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At least 1,603 records · Page 89

Capturing Coupled Structural and Electronic Motions During Excited-State Intramolecular Proton Transfer via Computational Multiedge Resonant Inelastic X-ray Scattering

Proton-transfer processes build the foundation of many chemical processes. In Excited State Intramolecular Proton Transfer (ESIPT) processes the proton transfer process is impulsively started through light. Here, in this study, we explore the changes in coupled atomic and electronic motions during and following ESIPT through computational time-resolved Resonant Inelastic X-ray Scattering (trRIXS). Excited-state Ab Initio Molecular Dynamics (AIMD) simulations combined with Time-Dependent Density Functional Theory (TDDFT) calculations were performed for 10-hydroxybenzo[h]quinoline to obtain trRIXS signatures. RIXS at both the nitrogen and oxygen K-edges were computed to resolve the dynamics electronic structure from both the proton donor and acceptor perspective. The results show how RIXS can reveal the local electronic structure, the coupling between different electronic states and how electronic structure and coupling change during the proton transfer process. Additionally, we observe a strong correlation between spectral changes and structural changes during ESIPT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Interfacial Structure on Heterogeneous Nucleation of Amorphous Carbonates

For this work, classical molecular dynamics simulations were performed to provide physical insight into the impact of interfacial structure on the heterogeneous nucleation of amorphous calcium carbonate (ACC, CaCO 3 ·H 2 O) and amorphous magnesium carbonate (AMC, MgCO 3 ·H 2 O) by using α-quartz as a model substrate. Interfacial structure and energies were computed for ACC and AMC in contact with the (100), (001), and (101) α-quartz surfaces. The simulations showed α-quartz surfaces drew water molecules out of the carbonate nuclei to form a partial hydration layer. The formation of a partial hydration layer and its disruption to the ACC/AMC structure meant the α-quartz–ACC/AMC interfaces were not energetically favored relative to separate α-quartz–water and ACC/AMC–water interfaces and, thus, homogeneous ACC/AMC nucleation was favored over heterogeneous nucleation. The CMD simulations hence provided an atomic-level explanation for a reported nonclassical growth mechanism whereby carbonate minerals grow via homogeneous nucleation and subsequent surface attachment of amorphous intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing Ultrafast Intersystem Crossing Pathways in Molecular Pt Dimers Using Time-Resolved Wide-Angle X-ray Scattering

Vibronic coupling between transition metal charge transfer states is a potential mechanism for enhancing the intersystem crossing (ISC) rate. Vibronic coupling-driven ISC has been observed in Pt­(II) dimer complexes, where the trajectory across excited-state pathways is tuned by atomic displacements via Pt–Pt stretching vibrations. Time-resolved wide-angle X-ray scattering (TR-WAXS) was utilized to quantify the Pt–Pt contraction following metal–metal-to-ligand charge transfer (MMLCT) excitation in Pt dimers with different bridging ligands. Both complexes exhibit Pt–Pt bond formation with a decrease in Pt–Pt distance of ∼ 0.25 Å and coherent vibrational wavepackets (CVWPs) encoded in the Pt–Pt contraction of both dimers. However, the complexes exhibit different time-dependent evolution of their CVWPs. Analysis of interference patterns between different CVWPs is used to track the trajectory across the excited-state surfaces. Furthermore, this work demonstrates that the interference between CVWPs in ultrafast TR-WAXS encodes indirect information regarding electronic excited-states to reveal the Pt dimer bridge-dependent ISC mechanism.

Computational chemistry↗

A Meta-Generalized Gradient Approximation for the Cavity-Dependent Exchange-Correlation Interaction in Strongly Coupled Light–Matter Systems

Strong light–matter coupling in optical cavities enables the manipulation of chemical and physical properties without altering molecular composition. Theoretical modeling of such phenomena requires exchange-correlation (XC) functionals that account for both electron–electron and electron–photon (ep) interactions within quantum electrodynamical density functional theory (QEDFT). In this work, we develop a meta-generalized gradient approximation (meta-GGA) specifically targeting the cavity-dependent XC interaction in strongly coupled light–matter systems. This novel approximation is built upon a new semilocal polarizability approximation, which draws from the jellium-with-a-gap model, and can be extended to a “global hybrid” variant that goes beyond the isotropic model from previous approximations. The polarizability model yields significantly improved dispersion coefficients and benchmark calculations with the cavity-dependent XC functional demonstrate improved agreement with QED Hartree–Fock (QED-HF) reference energies. Application to the regioselectivity of brominated nitrobenzene intermediates reveals the functional’s capacity to capture cavity-induced energetic shifts. In conclusion, our results advance the Jacob’s ladder of functionals for QEDFT and provide a practical tool for modeling polaritonic chemistry.

