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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DNS of Flame Stabilization Dynamics of a Swirl-Stabilized Spray Burner Using Sustainable Aviation Fuels

Concern for emission reduction has motivated the development of new cost-effective alternative sustainable aviation fuels (SAFs). Drop-in SAFs with blends of the certified and the alternative fuels are beneficial because they do not require engine modifications for use in current aviation engines. Combustion characteristics are of particular concern when comparing a new fuel with Jet-A. Lean blow-off and flame stabilization have been identified to be governed by the fuel propensity to autoignition, i.e. derived cetane number. However, fundamental investigation is required to identify the impact of derived cetane number on the combustion mode of flame stabilization in a realistic combustor. The combustion mode has also a direct impact on turbulent combustion modeling closures. DNS simulations are performed in the low-Mach solver of the Pele Suite called PeleLMeX. Lagrangian multi-phase modeling is used to capture the liquid spray injection of Jet-A (reference fuel) and C1 as a representative of a low cetane number SAF. Adaptive Mesh Refinement (AMR) is used to enable a more efficient simulation of a more realistic domain size and embedded boundary treatment is used to model a bluff-body geometry. Local extinction and edge flame propagation were observed for both fuels. The edge flame propagation mode was quantified in terms of a Damkohler number defined as the ratio between progress variable reaction rate and its diffusive flux. Initial analysis suggests that a mixed mode combustion occurs for the edge flame propagation, with flame propagation assisted by ignition and autoignition co-existing for both Jet-A and C1 flames. The analysis of the extinction region shows a larger progress variable for Jet-A which can further increase the local displacement speed and present a faster reignition of the stoichiometric mixture fraction.

adaptive mesh refinement↗
DOE OSTI2024

Reconceptualizing the Ir III Role in Metallaphotoredox Catalysis: From Strong Photooxidant to Potent Energy Donor

Dual Ir III /L n Ni II metallaphotoredox catalyzed C(sp 3 )–C(sp 2 ) cross-coupling reactions are widely assumed to proceed by photoinduced single electron transfer steps due to the highly oxidizing Ir III * excited state (Ir III = [Ir(dF(CF 3 )ppy) 2 (dtbbpy)] + [PF 6 ] – ; dF(CF 3 )ppy = 2-(2,4-difluorophenyl)-5-(trifluoromethyl)pyridine; L n = dtbbpy = 4,4'-di-tert-butyl-2,2'-bipyridine). Using time-resolved absorption and emission spectroscopy, we reveal that energy transfer between Ir III * and various LnNi II precatalysts and intermediates with k q ≥ 10 8 M –1 s –1 also drives catalysis. Specifically, the excited states of L n Ni II dihalide precatalysts/organometallic intermediates accessible by energy transfer appear to drive bond homolysis, halogen radical elimination, and reductive elimination reactions that facilitate formation of cross-coupled products. Energy transfer dynamics consequently circumvent the need for photoinduced electron transfer, thereby extending substrate scopes to coupling partners that cannot be oxidized by Ir III *. Within a cross-electrophile coupling model reaction between 4-bromobenzotrifluoride and bromocyclohexane, energy transfer activates the L n Ni II precatalyst at early reaction times before nucleophilic reductants are present. In the absence of Ir III , direct excitation of L n Ni II (Br) 2 also activates the precatalyst to form a L n Ni II (Br)(Aryl) intermediate. To compare energy transfer and electron transfer kinetics, we determined rate constants for reductive quenching by Br – (k SET = 4.1 × 10 8 M –1 s –1 ) and for the subsequent electron transfer from reduced Ir III•– to L n Ni II (Br) 2 (k SET = 4.1 × 10 7 M –1 s –1 ) using Stern-Volmer analysis and pulse radiolysis, respectively. Energy transfer rate constants are competitive with the electron transfer rate constants and energy transfer is a parallel pathway within metallaphotoredox catalysis. Exploiting the energy transfer mechanism, we demonstrate highly selective cross-electrophile coupling between 4-chlorobenzotrifluoride and bromocyclohexane to form exclusively cross-coupled product. Here, with alkyl-trifluoroborate nucleophiles that do not reductively quench IrIII* emission, transmetalation with L n Ni II (Br/Cl)(Aryl) followed by energy transfer also drives excited state reductive elimination to form C(sp 3 )–C(sp 2 ) cross-coupled product. Similarly, energy transfer rather than Ni II oxidation drives C(sp 2 )–OR reductive elimination, despite the strongly oxidizing ability of Ir III *. In total, these reactions demonstrate energy transfer processes from Ir III * to L n Ni II in metallaphotoredox catalysis that can unlock alternative reactive pathways.

