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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cobalt(II) Phthalocyanine Substituents Tune the Electrocatalytic CO 2 Conversion to Methanol

Cobalt phthalocyanine (Co(II)Pc) and its derivatives are promising molecular electrocatalysts for the electrochemical reduction of CO 2 to CO and methanol (CH 3 OH). Despite increasing interest, a detailed mechanistic understanding of how ligand substituents influence catalytic activity, selectivity, and efficiency remains limited. In this study, we employ density functional theory (DFT) to systematically investigate the influence of electron-donating groups (EDGs) and electron-withdrawing groups (EWGs) on the electronic structure and redox properties of the Co(II)Pc electrocatalyst, and to elucidate CO 2 RR mechanistic pathways. Our results reveal that EWGs cause a positive shift in the reduction potentials, favor CO 2 binding over protonation of the Co metal center and promote downstream methanol formation at mild potentials. EDGs show opposite trends including favorable protonation steps, promoting a negative shift in the reduction potential, and facilitating the hydrogen evolution reaction (HER), which competes with the desired CO 2 RR pathway. Notably, CO dissociation is thermodynamically and kinetically unfavorable across all systems, positioning the redox potential versus CO dissociation energy as a key factor for methanol selectivity. Furthermore, these insights provide a predictive framework for rational catalyst design and underscore the critical role of electronic tuning in advancing molecular electrocatalysts for sustainable CO 2 conversion.

Alcohols↗
DOE OSTI2025

An Atomistic Study of Reactivity in Solid-State Electrolyte Interphase Formation for Li/Li7P3S11

Lithium metal batteries offer superior volumetric and gravimetric specific capacities compared to those based on traditional graphite anodes. Although advancements in solid-state electrolytes address safety concerns, challenges remain, particularly regarding interphase formation in lithium metal anodes. This work presents a computational framework based on high-throughput first-principles density functional theory and machine-learning interatomic potentials (MLIPs) including automated iterative, active learning to enable robust computational exploration of interphase formation between lithium metal anodes and an inorganic solid-state electrolyte. As a demonstration, we apply the framework to a Li/Li7P3S11 interface and find that it accurately identifies the experimentally observed, thermodynamically stable interphase products as well as their overall spatial arrangement within a heterogeneous, amorphous layered structure, with Li2S domains of nanocrystallinity. Our simulations show two stages, a fast and slow diffusion reaction regime, that corroborate the relative phase formation rate of Li x P, Li2S, and Li3P. Using the Onsager transport theory, we capture time-dependent ionic diffusion within the reacting interface, including cross-correlation effects. We found that cross-correlation effects between Li-P and P-S ionic motion significantly influence P-ion diffusion, making it highly sensitive to the local environment and potentially leading to "kinetic trapping" of Li-P phases. The passivation of the interface is shown as the ionic fluxes all approach zero, effectively halting interphase growth.

Diffusion↗
DOE OSTI2024

Discovery of Multiple Light-Harvesting States of the Photosynthetic Protein PE545

Cryptophytes are photosynthetic microalga that flourish in a remarkable diversity of natural environments by using pigment-containing proteins with absorption maxima tuned to each ecological niche. While this diversity in the absorption has been well established, the subsequent photophysics is highly sensitive to the local protein environment and so may exhibit similar variation. Thermal fluctuations of the protein conformation are expected to introduce photophysical heterogeneity of the pigments that may have evolved important functional properties in a manner similar to that of the absorption. However, such heterogeneity is averaged out in ensemble measurements and, therefore, has not yet been probed. Here, we report single-molecule measurements of phycoerythrin 545 (PE545), the prototypical cryptophyte antenna protein, in its native dimeric form. A conformational ensemble was resolved consisting of distinct photophysical states with different light-harvesting properties. Proteins that did not quench, partially quenched, or fully quenched absorbed light were observed. Light intensity increased the quenched-state population of the dimer, potentially as a mechanism to deal with the extreme light intensities found in aqueous environments. Cross-linking, which mimics local interactions, introduces this light-dependent functionality while also suppressing other conformational dynamics. The cellular organization can, therefore, actively modulate the protein conformation and dynamics, selecting for distinct levels of light harvesting. Furthermore, the complex conformational equilibrium provides an additional mechanism for cryptophytes and likely other photosynthetic organisms to optimize solar energy capture and conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Advancing Protein Display on Bacterial Spores through an Extensive Survey of Coat Components