Approximation↗

Deconstructing Chirality: Probing Local and Nonlocal Effects in Azobenzene Derivatives with X-ray Circular Dichroism

Resolving molecular chirality on the atomic scale remains a critical challenge in chemistry. Conventional Optical Circular Dichroism spectroscopy often overlooks subtle and localized structural features. Here, we computationally investigate site-specific X-ray circular dichroism (XCD) across a series of trans-azobenzene derivatives to deconstruct and interpret chiroptical signals at the atomic level. Our modeling reveals that XCD is capable of distinguishing dichroic contributions arising from both a local chiral center and a global molecular twist, revealing their intricate interplay and potential for constructive or destructive interference. We show that sterically induced global distortions can dominate the XCD signal in some cases, even suppressing the response from the chiral center itself. This insight suggests a new molecular design principle for tuning the chiroptical activity, which we extend by proposing strategies to achieve unidirectional photoisomerization through steric gearing. Altogether, this work establishes a quantitative framework for engineering chiroptical responses, laying the foundation for the design of functional chiral systems utilizing principles of unidirectional molecular motor-like conformational dynamics.

X-ray spectroscopy↗

Self-Assembly of a Triblock Copolymer in the Presence of a Rigid Conjugated Polyelectrolyte

The properties of conducting polymers are strongly influenced by structural changes induced by long-range order, which can be achieved by using block copolymers that self-assemble into crystalline structures. These blends result in unique mesophases distinct from the pure components with self-assembly behavior modulated by solution conditions and polymer architectures. High-throughput small-angle X-ray scattering data of aqueous Pluronic P123 (PEO 20 –PPO 70 –PEO 20 ) and conjugated polyelectrolyte poly[3-(potassium-4-butanoate) thiophene-2,5-diyl] (PPBT) blends at various concentrations and temperatures were automatically classified into phase maps by autophasemap, an unsupervised statistical analysis algorithm. The outlined phase boundaries revealed that adding PPBT to high P123 concentrations induced a transition from cubicly ordered spherical micelles to hexagonally packed cylindrical micelles. Shear alignment via rheological small-angle neutron scattering of the blends produced monolithic oriented cubic and hexagonal crystal gels. Furthermore, these insights into the self-assembly of conductive polymer blends will aid in the design of soft materials with tunable structural and electronic properties.

36 MATERIALS SCIENCE↗

Directed Synthesis of Gold Nanoparticle Superstructures Using Self-Assembling Peptoids Containing Metal-Bonding N-Heterocyclic Carbenes

N-Heterocyclic carbene (NHC) ligands, with strong metal-binding affinity, offer a robust platform for constructing organic–inorganic nanohybrids with high stability and tunable properties. However, achieving precise structural control in a simple manner remains challenging. Here, we report a one-pot synthesis of nanohybrids using self-assembling peptoids functionalized with histidine-2-ylidene, which simultaneously enable peptoid assembly and NHC–metal binding. Histidine-2-ylidene-functionalized peptoids were designed to self-assemble and provide NHC binding sites, while AuNPs served as the inorganic component due to NHCs’ strong affinity for gold surfaces. The resulting peptoid-NHC@AuNPs form well-defined vesicles that are characterized by UV–vis spectroscopy, X-ray photoelectron spectroscopy, and electron microscopy. Importantly, the vesicle size and morphology can be tuned via the peptoid sequence or environmental conditions. Further experiments highlight the crucial role of the NHC sites in the formation and stabilization of these nanohybrids. This modular strategy offers a versatile route to fabricating functional NHC-based nanohybrids for potential applications in sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shallow Rate-Redox Potential Scaling in Aqueous Molecular Oxygen Reduction Electrocatalysis Across a Family of Iron Macrocycles

Rate-overpotential scaling relationships have been employed widely to understand trends in oxygen reduction reaction (ORR) electrocatalysis by dissolved metal macrocycles in organic electrolytes. Similar scaling relationships remain unknown for surface-adsorbed ORR electrocatalysts in the acidic aqueous environments germane to proton-exchange membrane (PEM) fuel cells. Herein, we examine ORR catalysis in aqueous perchloric acid media for a structurally diverse array of iron macrocycle complexes adsorbed on Vulcan carbon black. The macrocycles encompass Fe– N 4 , Fe–N 2 N' 2 and Fe–N x C 4-x motifs bearing pyrrolic, pyridinic, and N-heterocyclic carbene (NHC) moieties in the primary ligation sphere, giving rise to a 670 mV range in Fe(III/II) redox potentials, E Fe(III/II) . Experimental Tafel data in the micropolarization regime were extrapolated to the E Fe(III/II) to furnish estimated per-site-normalized current density (j per-site ) values that span ~4.6 orders of magnitude across the family of compounds. Despite the structural diversity of this family of compounds, extrapolated j per-site values correlate with the Fe(III/II) redox potentials in a roughly log-linear fashion with a shallow scaling factor of approximately 145 mV/decade. Further, these findings highlight that negative shifts in E Fe(III/II) lead to diminishing returns in catalytic rate promotion and suggest that changes to the primary ligating environment in a macrocycle are insufficient to break fundamental rate-potential scaling relationships in aqueous ORR catalysis. Together these studies motivate the further development of higher-potential iron complexes that employ motifs beyond the equatorial ligation plane to enhance ORR catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen Adsorption, Reactivity, and Catalysis on Colloidal Iron Carbide Nanoparticles

