI2025

Alternative Solid‐State Synthesis Route for Highly Fluorinated Disordered Rock‐Salt Cathode Materials for High‐Energy Lithium‐Ion Batteries

Abstract Fluorination has been identified as a key element for enabling the stable cycling of earth‐abundant manganese‐based disordered rock salt (DRX) cathodes. However, fluorination in the DRX bulk remains a challenge for scalable solid‐state synthesis. In this study, a tailored reaction pathway is proposed to synthesize a highly fluorinated DRX. It is demonstrated for the first time that the unconventional precursors, Li 6 MnO 4 , MnF 2 , and TiO 2 , can avoid the formation of Mn‐based intermediates (such as Li 2 (Mn,Ti)O 3, LiMnO 2 , and Mn 3 O 4 ), which, once formed, persist until the synthesis temperature reaches close to or above that required for fluorine volatility. Therefore, this method can form a highly fluorinated DRX with a composition of Li 1.23 Mn 0.40 Ti 0.37 O 2−y F y ( y = 0.29–0.34) at a low temperature (800 °C) relative to that required for conventional DRX solid‐state reactions (≥900 °C). Li 1.23 Mn 0.40 Ti 0.37 O 2−y F y ( y = 0.29–0.34) delivers a specific capacity above 300 mAh g −1 and a specific energy of 980 Wh kg −1 at 30 °C. Detailed characterization reveals that this DRX phase reversibly utilizes Mn 2+/3+ redox in the low‐voltage region and Mn 3+/4+ redox in the middle‐voltage range, whereas reversible oxygen redox is observed at high potentials.

Avvaru, Venkata Sai↗
DOE OSTI2025

Imine Reductase-Catalyzed, Radical-Mediated Asymmetric Cyano Group Migration

Functional group migration (FGM) reactions represent a fundamental class of transformations in organic chemistry, enabling the repositioning of functional moieties in nonobvious ways. However, catalytic asymmetric radical-mediated FGMs remain rare due to the inherent challenges of achieving catalyst-controlled enantioselectivity over free radical intermediates. Herein, we repurpose imine reductases (IREDs), a class of biotechnologically important enzymes known for their substrate promiscuity, to enable the first examples of catalytic asymmetric cyano group migration via a radical mechanism. An orthogonal set of radical enzymes, including PbaIREDCym and SmiIREDCym, was engineered, allowing both 1,4- and 1,5-cyano group migration reactions to occur in an enantiodivergent fashion. The use of the nonionic surfactant TPGS-1000 was found to improve both the yield and enantioselectivity of these cyano migration reactions. Furthermore, this biocatalytic process exhibited a broad substrate scope and is readily scalable, affording a rare example of chiral nonamine product assembly with imine reductases. More broadly, stereoselective radical biocatalysis with engineered IREDs and other versatile enzymes provides a potentially general solution to challenging asymmetric FGM reactions.

Biocatalysis↗