The profound stability of bacterial spores makes them a promising platform for biotechnological applications like biocatalysis, bioremediation, drug delivery, etc. However, though the Bacillus subtilis spore is composed of >40 types of proteins, only ∼12 have been explored as fusion carriers for protein display. Here, we assessed the suitability of 33 spore proteins (SPs) as enzyme display carriers by direct allele tagging at native genomic loci. Of the 33 SPs investigated, 26 formed functional fusions with β-glucuronidase (GUS)─a ∼272 kDa homotetramer. This almost triples the number of SPs assessed for enzyme display and doubles the number of functional fusions documented in the literature. We quantitatively assessed 1) SP promoter activation dynamics, 2) GUS activity on spores, 3) surface availability, and 4) protection from thermal and proteolytic degradation. Multicopy expression and pairwise coexpression of the most promising SP-GUS fusions highlighted the complexity of spore structure/assembly and the difficulty in predicting compatibility between different SP fusions. We also assessed the suitability of engineered spores to degrade PET (polyethylene terephthalate) films and found that surface-exposed SPs were most effective. Beyond the broad survey, a key outcome of our work was the identification of SscA (small spore coat assembly protein A) as an effective spore display carrier. SscA supported enzyme activity at least 4-fold higher than any other SP, including the well-established anchor, CotY. We attribute this to its promoter, which demonstrated early and sustained activation relative to other SPs and its small size (∼3 kDa), which likely minimally interferes with enzyme folding, oligomerization, and activity. Labeling and genetic studies, its hydrophobic nature, and low surface availability suggest that SscA assembles within the inner spore coat, which makes it stabilizing and suitable for many biocatalytic applications. Overall, this work serves as a knowledge base to advance the biotechnological utility of B. subtilis spores.

Bacillus subtilis↗
DOE OSTI2024

Single-cell RNA sequencing reveals plasmid constrains bacterial population heterogeneity and identifies a non-conjugating subpopulation

Transcriptional heterogeneity in isogenic bacterial populations can play various roles in bacterial evolution, but its detection remains technically challenging. Here, we use microbial split-pool ligation transcriptomics to study the relationship between bacterial subpopulation formation and plasmid-host interactions at the single-cell level. We find that single-cell transcript abundances are influenced by bacterial growth state and plasmid carriage. Moreover, plasmid carriage constrains the formation of bacterial subpopulations. Plasmid genes, including those with core functions such as replication and maintenance, exhibit transcriptional heterogeneity associated with cell activity. Notably, we identify a cell subpopulation that does not transcribe conjugal plasmid transfer genes, which may help reduce plasmid burden on a subset of cells. Our study advances the understanding of plasmid-mediated subpopulation dynamics and provides insights into the plasmid-bacteria interplay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

First-principles elucidation of defect-mediated Li transport in hexagonal boron nitride

Hexagonal boron nitride (hBN) is a promising candidate as a protective membrane or separator in Li-ion and Li–S batteries, given its excellent chemical stability, mechanical robustness, and high thermal conductivity. In addition, hBN can be functionalized by introducing defects and dopants, or be directly integrated into other active components of batteries, which further augments its appeal to the field. Here, we use first-principles simulations to evaluate the role of atomic defects in hBN in regulating the Li-ion diffusion mechanism and associated kinetics. Specifically, the following four distinct types of vacancy defects are considered: isolated single B and N vacancies, a B–N vacancy pair, and a B 3 N vacancy cluster. It is found that these defect sites generally favor Li intercalation and out-of-plane diffusion but slow down in-plane Li-ion diffusion due to a strong Li trapping effect at the defect sites. Such a trapping effect is, however, highly local such that it does not necessarily affect the overall Li-ion conductivity in defected hBN layers. The present systematic evaluation of the impact of atomic defects on Li ion migration and accompanied charge analysis of hBN lattice in response to Li-ion diffusion provide a mechanistic understanding of Li-ion transport behavior in defected hBN and highlight the potential of defect engineering to achieve optimal material performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗
DOE OSTI2024