Supported iron carbide particles have long served as catalysts for CO hydrogenation (the Fischer Tropsch synthesis, FTS) and continue to be attractive. Despite this, little is known about their chemistry. Reported here is a colloidal Fe x C nanoparticle (NP) model system that allows direct observation of surface hydrogen and CO, as well as quantification of the surface H. Dodecylamine-capped Fe x C NPs (DDA-Fe x C NPs) were synthesized through solution-phase carburization of Fe NPs and form stable colloids in low-polarity organic solvents. Treatment of these colloids with H 2 or D 2 produced highly hydrogenated materials, and FTIR spectra of DDA-Fe x C-D n showed that most of the D binds to carbides, with at least four distinct v(C-D) modes. The surface C-H(D) bonds were all reactive, transferring hydrogen to alkenes and other reagents in solution. Titration and ICP measurements showed a 0.17:1 ratio of added H:total Fe, or roughly. 40 H per 1.8 nm DDA-Fe x C NP. Conversely, CO was preferentially bound to surface Fe sites, with FTIR spectra showing a single broad v(CO) that shifted with CO coverage or co-adsorption of H 2 . The DDA-Fe x C NPs were active catalysts for both olefin hydrogenation and the FTS, under mild conditions and without catalyst pre-treatment. The CO hydrogenation reactions yielded a broad distribution of long-chain linear paraffins and olefins. Though quantitative comparisons with typical FTS results are not possible because of our use of sealed batch reactors and other factors, the observations of high catalytic reactivity demonstrate the relevance of this model system to iron-carbide catalysis. DFT calculations on model slab surfaces with varying iron carbide stoichiometries revealed that the thermodynamically preferred surface adsorption sites are C for H ads and Fe for CO ads . A variety of binding sites and binding energies were found for each adsorbate. We are unaware of previous studies indicating that a diverse array of C-H bonds is the primary source of reactive H on iron carbides. Experimentally, the diversity of *C-H sites was evident in reactions with H-atom donors and abstractors of different strengths, from both the reaction stoichiometries and IR spectra. The different surface–H binding energies correlate with the v(C-D) stretching frequencies. Furthermore, these insights into complex iron carbide surfaces and catalysis could assist catalyst design, and they showcase the importance of stoichiometric studies of reaction intermediates.

08 HYDROGEN↗

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗

Ab Initio Structures and Energetics of Hydrated Flat and Terrace-Step Surfaces of Forsterite (Mg 2 SiO 4 )

Forsterite (Mg 2 SiO 4 ), a model divalent metal silicate mineral, has been extensively studied in the context of mineral carbonation. Although dissolution is a key step in this process, the mechanisms by which forsterite dissolves under high CO 2 conditions remain poorly understood. Atomistic simulations could aid in exploring these mechanisms, but it is essential first to understand the structures and energetics of the relevant forsterite surfaces. We present an ab initio study of the structure and surface energy at 0 K of the flat $(010), (110), (001), (111), (021), (101)$ and $(120)$ faces of forsterite using the density functional PBE Hamiltonian and a plane-wave basis set. Dry surfaces became stabilized upon hydration through the formation of bonds between surface Mg and O from water, as well as by the formation of hydrogen bonds. According to surface energy values, the stability order of the hydrated forsterite faces was found to be $(120) < (101) < (021) < (111) < (001) < (110) < (010)$. We also investigated the energetics of the terrace-step $(0\bar{41})$ surface as a model site for forsterite dissolution. Among all the facets, the $(0\bar{41})$ surface is the least stable termination in water. Hydration of Mg atoms on the $(0\bar{41})$ surface increases their susceptibility to dissolution. The presence of a step and its hydration destabilizes the terraces, making step retreat more likely than a dissolution front advancing along the [010] direction. This research will support future simulations to investigate forsterite dissolution in water under CO 2 -rich conditions.

