Achieving Product Control in Furfural Hydrogenation Using Intermetallic Catalysts
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Redox-induced interconversions of metal oxidation states typically result in multiple phase boundaries that separate chemically and structurally distinct oxides and suboxides. Directly probing such multi-interfacial reactions is challenging because of the difficulty in simultaneously resolving the multiple reaction fronts at the atomic scale. Using the example of CuO reduction in H 2 gas, a reaction pathway of CuO → monoclinic m-Cu 4 O 3 → Cu 2 O is demonstrated and identifies interfacial reaction fronts at the atomic scale, where the Cu 2 O/m-Cu 4 O 3 interface shows a diffuse-type interfacial transformation; while the lateral flow of interfacial ledges appears to control the m-Cu 4 O 3 /CuO transformation. Together with atomistic modeling, it is shown that such a multi-interface transformation results from the surface-reaction-induced formation of oxygen vacancies that diffuse into deeper atomic layers, thereby resulting in the formation of the lower oxides of Cu 2 O and m-Cu 4 O 3 , and activate the interfacial transformations. In conclusion, these results demonstrate the lively dynamics at the reaction fronts of the multiple interfaces and have substantial implications for controlling the microstructure and interphase boundaries by coupling the interplay between the surface reaction dynamics and the resulting mass transport and phase evolution in the subsurface and bulk.
A new self-conductive all-polymer GDL configuration, using a conductive polymer layer and hydrophobic layer, overcomes the most prominent obstacles of existing carbon-based and PTFE-based GDLs, representing a next-generation GDL technology.
The coupling of catalysts and atmospheric-pressure plasma has the potential to improve the efficiency of certain catalytic reactions. Understanding the changes that the catalyst surface undergoes during exposure to plasma is key to improving plasma–catalytic performance. In this work, long term exposure of Pt–Al 2 O 3 powder catalyst to an Ar/N 2 /O 2 non-equilibrium atmospheric-pressure plasma-jet was investigated. Products produced by the interaction were analyzed downstream with Fourier-transform infrared spectroscopy while surface species were analyzed operandi with diffuse reflectance infrared Fourier transform spectroscopy. During exposure, the catalyst temperature was ramped cyclically between 100 °C and 350 °C to understand how substrate temperature affects the plasma–catalyst interaction. Long-lasting changes were revealed to take place on the catalyst surface during plasma exposure. At low temperatures, Pt–O and Pt–NO accumulate on the surface which react at elevated temperatures to form NO 2 . NO 2 initially appears to spill on to the Al 2 O 3 support as nitrites and nitrates instead of desorbing. Stable surface conditions are only achieved after prolonged plasma exposure, when nitrate sites on the Al 2 O 3 support are filled. By changing the catalyst temperature at various rates, the impact of total plasma species flux to the surface was analyzed. It was found that decreasing the heating rate increased the hysteresis in the pattern of NO 2 formation during thermal cycling. The variation with temperature demonstrates that plasma exposure results in a buildup of surface NO x and oxygen species which react or desorb at high temperatures. The observed changes are discussed from the generic viewpoint that a non-equilibrium plasma interacting with a catalyst at low temperature introduces metastable steady-state surface conditions. Upon heating above a threshold temperature, the introduced surface modifications can change either due to thermal effects, or, for a plasma environment, by additional interaction with the incident plasma species flux. The surface/material changes take place in a highly predictable fashion and after sufficient time above the threshold temperature reach a steady-state condition that is different from the transient behavior that is observed during initial heating. During cooling the plasma-surface interaction exhibits a different behavior than during heating, and this results in hysteresis of diverse observables. The metastability/hysteresis description appears quite generic and analogous to hysteresis behavior seen for different systems. Furthermore, it is expected to be useful for understanding the consequences of plasma–catalyst surface interactions for various systems.
Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce diffusion-based runoff model (DRUM), a probabilistic deep learning (DL) approach that advances extreme flood forecasting across representative basins in the contiguous United States. DRUM outperforms state-of-the-art benchmarks, enhancing nowcasting skill for the top 1‰ of flows in 72.3% of studied basins. Under operational scenarios, DRUM extends reliable lead times by nearly a full day for 20- and 50-year floods. When evaluated with measured precipitation, an ideal condition, recall improves by 0.3–0.4 and the early warning window extends by 2.3 days for 50-year floods. The enhancement potential varies regionally, with precipitation-driven flood zones in the eastern and northwestern US benefiting most, gaining 3–7 days in lead time. These findings highlight the transformative potential of diffusion models as a cutting-edge generative AI technique for advancing hydrology and broader Earth system sciences.