Self-compensation of group-V acceptors in CdTe

Cadmium Telluride is at the core of an important thin-film technology for photovoltaics that is already commercially available, yet the CdTe-based solar cell efficiency remains limited at 22%, well below the theoretical limit of ~30%. Increasing the hole concentration is crucial for higher efficiency, and group-V elements such as As, P, and Sb are potential dopants as they are shallow acceptors. Nevertheless, group-V doped p-type CdTe often exhibits low doping activation, and the compensation source remains debated. Here, we performed hybrid density functional calculations with spin-orbit coupling to investigate possible sources of hole compensation in group-V doped CdTe. First, regarding possible self-compensation of the group-V dopants, we find that the formation of AX centers is unlikely since they are found to be unstable relative to the shallow acceptor forms. However, if the group-V dopants come in during growth (such as dimer molecules As2, P2, and Sb2), we find that the impurity atoms, which would occupy nearest neighbor sites, maintain the V-V bonds, limiting the hole density. For the native defects, our study reveals that Cd interstitial is the lowest energy donor defect in p-type CdTe. Still, it has a small migration barrier of 0.5 eV, making it highly mobile and unstable at room temperature. The Te vacancy is the next lowest formation energy donor. The migration barrier of 1.4 eV indicates that the Te vacancy is stable at room temperature. The antisite CdTe is also a donor, with low formation energy and stable at room temperature, potentially limiting the hole concentration. Our results, therefore, shed light on possible compensation centers and some guidance on how to avoid them.

14 SOLAR ENERGY↗
DOE OSTI2025

Higher-order factorization machine for accurate surrogate modeling in material design

Efficient and robust optimization is important in material science for identifying optimal structural parameters and enhancing material performance. Surrogate-based active learning algorithms have recently gained great attention for their ability to efficiently navigate large, high-dimensional design spaces. Among surrogate models, 2 nd -order factorization machine (FM) models are widely employed as the surrogate model in active learning algorithms due to their balance between simplicity and effectiveness. However, their quadratic nature limits their capacity to capture complex, higher-order interactions among variables, often leading to suboptimal solutions. To overcome this limitation, we propose an active learning scheme integrating a 3 rd -order FM model, capable of modeling three-variable interactions and more intricate relationships in material systems. We comprehensively evaluate the surrogate modeling performance of the 3 rd -order FM case using various objective functions. Furthermore, we examine the optimization reliability and efficiency of the 3 rd -order FM-based active learning in a real-world material design task (e.g., nanophotonic structures for transparent radiative cooling). Our study shows that the 3 rd -order FM outperforms the 2 nd -order model in both surrogate accuracy and optimization performance, highlighting higher-order models’ promises for material design and optimization problems.

Factorization machine↗
DOE OSTI2024

Physical and Chemical Responses of Amidine-Containing Polymers in the Capture and Release of CO 2

Polymeric materials containing amidine motifs are of high interest due to their ability to reversibly capture and release CO 2 at ambient temperature. Here, in this study, we probe physical and chemical responses of styrene-based copolymers containing linear amidine motifs as functions of CO 2 and inert gas exposures and temperature. A copper-catalyzed azide–alkyne cycloaddition “click” reaction involving N′-propargyl-N,N-dimethylacetamidine is used to modify random copolymers, resulting in an array of linear amidine motifs along the chain backbone with the amount of CO 2 -active amidine controlled by the copolymer composition. Through thermogravimetric measurements, we demonstrate that the amidine-functionalized copolymers efficiently capture CO 2 upon exposure to a stream of CO 2 (at 27 °C) and release it at a slightly elevated temperature (50 °C) when exposed to an inert gas stream (N 2 ). In addition to displaying a maximum adsorption capacity of 22 wt % in the presence of pure CO 2 , the copolymers show composition-dependent direct air capture (DAC) behaviors. Small molecule analogs are used to definitively understand degradation via chemical hydrolysis of the amidine moiety, which leads to insolubility and a large reduction in CO 2 adsorption capacity (1.7 wt %). Neutron vibrational spectroscopy and DFT calculations confirm that CO 2 binds strongly to the amidine motif, inducing a strong bending of the CO 2 molecule from its linear geometry. The coupled insights into mechanisms and behaviors of CO 2 adsorption in amidine-functionalized polymers provides a foundation for future investigations of CO 2 -responsive polymers and soft materials to improve carbon capture and sequestration technologies.