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

Role of Metal Cocatalysts in the Photocatalytic Production of Hydrogen from Water Revisited

The use of photocatalysts to promote the production of molecular hydrogen from water, following the so-called water splitting reaction, continues to be a promising route for the green production of fuels. The molecular basis of this photocatalysis is the photoexcitation of electrons from the valence band of semiconductors to their conduction band, from which they can be transferred to chemical reactants, protons in the case of water, to promote a reduction reaction. The mechanism by which such a process takes place has been studied extensively using titanium oxide, a simple material that fulfills most requirements for water splitting. However, photocatalysis with TiO 2 tends to be highly inefficient; a cocatalyst, commonly a late transition metal (Au, Pt) in nanoparticle form, needs to be added to facilitate the production of H 2 . The metal is widely believed to help with the scavenging of the excited electrons from the conduction band of the semiconductor in order to prevent their recombination with the accompanying hole formed in the valence band, a step that cancels the initial photon absorption and competes with the photolytic chemical reduction. Here we review and analyze the molecular basis for that mechanism and argue for an alternative explanation, that the role of the metal is to help with the recombination of the atomic hydrogen atoms produced by proton reduction on the semiconductor surface instead. First, we summarize what is known about the electronic structure of these photocatalysts and how the electronic levels need to line up for the reduction of protons in water to be feasible. Next, we review the current understanding of the dynamics of the steps associated with the absorption of photons, the de-excitation via electron–hole pair recombination and fluorescence decay, and the electronic transitions that lead to proton reduction, and contrast those with the rates of the chemical steps required to produce molecular hydrogen. The following section addresses the changes introduced by the addition of the metal cocatalyst, comparatively evaluating its role as either an electron scavenger or a promoter of the recombination of hydrogen atoms. A discussion of the viable chemical mechanisms for the latter pathway is included. Finally, we briefly mention other associated aspects of this photocatalysis, including the possible promotion of H 2 production with visible light via resonant excitation of the surface plasmon of Au nanoparticles, the use of single-metal (Au, Pt) atom catalysts and of yolk–shell nanostructures, and the reduction of organic molecules. We end with a brief personal perspective on the possible generality of the concepts introduced in this Critical Review.

08 HYDROGEN↗
DOE OSTI2024

Training self-learning circuits for power-efficient solutions

As the size and ubiquity of artificial intelligence and computational machine learning models grow, the energy required to train and use them is rapidly becoming economically and environmentally unsustainable. Recent laboratory prototypes of self-learning electronic circuits, such as “physical learning machines,” open the door to analog hardware that directly employs physics to learn desired functions from examples at a low energy cost. In this work, we show that this hardware platform allows for an even further reduction in energy consumption by using good initial conditions and a new learning algorithm. Using analytical calculations, simulations, and experiments, we show that a trade-off emerges when learning dynamics attempt to minimize both the error and the power consumption of the solution—greater power reductions can be achieved at the cost of decreasing solution accuracy. Finally, we demonstrate a practical procedure to weigh the relative importance of error and power minimization, improving the power efficiency given a specific tolerance to error.

Stern, Menachem (ORCID:0000000302158082)↗
DOE OSTI2023

Understanding the dynamic evolution of atomically dispersed Cu catalyst for CO 2 electrochemical conversion using integrated XANES analysis and mechanistic studies