Here, this work investigates structure-function relationships in electronically tunable, redox-active, basic Cu-Ca mixed metal oxide catalysts for oxidative dehydrocyclization of liquid diols to lactones. Compositional screening identified Ni 2+ and Zn 2+ as effective promoters that increase the surface Cu 2+ population by ∼1.7× and Cu-normalized activity for liquid 1,4-butanediol conversion to γ-butyrolactone by ∼3–4×. In situ Raman spectroscopy, in situ X-ray absorption spectroscopy (XAS), in situ diffuse-reflectance Fourier transform infrared spectroscopy (DRIFTS), ex situ X-ray diffraction (XRD), and H 2 -temperature-programmed reduction (H 2 -TPR) show that Ni 2+ or Zn 2+ incorporation promotes the formation of Ca 0.82 Cu 1.00 O 2 nanoparticles under mild calcination conditions. This cuprate phase features stronger and shorter Cu–O bonds (1.90 Å) than inactive bulk CuO (1.95 Å) and square-planar Cu 2+ O 4 sites with enhanced d z2 electrophilicity, strengthening alkoxy adsorption. Pyridine-DRIFTS confirms the purely basic nature of the catalyst surface, while methanol-DRIFTS indicates Cu 2+ surface enrichment with Ni or Zn promotion, where Cu–O(Ca)–Cu sites can exist as amorphous domains or a truncation layer on crystalline nanoparticles.
C–H terminated nanometer scale diamonds ( d = 1 to 15 nm) are synthesized from 1-fluoroadamantane at high pressure (6–8 GPa) and high temperature (500–1500 °C) in a multianvil press. High resolution transmission electron microscopy, X-ray diffraction, Raman, diffuse reflectance Fourier transform infrared, and X-ray absorption spectroscopies demonstrate the excellent crystallinity and atomically flat C–H terminated surfaces of nanodiamonds with (111) and (110) facets. The importance of hydrogen to the synthesis of nanodiamond and its faceting is discussed. Following vacancy generation, annealing and oxidation of the nanodiamonds, optically detected magnetic resonance and electron spin resonance coherence times ( T 2 = 0.9 and 2.1 μs) of nitrogen vacancy (NV) centers are measured. Finally, the obtained T 2 values are equivalent to the shallow NV centers (depth <10 nm) in bulk diamond crystals and larger nanocrystals prepared by mechanical milling.
Silica-supported ZnO efficiently catalyzes the nonoxidative dehydrogenation of ethanol to acetaldehyde, which is relevant for production of 1,3-butadiene from bioethanol. Characterization with in situ spectroscopies under dehydrated conditions (high sensitivity-low energy ion scattering (HS-LEIS), diffuse reflectance (DR) UV–vis, X-ray absorption spectroscopy (XAS), diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS), inelastic neutron scattering (INS), and UV Raman), and ammonia adsorption probed by temperature-programmed desorption followed by DRIFTS and mass spectrometry (DRIFTS-MS NH 3 -TPD), and DFT calculations revealed that the supported ZnO x phase was present as isolated surface ZnO x sites on SiO 2 , with the vast majority coordinated by two siloxane bonds and one silicon atom with two nonbridging oxygens ((≡SiO) 2 Zn 2+ O 2 Si=), anchored at 4-, 5-, and 6-membered siloxane rings. A minor fraction of surface ZnO x sites possessed Lewis acidity, and even fewer sites possessed a Bro̷nsted acidic Zn(OH) + Si moiety. Ethanol temperature-programmed surface reaction-mass spectrometry (TPSR-MS) with various oxidative or ethanol reaction pretreatments indicated that only sites with Lewis and Bro̷nsted acidic character (Zn(OH) + Si) were active for ethanol dehydrogenation, while the majority surface (≡SiO) 2 Zn 2+ O 2 Si= sites were inactive. Greater heterogeneity among all surface ZnO x sites, as assessed by in situ DR UV–vis spectroscopy, was associated with a greater number of ZnO x sites that were active for ethanol dehydrogenation as well as lower enthalpic barriers for acetaldehyde production among the most active surface ZnO x sites. Turnover frequencies and the apparent activation energy for ethanol dehydrogenation were determined from steady-state kinetics. Together, these findings suggested that anchoring inactive surface (≡SiO) 2 Zn 2+ O 2 Si= sites on the silica support caused a greater number of active surface ZnO x sites to adopt a more strained configuration, promoting ethanol dehydrogenation catalysis. Pretreatments and catalysts that promoted desorption of ethanol during TPSR, taken as a marker of surface dehydroxylation, were associated with an increased number of the most active surface (Zn(OH) + Si) sites. Such findings suggested that inactive surface ZnO x sites were activated for ethanol dehydrogenation by dehydroxylation of the support and/or decreased coordination to hemilabile siloxane ligands.
