Engineering Atomically Dispersed FeN[subscript 4] Active Sites for CO[subscript 2] Electroreduction
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Lithium‐ion batteries with high gravimetric capacity density and improved cycle life performance under fast‐charging conditions are crucial for widespread electric vehicle (EV) adoption. This study investigates how designing graphite anode microstructure, specifically porosity, and particle‐size gradients, improves lithium‐ion (Li + ) transport during fast‐charging conditions. Three‐layered graphite anodes with varying porosity (24%, 36%, 46%) and particle size gradients (3, 5, 10 μm) were compared to a conventional single‐layered electrode in half‐cell configurations. At room temperature and high discharge rate (2C), both gradient structures showed significantly enhanced capacity retention (80% and 67% vs. 50%) compared to the conventional electrode, highlighting the effectiveness of microstructure engineering for fast charging. The study also investigated the temperature's impact on cycle life. After 200 cycles at 2°C and 45°C, all gradient structures demonstrated superior capacity retention (≈80%) compared to the conventional electrode (35%), suggesting the gradients mitigate degradation rate at high temperatures. Electrochemical impedance spectroscopy confirmed superior Li+ diffusion and lower resistivity in gradient electrodes. Simulations explored the influence of gradient profiles on reaction kinetics across the electrode thickness. Overall, this research demonstrates that the fast‐charging capability of graphite electrodes can be greatly enhanced by engineering the electrode microstructure, thereby making EV technology more accessible and appealing.
Cross-couplings are essential reactions in modern chemical synthesis, enabling the rapid construction of complex molecules from simple precursors. Transition metal catalysts are prized for these transformations because their reactivity and selectivity can be tuned via judicious selection of the metal and ligand. Although enzymes offer analogous opportunities for tuning via protein engineering, their application to cross-coupling remains limited, as nature relies on alternative paradigms for building molecular complexity. Here, we report the cross-coupling of alkyl halides and benzylic carboxylic acids using an engineered flavin-dependent lactate monooxygenase—a photoenzyme. The enzyme achieves this feat by exploiting the redox versatility of the flavin cofactor. Stoichiometric experiments, ultrafast spectroscopy, and computational studies support a mechanism in which photoexcited flavin quinone initiates the reaction via oxidative decarboxylation to generate a benzylic radical. The resulting flavin semiquinone can reduce the alkyl halide to form a second organic radical within the protein active site, which rapidly engages in C(sp 3 )–C(sp 3 ) bond formation. A variant was engineered to control the stereochemical outcome of this radical–radical coupling event, highlighting the ability of the protein to alter the energetic barrier for a mechanistic step that is traditionally understood to be near barrierless. This work demonstrates that the scope for nonnative reaction mechanisms in biocatalysis far exceeds previously established bounds and has potential to solve a variety of reactivity challenges in cross-coupling chemistry.
The use of intermetallic Pt–Co nanocrystals (NCs) for the electrocatalytic oxygen reduction reaction is quickly gaining interest thanks to the higher electrochemical stability of the intermetallic L1 o phase compared to a random alloy A1 phase. However, the thermal treatment that enables the intermetallic phase transformation also causes considerable NC aggregation, resulting in a significant loss of electrochemically active surface area. Herein, we report the use of microwave radiation to induce the intermetallic phase transformation in Cu-doped Pt–Co NCs. We demonstrate that microwave radiation reduces NC aggregation while allowing for a complete phase transformation in only 30 s. Furthermore, these microwave-treated NCs demonstrate higher mass activity for the oxygen reduction reaction while maintaining electrochemical stability similar to the thermally annealed samples.
Efficiency of water splitting for hydrogen production is often limited by the sluggish kinetics of multiple electronic transfers required in the heterogeneous oxygen evolution reaction (OER). Catalyst design for reducing the high OER overpotential remains a major scientific challenge. Lattice-strain engineering, a method for tuning the electronic structure and surface geometric configuration of active sites, may greatly affect the interaction between adsorbates and catalytic surfaces for high activity and stability. Here, in this study, we present the synthesis of biphasic oxides of YPrSrRuMnO x , which consists of distinct phases of Y 2 Ru 2 O 7 pyrochlore and (Pr 0.7 Sr 0.3 )MnO 3 perovskite, and the development of a suitable analytical approach to study the strain–catalytic property relationship. Linear sweep voltammetry results reveal that the biphasic oxide exhibits approximately 3.1 times greater mass activity and 2.4 times larger turnover frequency (TOF) than single-phase Y 2 Ru 2 O 7 in the 0.1 M HClO 4 electrolyte. The biphasic catalyst is also about 3 times more stable than the single-phase oxide under acidic conditions. X-ray photoelectron spectroscopy, nitrogen isotherm, and electrochemical surface area analyses indicate that the oxidation state, specific surface area, and electrochemical surface area do not cause enough difference in the observed enhancement of OER performance. We examined the effects of microstrain on electrocatalysis, originating from lattice mismatch between different phases, using three different structural models. Specifically, we compared the Williamson–Hall method, standard stress–strain analysis, and Rietveld refinement in analyzing the structure–property relationship. Strain mapping using geometric phase analysis (GPA) further revealed significant microstrain and lattice dislocations localized near phase boundaries in the biphasic oxide, in contrast to the uniform strain in single-phase materials. The results reveal that the increased microstrain correlates well with the improved OER performance, as the biphasic oxide catalyst exhibits 2–3 times greater microstrain than Y 2 Ru 2 O 7 pyrochlore.