PBE Hamiltonian↗

Cathode-Confined Polysulfide Retention-Release Reprograms Li 2 S Deposition in High-Loading Li–S Batteries

High-loading lithium-sulfur (Li-S) cells operated with lean electrolyte are limited by polysulfide crossover to Li metal and by transport-limited liquid-solid conversion that forms passivating Li 2 S films. Here, we show that a cathode-facing separator coating of carboxylated multiwalled carbon nanotubes acts as a cathode-confined polysulfide reservoir with intermediate binding. Early in discharge it captures newly generated polysulfides at the separator interface, suppressing shuttle reactions. As polysulfides are consumed, the reservoir buffers concentration gradients and feeds reactants back to the cathode, shifting Li 2 S deposition from burst-like film growth to progressive, three-dimensional, porous formation. Synchrotron XRD and S K-edge XANES, together with Scharifker–Hills nucleation analysis and depth-of-discharge EIS/DRT, substantiate this coupled transport–reaction control. With 4.3 mg S cm -2 and E/S = 5, cells reach 4.2 mAh cm -2 and retain 90% capacity over 100 cycles at 20 °C.

25 ENERGY STORAGE↗

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model

54 ENVIRONMENTAL SCIENCES↗

Automated Redox Titrations via Interdigitated Electrode Arrays: Application to the Mediated Electron Transfer Interrogation of Charge and Rate on Electrodeposited Polymers

Mediated electron transfer (MET) plays a crucial role in energy storage and conversion technologies such as redox targeting flow batteries (RTFBs), yet its experimental investigation often requires labor-intensive and low-throughput setups. To address this, we developed a microfabricated interdigitated electrode array (IDA) platform that enables automated, high-throughput electrochemical redox titration measurement to be performed to study the MET process. Our redox titration method enables simultaneous measurement of the charge capacity and rate of MET processes on a material or surface. Automated redox titration (ART) facilitates systematic investigation of the MET process across a broad parameter space, exemplified through the study of polypyrrole (PPy) and a pyrene-4,5,9,10-tetrone azo group-based polymer (PTAP), both redox-active polymers relevant to various energy storage applications. Using PPy as a model material, 500 redox titration measurements were conducted within 50 h, varying the electrode gap widths, polymer charging potentials, voltammetric scan rates, and electrolyte concentrations. Finite-element simulations confirmed the electrochemical responses and elucidated the kinetics of the MET reactions. Our automated methodology was further tested with PTAP, revealing a surprising charging potential dependence on the rate of MET. The automation, flexibility, and scalability of our redox titration platform pave the way not only for advanced studies of MET processes relevant to RTFBs, but also with implications in the understanding of next-generation energy storage materials, molecular electrocatalysis, and biosensing.

electrochemical analysis↗

Nanoporous Fe 2 O 3 and Soluble Fe(II) Intermediates Accelerate the Electrodeposition of Fe in NaOH(aq)

Electrochemical conversion of iron oxide to iron metal can enable low-cost batteries for long duration energy storage and zero-emissions ironmaking for steel. Iron oxides, such as hematite, can be electrochemically reduced to metallic iron in concentrated alkaline electrolytes at modest temperatures, but the relative influences of solid-state and dissolved intermediates at practical reaction rates remains unclear. Here, in this study, we prepare a homologous set of well-defined hematite particles to measure how the nanoscale morphology of oxides controls both their reactivity and apparent reduction mechanism in concentrated hydroxide. Correlated electron microscopy and rotating-ring-disk-electrode measurements revealed that nanoporous hematite and solid intermediates formed iron via a dissolution-redeposition pathway. In contrast, dense hematite particles directly formed iron metal via reactive fracture. While previous studies on iron electrowinning have primarily emphasized the role of particle diameter at the micron scale, these results demonstrate the importance of the dissolution-redeposition pathway to support rapid reaction rates and suggest that nanoscale porosity controls iron oxide reactivity at temperatures <100 °C. Therefore, iron-oxide-to-metal electrolyzers and fast-charging iron-air batteries supported by curtailed electricity can increase the rate of metal formation by accelerating fracture and dissolution in reactant oxides.

TEM↗

Phosphate-Based Approaches for Dechlorination and Treatment of Salt Waste from Electrochemical Processing of Used Nuclear Fuel: A Perspective on Recent Work

Phosphate-based reagents are being considered by the U.S. Department of Energy (DOE) Office of Nuclear Energy to process halide salt-based nuclear wastes for stabilization prior to disposal. As evidenced by the Experimental Breeder Reactor-II (EBR-II) project, electrochemical processing (pyroprocessing) can be employed to recover uranium and other actinides for reintegration into the nuclear fuel cycle from metallic fuels. The resultant salt-based wastes generated from electrochemical processing of EBR-II fuel contains fission products within a LiCl–KCl eutectic salt that necessitate appropriate disposal. This paper provides an overview of recent efforts to support halide-based salt waste treatment for disposition, as well as a basis for comparison with other related efforts in salt waste treatment through salt partitioning initiatives. The U.S. DOE has selected a phosphate waste form reference material for further investigation and longer-term studies.

electrorefiner↗

Cell-Free-Based Thermophilic Biocatalyst for the Synthesis of Amino Acids from One-Carbon Feedstocks

Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.

bacteria↗