Direct electrochemical conversion of CO 2 to ethanol (CH 3 CH 2 OH) offers a promising strategy to lower CO 2 emission while storing energy from renewable electricity. Our recent study reported a carbon-supported atomically dispersed Cu catalyst that achieved the highest reported selectivity for CH 3 CH 2 OH formation (91%) at a relatively low potential (-0.6 V), however, the active site structure that is responsible for such high activity and selectivity has yet to be understood. Here, in this paper, we demonstrate a computational investigation combining X-ray absorption near edge structure (XANES) simulations and a mechanistic study via density functional theory (DFT) to understand the catalyst structures of this Cu catalyst during electrocatalysis and the corresponding reaction mechanisms of the key products. An integrated computational and experimental XANES analysis depicted the dynamic evolution of the catalytic site during electrocatalysis. The as-prepared, atomically dispersed Cu catalyst aggregates and forms metallic clusters/nanoparticles under electrochemical condition, which then break down to smaller oxidized clusters after electrocatalysis. The formed Cu clusters/nanoparticles showed distinct catalytic activity and selectivity as a function of particle size based on the mechanistic investigation using DFT, which is consistent with experimental observations for catalyst samples with different Cu loadings. This comprehensive study which combines experimental and computational XANES investigation, mechanistic study via DFT calculations, and experimental performance of the catalysts, provides unprecedented dynamic and mechanistic insights into the supported atomically dispersed metal catalysts for CO 2 reduction. Such strategy and details gained can further guide discovery of novel catalyst materials for CO 2 electrochemical reduction.

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

Declining groundwater storage expected to amplify mountain streamflow reductions in a warmer world

Abstract Groundwater interactions with mountain streams are often simplified in model projections, potentially leading to inaccurate estimates of streamflow response to climate change. Here, using a high-resolution, integrated hydrological model extending 400 m into the subsurface, we find groundwater an important and stable source of historical streamflow in a mountainous watershed of the Colorado River. In a warmer climate, increased forest water use is predicted to reduce groundwater recharge resulting in groundwater storage loss. Losses are expected to be most severe during dry years and cannot recover to historical levels even during simulated wet periods. Groundwater depletion substantially reduces annual streamflow with intermittent conditions predicted when precipitation is low. Expanding results across the region suggests groundwater declines will be highest in the Colorado Headwater and Gunnison basins. Our research highlights the tight coupling of vegetation and groundwater dynamics and that excluding explicit groundwater response to warming may underestimate future reductions in mountain streamflow.

Carroll, Rosemary W. H. (ORCID:0000000293028074)↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2024

Optimization-Based Model Reduction Scheme for Renewable Energy Power Plants Using Standardized Testing Scenarios

This paper presents an optimization-based model reduction scheme for renewable energy (RE) power plants consisting of inverter-based resources (IBRs) operating in grid-following (GFL) or grid-forming (GFM) modes. More importantly, the datasets feeding the optimization-based model reduction scheme are generated and re-used through the standardized grid-interactive testing scenarios. Particularly, the proposed scheme makes use of the power plant point of common coupling (PCC) measurements of various quantities specified by standardized tests (e.g., voltage and frequency ride through) as per IEEE 2800, to estimate the parameters of the reduced-order model such that its dynamic performance aligns with the original detailed power plant model. The proposed model reduction approach does not require the parameters of individual IBRs and using standardized test data as input to the formulated optimization problem simplifies the reduced-order modelling scheme. Extensive case studies following standardized test scenarios verified the remarkable accuracy of the proposed approach.

Yallamilli, Ram S. [Purdue University]↗
DOE OSTI2023

Modeling simultaneous particle shrinkage, dissolution and breakage using the modified moving grid technique

Simultaneous shrinkage, dissolution and breakage are important particle size reduction phenomena that characterize processes like the reactive degradation of solid chemicals. The dynamics of the particle size distribution (PSD) for such processes are non-trivial to model due to the number expending processes brought about by the eventual dissolution of particles. To this end, Population Balance Model (PBM) resolved through the sectional techniques is the natural approach. Here, we introduce a modified Moving Grid technique (m-MGT) to accurately resolve the particle size reduction phenomena. Our technique mimics the perpetual particle shrinkage through a continuously left-moving size grid and incorporates a strategic grid removal routine to capture the disappearance of particles. Coupled with the Fixed Pivot (FP) discretization for breakage, our m-MGT not only preserves the moment-related properties, but also benchmarked very well against the analytical number densities and exhibited a minimum of first-order convergence in all assessed case studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Heterogeneous Polymer Dynamics Explored Using Static 1H NMR Spectra