An ink formulation and electrode that enhances hydrogen production, oxygen production, carbon dioxide reduction and other electrocatalytic reactions. Embodiments include an ink formulation with polymer binders having different catalytical precursors and a 3D electrode produced by additive manufacturing from the inventor's ink formulation. Various embodiments of the inventor's apparatus, systems, and methods provide inks that that are 3D-printed into patterns that optimize surface area and flow. The catalytic materials are imbedded into the ink matrix which is then printed into a 3D structure that has architecture that optimizes surface area and flow properties.
Photobiocatalysis integrates enzymatic catalysis with photochemistry, enabling challenging radical transformations with high selectivity under mild conditions. Early developments in this field were largely driven by the discovery that enzyme-bound cofactors can form photoactive charge–transfer complexes with substrates, thereby initiating radical chemistry upon light irradiation. Recent advances, however, have substantially expanded the mechanistic landscape of photobiocatalysis through diverse mechanisms. This review summarizes major developments in photobiocatalysis reported since 2024. Rather than cataloging individual reactions, we focus on the fundamental mechanisms of radical generation and interception within enzyme active sites, and discuss how these mechanistic principles guide the discovery, engineering, and design of enzymes for new-to-nature photobiocatalysis.
This project primarily sought to address some of the computational cost concerns of detailed simulations by developing improved methods of handling species transport, and chemical kinetics evaluation in a commercial 3D Computational Fluid Dynamics (CFD) environment. Secondary goals were to apply these techniques to fuels and conditions of interest to better understand the key species and reactions required to adequately capture cycle to cycle coupling. Improved modeling will lead to better understanding of these combustion modes and their dependence on fuel composition, which can then enable more clean and efficient engines, ultimately benefiting the consumer as well as the general public. Two approaches were used to address the computational cost. A “Dynamic Species Reduction” (DSR) procedure was developed to remove chemical species from the simulation during periods when chemical reactions were not expected to be important, particularly during gas exchange when temperatures are low and little fuel remains. This modelling procedure automatically detects relevant species to retain in the simulation domain based on their local concentration, removes species below a specified concentration threshold, and then adjusts the remaining species mass to conserve not only the number of H, C, and O atoms in each cell, but also the relative proportions between species and the heating value of the mixture in every cell. The second procedure was a “Product Directed Remapping” (PDR) updates the algorithm used to group individual computational cells for chemical kinetics evaluation to account for non-uniform temperature distributions and the CO to CO 2 ratio in the cells. The model techniques developed in this work successfully demonstrated computational performance improvements for a range of conditions relevant for Highly Dilute SI and HCCI engine operation. Runtime reductions of 10% were observed for small mechanisms, with further reductions of up to 36% observed for larger mechanisms. Improvements were primarily related to reducing the number of chemical species tracked during the gas exchange process using the Dynamic Species Reduction method. With smaller benefits observed from changes to the kinetics binning and evaluation strategy in the post combustion region using the PDR method. The results of this work show the potential for improved computational runtime for complicated simulations. They can and should be extended to additional conditions and new bio-derived and renewable fuels as they are developed and new kinetic mechanisms become available.
Training the future synthetic biology workforce requires the opportunity for students to be exposed to biotechnology concepts and activities in secondary education. Detecting Wolbachia bacteria in arthropods using polymerase chain reaction (PCR) has become a common way for secondary students to investigate and apply recombinant DNA technology in the science classroom. Despite this important activity, cutting-edge biotechnologies such as clustered regularly interspaced short palindromic repeat (CRISPR)-based diagnostics have yet to be widely implemented in the classroom. To address this gap, we present a freeze-dried CRISPR-Cas12 sensing reaction to complement traditional recombinant DNA technology education and teach synthetic biology concepts. The reactions accurately detect Wolbachia from arthropod-derived PCR samples in under 2 h and can be stored at room temperature for over a month without appreciable degradation. Here, the reactions are easy-to-use and cost less than $40 to implement for a classroom of 22 students including the cost of reusable equipment. We see these freeze-dried CRISPR-Cas12 reactions as an accessible way to incorporate synthetic biology education into the existing biology curriculum, which will expand biology educational opportunities in science, technology, engineering, and mathematics.