Chun, Danielle J.↗
DOE OSTI2025

Design and synthesis of biobased superhydrophobic biochar catalyst derived from Citrus sinensis for biodiesel production using inedible oil feedstocks

In an one-pot in situ trans/esterification of low-grade feedstocks, the simultaneous presence of triglycerides (TAGs) and free fatty acids (FFAs) presents a dual catalytic challenge. While TAGs undergo transesterification to form biodiesel and glycerol, FFAs present in the feedstocks are esterified simultaneously, producing water as a by-product. This water can deactivate acid catalysts by interacting with their active sites, reducing catalytic efficiency and reusability. To overcome this, we developed a hydrophobic sulfonic acid-functionalized biochar catalyst derived from Citrus sinensis (orange peel) via sulfonation with H 2 SO 4 and subsequent silylation using hexamethyldisilazane (HMDS). The optimized catalyst exhibited a high surface area (355.09 m 2 g −1 ), sulfur content (5.33 wt%), and strong hydrophobicity (water contact angle: 154°). Compared to non-hydrophobic analogs, it showed enhanced activity and reusability (up to 10 cycles). Using response surface methodology with central composite design, a biodiesel yield of 99.1 ± 0.4% was achieved under optimal conditions. Life cycle assessment was performed to evaluate the environmental impacts of biodiesel production utilising the synthesized catalyst, considering 1000 kg of biodiesel produced as 1 functional unit. In conclusion, the recorded results showed the cumulative abiotic depletion of fossil resources over the entire biodiesel production process as 87 243.423 MJ and global warming potential as 4103.494 kg CO 2 equivalent.

Biochar↗
DOE OSTI2025

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗
DOE OSTI2025

Rational Selection of Transition-Metal Oxide Electrocatalysts from Structure Electronic Structure-Activity Relations: The Role of Defects, Strain, and Sub-Surface Layering

This BES research investigates the physicochemical properties of metal oxides and how they affect electrocatalytic functionalities. The goal is to develop a predictive framework for realizing top-performing electrocatalytic materials for energy-critical reactions. The hypothesis is that well-defined thin films allow detailed mapping of structural-activity relationships because flat surfaces are more straightforward to characterize. Furthermore, the well-defined nature of thin-film metal oxides allows precise tuning of structural and chemical variables for structure-activity-relationship mapping. The proposed research has two technical objectives. The first is to experimentally assess whether the binding energies of surface oxygen can serve as an activity descriptor for oxygen electrocatalysis on metal oxides and then how to control them by tuning the structure and chemical variables. The second is to find the rate-limiting process in oxygen electrocatalysis and other small-molecule reactions. Similar mechanistic insights have been developed on well-defined platinum surfaces but not yet on oxides. This research addresses this gap and uses electrochemistry and X-ray photoemission spectroscopy to study oxide surface chemistry. The obtained insights are collectively analyzed to reveal how the oxides’ structural and chemical variables affect kinetics and can be used to design more active electrocatalysts for energy-critical reactions.

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

Atomistic Investigation of Plastic Deformation and Dislocation Motion in Uranium Mononitride

Uranium mononitride (UN) is a promising advanced nuclear fuel due to its high thermal conductivity and high fissile density. However, many aspects of its mechanical behavior, particularly at reactor-relevant conditions, remain unclear. In this study, molecular dynamics (MD) simulations were employed to investigate the deformation behavior and dislocation motion in UN. We found that the Kocevski potential predicts the principal slip system as $\frac{1}{2}$ $\langle110\rangle${110}, aligning with experimental data. On the other hand, the Tseplyaev potential predicts slip to primarily occur on $\frac{1}{2}$ $\langle110\rangle${111}. MD simulations of stress–strain behavior were used to estimate the nanoindentation hardness, revealing that the Kocevski potential accurately predicts hardness even though it fails to model dynamic plasticity. Complete dislocation mobility functions have been fitted for the edge and screw dislocations in both the thermally activated and phonon-drag regimes. The 300 K linear mobility of the edge dislocation using the Tseplyaev potential was found to be 817 Pa -1 ·s -1 , whereas that of the screw dislocation using the Kocevski potential was found to be 4546 Pa -1 ·s -1 . At intermediate stresses, we observed that the subsonic steady-state motion of the edge dislocation in UN is intermittently interrupted by velocity jumps, reaching the average sound velocity. Finally, the threshold Schmid stress is calculated as 179–197 MPa, which gives an upper-limit estimate of the uniaxial yield stress of polycrystalline UN of 548–603 MPa. These findings, including the fitted dislocation mobility function, provide essential input for future plasticity and dislocation dynamics models of nuclear fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Biochemical characterization of Fsa16295Glu from “Fervidibacter sacchari,” the first hyperthermophilic GH50 with β-1,3-endoglucanase activity and founding member of the subfamily GH50_3