NMR spectroscopy continues to provide important molecular level details of dynamics in different polymer materials, ranging from rubbers to highly crosslinked composites. It has been argued that thermoset polymers containing dynamic and chemical heterogeneities can be fully cured at temperatures well below the final glass transition temperature (Tg). In this paper, we described the use of static solid-state 1H NMR spectroscopy to measure the activation of different chain dynamics as a function of temperature. Near Tg, increasing polymer segmental chain fluctuations lead to dynamic averaging of the local homonuclear proton-proton (1H-1H) dipolar couplings, as reflected in the reduction of the NMR line shape second moment (M2) when motions are faster than the magnitude of the dipolar coupling. In general, for polymer systems, distributions in the dynamic correlation times are commonly expected. To help identify the limitations and pitfalls of M2 analyses, the impact of activation energy or, equivalently, correlation time distributions, on the analysis of 1H NMR M2 temperature variations is explored. It is shown by using normalized reference curves that the distributions in dynamic activation energies can be measured from the M2 temperature behavior. An example of the M2 analysis for a series of thermosetting polymers with systematically varied dynamic heterogeneity is presented and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanocluster and single-atom catalysts for thermocatalytic conversion of CO and CO 2

In this Minireview, we discuss recent advances in understanding nanocluster and single-atom catalysts for CO and CO 2 emissions control applications. Through analyzing thermocatalytic CO oxidation and CO 2 reduction, two fundamentally and industrially important reactions, we compare representative nanocluster and single-atom catalytic systems from perspectives of intrinsic chemistry and reaction engineering. Generally, nanoclusters and single atoms display different catalytic performances (i.e., activity, selectivity, and stability) for these reactions depending on the synthesis methods, support materials, and reaction conditions. Key observations of activity and selectivity tradeoffs between nanoclusters and single-atom catalysts are highlighted. Here, the dynamic structural responses of these catalytic species under CO oxidation or CO 2 reduction reaction conditions are also discussed. Synthetic control and detailed experimental and computational characterization of single-atom and nanocluster catalysts for CO and CO 2 conversion have led to exciting progress over the past decade. Still, more efforts are needed to understand and develop catalysts that meet the environmental, energy, and technical requirements to power a sustainable global economy.

03 NATURAL GAS↗
DOE OSTI2023

C–H Functionalization of Polyolefins to Access Reprocessable Polyolefin Thermosets

Upcycling plastic waste into reprocessable materials with performance-advantaged properties would contribute to the development of a circular plastics economy. Here, we modify branched polyolefins and postconsumer polyethylene through a versatile C–H functionalization approach using thiosulfonates as a privileged radical group transfer functionality. Cross-linking the functionalized polyolefins with polytopic amines provided dynamically cross-linked polyolefin networks enabled by associative bond exchange of diketoenamine functionality. A combination of resonant soft X-ray scattering and grazing incidence X-ray scattering revealed hierarchical phase morphology in which diketoenamine-rich microdomains phase-separate within amorphous regions between polyolefin crystallites. The combination of dynamic covalent cross-links and microphase separation results in useful and improved mechanical properties, including a ~4.5-fold increase in toughness, a reduction in creep deformation at temperatures relevant to use, and high-temperature structural stability compared to the parent polyolefin. The dynamic nature of diketoenamine cross-links provides stress relaxation at elevated temperatures, which enabled iterative reprocessing of the dynamic covalent polymer network with little cycle-to-cycle property fade. Finally, the ability to convert polyolefin waste into a reprocessable thermoformable material with attractive thermomechanical properties provides additional optionality for upcycling to enable future circularity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Improving PGM-free ORR Electrocatalyst Activity: Suggestions from DFT Studies

In this opinion, the limitations of platinum group metal–free oxygen reduction reaction electrocatalyst activity based on scaling laws and resulting Balandin-Sabatier volcano plots are presented. Previous theoretical work aimed at overcoming this limitation is discussed. In this work, a theoretical study of a novel approach toward catalyst activity improvement, dynamic strain engineering, is proposed and tested for a possible platinum group metal–free oxygen reduction reaction active site. It is shown that not only can this approach produce thermodynamic limiting potentials well beyond scaling law relationship limits but also be capable of doing so in an energy-efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cu(II) Stability and UV-Induced Electron Transfer in a Metal–Organic Hybrid: An EPR, DFT, and Crystallographic Characterization of Copper-Doped Zinc Creatininium Sulfate