Abstract Engineering efficient biocatalysts is essential for metabolic engineering to produce valuable bioproducts from renewable resources. However, due to the complexity of cellular metabolic networks, it is challenging to translate success in vitro into high performance in cells. To meet such a challenge, an accurate and efficient quantification method is necessary to screen a large set of mutants from complex cell culture and a careful correlation between the catalysis parameters in vitro and performance in cells is required. In this study, we employed a mass‐spectrometry based high‐throughput quantitative method to screen new mutants of 2‐pyrone synthase (2PS) for triacetic acid lactone (TAL) biosynthesis through directed evolution in E. coli . From the process, we discovered two mutants with the highest improvement (46 fold) in titer and the fastest k cat (44 fold) over the wild type 2PS, respectively, among those reported in the literature. A careful examination of the correlation between intracellular substrate concentration, Michaelis‐Menten parameters and TAL titer for these two mutants reveals that a fast reaction rate under limiting intracellular substrate concentrations is important for in‐cell biocatalysis. Such properties can be tuned by protein engineering and synthetic biology to adopt these engineered proteins for the maximum activities in different intracellular environments.
Methane production and emission from riverbed sediments constitute a significant yet underexplored component of the river methane budget. Despite their importance, a mechanistic and quantitative understanding of these processes under dynamic flow conditions remains elusive, particularly at the basin scale. In this study, we investigate the multiscale (site-to-basin) mechanisms governing methane emissions from riverbeds, focusing on the interplay between biogeochemical processes and hydrological dynamics. We developed a reactive transport model that integrates methane production with hydrodynamic and ebullitive pathways and coupled it with a basin-scale groundwater flow model to simulate methane emissions across scales. By incorporating key factors such as vertical hydrological exchange flow (VHEF), particulate organic carbon availability, sediment properties, and temperature sensitivity, our model captures the spatiotemporal variability of methane ebullition at both the site and basin scales. Our results reveal that methane ebullition is strongly modulated by VHEF, with lower flow rates promoting methane accumulation and subsequent ebullition. Sensitivity analyses underscore nonlinear responses of methane fluxes to environmental drivers. Furthermore, these findings emphasize the critical roles of sediment composition, hydrological exchange, and environmental conditions in shaping methane dynamics. Overall, this work advances our understanding of riverine methane emissions and offers insights for guiding climate models and mitigation strategies.
Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.
Engineering the atomic arrangement of bimetallic catalysts can improve the efficiency and selectivity of electrochemical CO 2 reduction reaction (CO 2 RR) to form highly valued chemicals.
Heterointerface engineering is a desirable way to rationally design efficient and low-cost electrocatalysts for the oxygen evolution reaction (OER). Herein, urchin-like Co 9 S 8 @NiFe layered double hydroxide (Co 9 S 8 @NiFe LDH) heterostructured hollow spheres are assembled from Co 9 S 8 hollow spheres as the core and porous NiFe LDH nanowires as the shell. The heterostructured hollow spheres show a small overpotential of 220 mV at a current density of 10 mA cm -2 , a low Tafel slope of 52.0 mV dec -1 , and robust stability, which is better than that of commercial IrO 2 and most reported non-precious electrocatalysts. Density functional theory (DFT) calculations show that the synergetic effect at the interface could improve the electrical conductivity of Co 9 S 8 @NiFe LDH, induce electron transfer from NiFe LDH to Co 9 S 8 , and lower the energy barriers of intermediates for the OER, leading to enhanced electrocatalytic activity. Meanwhile, the urchin-like hollow structure with nanopores and super-hydrophilicity can provide desired structural stability, facilitate ion penetration and release bubbles, improving the accessibility of active sites and thereby boosting OER catalytic performance. This work provides a viable route to develop high performance electrocatalysts for the OER.
Lipids accumulated in the vegetative tissues of cellulosic feedstocks can be a potential raw material for biodiesel and bioethanol production. In this work, bagasse of genetically engineered sorghum was subjected to liquid hot-water pretreatment at 170, 180, and 190 °C for different reaction time. Under the optimal pretreatment condition (170 °C, 20 min), the residue was enriched in glucan (57.39 ± 2.63 % w/w) and xylan (13.38 ± 0.49 % w/w). The total lipid content of the pretreated residue was 6.81% w/w, similar to that observed in untreated bagasse (6.30% w/w). Pretreatment improved the enzymatic digestibility of bagasse, allowing a recovery of 79% w/w and 86% w/w of glucose and xylose, respectively. The pretreatment and enzymatic saccharification resulted in a 2-fold increase in total lipid in enzymatic residue compared to the original bagasse. Thus, pretreatment and enzymatic hydrolysis enabled high sugar recovery while concentrating triglycerides and free fatty acids in the residue.