The aerobic hyperthermophile “Fervidibacter sacchari” catabolizes diverse polysaccharides and is the only cultivated member of the class “Fervidibacteria” within the phylum Armatimonadota. It encodes 117 putative glycoside hydrolases (GHs), including two from GH family 50 (GH50). In this study, we expressed, purified, and functionally characterized one of these GH50 enzymes, Fsa16295Glu. We show that Fsa16295Glu is a β-1,3-endoglucanase with optimal activity on carboxymethyl curdlan (CM-curdlan) and only weak agarase activity, despite most GH50 enzymes being described as β-agarases. The purified enzyme has a wide temperature range of 4–95°C (optimal 80°C), making it the first characterized hyperthermophilic representative of GH50. The enzyme is also active at a broad pH range of at least 5.5–11 (optimal 6.5–10). Fsa16295Glu possesses a relatively high k cat /K M of 1.82 × 10 7 s-1 M-1 with CM-curdlan and degrades CM-curdlan nearly completely to sugar monomers, indicating preferential hydrolysis of glucans containing β-1,3 linkages. Finally, a phylogenetic analysis of Fsa16295Glu and all other GH50 enzymes revealed that Fsa16295Glu is distant from other characterized enzymes but phylogenetically related to enzymes from thermophilic archaea that were likely acquired horizontally from “Fervidibacteria.” Given its functional and phylogenetic novelty, we propose that Fsa16295Glu represents a new enzyme subfamily, GH50_3.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Using real-time nuclear activation detectors for measuring neutron yields from D(D, T)n reactions on the national ignition facility (NIF)

The National Ignition Facility (NIF) has 48 Real-Time Nuclear Activation Detectors distributed around the target chamber capable of measuring deuterium-triton reaction neutron yields with high precision. Here, in this work, we extend this functionality to deuterium–deuterium (DD) reaction neutrons using a nuclear reaction that occurs in the detector’s scintillator material. The corresponding decay of the activated material has a very short half-life of 5 s, which necessitates rapid data collection immediately following an experiment. In this regime, dead time can be very high (>50%) adding significant uncertainty to the measurement. To combat this, we have developed a dead time model that can self-consistently describe the measured data. Initial results show reasonable agreement (within 20%) with DD neutron yields from neutron time-of-flight spectrometers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Synergistic Ru Co atomic pair with enhanced activity toward levulinic acid hydrogenation

Development of efficient metal-based catalysts is of great importance for levulinic acid (LA) hydrogenation to γ-valerolactone (GVL). The widely employed Ru-based catalysts are advantageous for H 2 dissociation, however, the steric hindrance for large Ru particles hampers their coordination to C=O moiety in LA, and thereby decreasing the activity. Herein, we report a Ru 1 Co 1 -N-C double single-atom catalyst (DSAC) with synergistic Ru and Co atomic pairs for LA hydrogenation into GVL. The Ru and Co doped zeolitic imidazole frameworks (RuCo-doped ZIF-8) precursor was rationally designed ((Ru+Co)/(Zn+Ru+Co) = 2 at.%), where the Zn node spatially isolates Ru and Co species, expanding the adjacent Ru-Co distance and facilitating the formation of the Ru-Co atomic pair upon pyrolysis, with each atom coordinated with three nitrogen atoms (N 3 -Ru 1 Co 1 -N 3 ). The Ru 1 Co 1 -N-C catalyst exhibits outstanding catalytic activity, with a turnover frequency (TOF) of 1980 h –1 , surpassing previously reported Ru-based catalysts. Experimental investigation and density functional theory (DFT) calculations reveal that the electron-rich Ru induced by less electronegative Co facilitates H 2 dissociation, while atomic Ru in dual-atomic pairs promotes C=O activation, Ru and Co atomic pairs synergistically enhancing LA conversion to GVL. In conclusion, this research will shed light on the precise control of active sites at atomic scale, and also provides a new concept for designing high-performance Ru-based catalysts towards LA hydrogenation to GVL.

Double single-atom catalysts↗