Single-crystal X-ray diffraction and electron paramagnetic resonance (EPR) spectroscopic experiments, complemented by quantum chemical DFT calculations, were carried out on the copper-doped metal–organic hybrid and Tutton salt analogue zinc creatininium sulfate to determine its crystal structure, to characterize the electronic structure of the doped Cu(II) binding site, and to propose a pathway for an excited-state, proton-coupled electron transfer (PCET) process in UV-exposed crystals. The crystal structure is isomorphous to that of cadmium creatininium sulfate, which has the transition ion, not in direct coordination with the creatinine, but forming a hexahydrate complex, which is bridged to a creatininium through an intervening sulfate ion. The EPR g (2.446, 2.112, 2.082) and copper hyperfine (A Cu : -327, -59.6, 10.8 MHz) tensor parameters are consistent with doped copper replacing host zinc in the metal–hexahydrate complex. These parameters are similar to those observed for copper hexahydrate in doped Tutton salt systems at low temperature, where the unpaired electron occupies mainly the copper 3d x 2 –y 2 orbital. At room temperature in the Tutton systems, vibration couplings stemming from a dynamic Jahn–Teller effect cause tensor averaging which results in a reduction in their maximum g-tensor and hyperfine tensor values. However, like for the doped isomorphous Cd creatinine crystal, the Cu(II) EPR exhibits little, or no room temperature averaging compared to its low temperature pattern. Samples exposed to 254 nm UV light generate a carbon-centered free radical species, characterized by an isotropic g-tensor (g = 2.0029) and an alpha-proton hyperfine coupling (-24 -14 +4 G). These parameters identify it as a creatinine radical cation formed by the oxidative release of one of its C2 methylene hydrogens. DFT calculations confirm the unpaired electronic structures of both the Cu(II) site and free radical. The growth in radical concentration with an increase in the UV exposure time coincides with a decrease in the copper EPR signal, indicating a coupled light-induced oxidation reduction process. A comparison of the crystal structure with the EPR parameters and DFT results provides evidence for a UV-induced PCET.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Transactive HVAC Agent - Design and Performance Evaluation

Transactive energy systems are playing an increasingly important role in the efficient and reliable marketbased operation of the power grid. Since a significant portion of the residential building energy consumption is from heating ventilation and air conditioning (HVAC) systems, HVAC is one of the most promising resources to provide load flexibility. However, utilizing HVAC flexibility to provide various grid services while simultaneously maintaining consumer comfort and cost-reductions is challenging. This paper presents a design of a transactive HVAC agent (T-HVAC) to be used as a supervisory control for the HVAC system that can simultaneously ensure comfort and cost-reduction. In particular, the T-HVAC a) estimates HVAC thermal dynamics, b) ensures optimal operations of the HVAC system, and c) participates into markets, and d) implements a market-based control via controlling the thermostat temperature set-point. The T-HVAC performance is demonstrated through multiple scenarios and illustrations.

Demand flexibility, distribution system, HVAC, Tra↗
DOE OSTI2023

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗
DOE OSTI2024

Self-Inhibition Phenomena in Cu 3 Pt Oxidation by CO 2

Here, this study investigates the oxidation behavior of Cu 3 Pt(100) in CO 2 using a combination of ambient-pressure X-ray photoelectron spectroscopy, mass spectroscopy, and density functional theory modeling. Our in situ measurements reveal the simultaneous oxidation and reduction of Cu 2 O due to the opposing effects of atomic oxygen and CO generated from dissociative CO 2 adsorption, leading to a dynamic equilibrium state of simultaneously occurring redox reactions. Complementary atomistic calculations elucidate the inhibitory effects of subsurface Pt enrichment and the counteracting roles of CO 2 and CO in surface oxidation and reduction. These results provide mechanistic insights into the dissociative pathway of CO 2 molecules and dynamic evolution of surface composition and reactivity of Cu-based alloy catalysts in CO 2 -rich environments, with broader implications for tuning gas–surface reactions by manipulating gas reactants or solid surface composition.

36 MATERIALS SCIENCE↗