LLNL produced two lots of lyophilized LAMP assay containing cartridges, LNL022818 and LNL071818, for testing on Gen3 BioID systems. Thirty-nine cartridges were tested for lot LNL022818. All thirty-nine cartridges performed as expected regarding correct positive control (IPC) and negative control (NTC) reactions. Five different templates were tested on these 39 cartridges. The BioID system detected 79.1% true positives and 9.3% false positives along with 98.9% true negatives and 2.9% false negatives for cartridge lot LNL022818. Thirty cartridges were tested for lot LNL071818. It was noted early that due to a manufacturing issue with the cartridges related to incomplete sonic welding of the cartridge, a large fraction of lot LNL071818 cartridges leaked. Insufficient funds were available to replace this lot of cartridges. Twenty three of 30 cartridges performed as expected regarding correct positive control (IPC) and negative control (NTC) reactions. Four different templates were tested on these 30 cartridges. The BioID system detected 77% true positives and 23% false positives along with 96.9% true negatives and 3.1% false negatives for cartridge lot LNL071818. For all tested cartridges using DNA template, DNA was added at a final concentration of 25 pg/ul. All reactions contained positive control DNA at 2.5 pg/ul.
Methanol is an attractive fuel for the maritime sector due to its wide availability. Its direct use as a fuel, however, is accompanied by challenges such as high latent heat of vaporization and low cetane number. A potential solution to overcome the ignition properties of methanol could be through on-board generation of dimethyl ether (DME) via catalytic dehydration of methanol. The resulting mixture from dehydration can be mixed in with the intake air to generate a homogenous charge compression ignition (HCCI) preburn for subsequent direct injection (DI) mixing controlled compression ignition (MCCI) of neat methanol. Within that context, complementary experimental work found that the influence of combustion residuals on the heat release rate (HRR) was significant, specifically for residual NO. This finding motivated the present computational and kinetic evaluation of the effects of NO on the low (LTHR) and high (HTHR) temperature heat release rates. The strong influence of small quantities of NO on the combustion process of a DME/methanol/H2O mixture (low catalyst or reactor efficiency) necessitated a kinetics-based investigation into this phenomenon. A mechanism sourced from the existing literature with NO had 172 species and 1375 reactions, making it computationally expensive for use. Hence, a mechanism reduction effort was implemented, and a rate constant (k) tuning effort based on sensitivity analysis was needed to validate experimental results using a zero-dimensional engine model in Cantera. The reduced mechanism was able to successfully capture the negligible influence of NO addition on DME HCCI combustion, whereas an advancement in LTHR and HTHR for a DME/methanol/H2O mixture was kinetically confirmed. Reaction pathway analysis showed that addition of NO chemically counteracted the OH sink created by alcohols like methanol, increasing the effectiveness of DME ignition.
Several material properties have been studied as a function of composition as part of the USHPRR effort to use U-10Mo for LEU monolithic fuel foils, with special attention to areas where simulation outcomes can be improved. The liquidus and solidus phase boundaries are important for engineering design of processing parameters and for predicting the degree of microsegregation within initial castings. The numerous phase diagram constructions available in the literature differ significantly in their solid/liquid boundary definitions, therefore, an experimental strategy was employed in order to resolve some of the discord. That strategy focuses not on proving any singular point, but instead to provide data with highly characterized uncertainty. The data presented here is the most consistent with the U-rich liquidus and solidus boundaries provided by H. Okamoto (2012), Berche et al. (2011), and Mardon et al. (1959). The recently suggested change in the peritectic reaction temperature (to 1302 K) suggested by Berchè and adopted by Okamoto is also supported, but with lower confidence. The enthalpy of fusion is a basic characteristic of the solidification reaction property for which is required for both research-oriented predictions of behavior and development of applied design strategies for casting engineering. It has been determined that an admixture model for the heat of fusion between U BCC and Mo BCC is a reasonable assumption within the composition region of interest, though limitations of the measurement accuracy impacts the ability to support any trends more detailed than this baseline behavior. A limited number of thermal diffusivity measurements were also performed into the gamma region to provide additional information for solidification modeling and simulations as well as a check on the component properties of thermal conductivity, density, and heat capacity.