In electron diffraction patterns of nickel-rich beta-NiAl alloys, many anomalies are observed. One of these is the appearance of diffuse intensity maxima between the reflexions of the B2 structure. This is explained by the short-range ordering of the excess nickel atoms on the simple cubic sublattice occupied only by aluminum atoms in the stoichiometric, perfectly ordered NiAl alloy. After annealing Ni 37.5 atomic percent Al and Ni 37.75 atomic percent Al for 1 week at 300 and 400 C, the diffuse intensity maxima transformed into sharp superstructure reflexions. These reflexions are explained by the formation of the four possible variants of an ordered hexagonal superstructure corresponding to the Ni2Al composition. This structure is closely related to the Ni2Al3 structure (same space group) formed by the ordering of vacancies on the nickel sublattice in aluminum-rich beta-NiAl alloys.
The results of a parametric study on the entrance flow region in a gas core nuclear reactor are presented. The physical system is modeled as laminar confined, coaxial flow with heat generation in the inner fluid. The governing equations include the boundary layer approximations and the assumptions of only radial radiative transport of energy represented as an energy diffusion term. The Von Mises transformation and a zeta transformation are used to transform the equations into nonlinear nonhomogeneous convective-diffusion equations. A unique combination of forward and backward difference equations which yields accurate results at moderate computational times, is used in the numerical method. Results show that the rapidly accelerating, heat generating inner stream actually shrinks in radius as it expands axially.
This dataset supports a publication, "Surface Protected Organozirconium Catalyzes C–H Alumination of Saturated Hydrocarbons", and describes the surface-organozirconium catalyzed exchange of ethyl group in AlEt3 for dodecyl or methyl from dodecane or methane. The research describes the benefits of capping remaining surface OH with SiMe3 for improving yields and turnovers. The dataset includes characterization of the precatalyst using solid-state nuclear magnetic resonance spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), as well as gas chromatography and solution NMR of reaction products.
Molecular-level characterization of polymeric matrix resin in cured graphite-reinforced composite materials now determined through analysis of diffuse reflectance (DR) with Fourier Transform Infrared (FTIR) spectroscopy. Improved analytical method based on diffuse reflectance. DR/ FTIR technique successfully applied to analysis of several different composites and adhesives impossible to analyze by conventional methods.
Original data of whole-soil warming experiment after 9.5 years at Blodgett Forest Research Station. The Blodgett Forest is a mixed coniferous temperate forest with Mediterranean climate. The annual air temperature is 12.5℃ and the annual precipitation is 1774 mm yr-1- The soil is mesic ultic Alfisol of granitic origin, equivalent to Dystric Cambisol according to The World Reference Base for Soil Resources (WRB) system. The soil is warmed down to 1 m at + 4℃ by vertically installed heating cables. At the time of soil sampling on 1 May 2023, the whole-soil warming experiment had been running for approximately 9.5 years, from January 2014 to May 2023. The dataset includes: - Bulk_EA: C, N content, δ13C, and CN ratio of bulk soil; - Density_fractionation: organic carbon concentration, δ13C, and C/N ratio of free light fraction (fLF), occluded ligh fraction (oLF), and heavy fraction (HF); - PCA_DRIFT_AUC: original data of area under the curve (AUC) values of eight carbon bond types integrated on diffuse reflectance infrared fourier transform spectroscopy for each soil sample and soil fraction, which are consequently used for principal component analysis (PCA); - DRIFTS_stability_index: the calculation of aliphatic C–H (3000–2800 cm-1) to aromatic C=C (1670–1600 cm-1) ratios for each bulk soil sample and soil fraction. All data are provided in CSV format and can be viewed using Microsoft Excel.
Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.
An in situ diffuse reflectance-Fourier transform infrared technique was developed to determine infrared spectra of graphite fiber prepregs as they were being cured. A bismaleimide, an epoxy, and addition polyimide matrix resin prepregs were studied. An experimental polyimide adhesive was also examined. Samples were positioned on a small heater at the focal point of diffuse reflectance optics and programmed at 15 F/min while FTIR spectra were being scanned, averaged, and stored. An analysis of the resulting spectra provided basic insights into changes in matrix resin molecular structure which accompanied reactions such as imidization and crosslinking. An endo-exothermal isomerization involving reactive end-caps was confirmed for the addition polyimide prepregs. The results of this study contribute to a fundamental understanding of the processing of composites and adhesives. Such understanding will promote the development of more efficient cure cycles.
A systematic solution approach for the neutron transport equation, based on a least-squares finite-element discretization, is presented. This approach includes the theory for the existence and uniqueness of the analytical as well as of the discrete solution, bounds for the discretization error, and guidance for the development of an efficient multigrid solver for the resulting discrete problem. To guarantee the accuracy of the discrete solution for diffusive regimes, a scaling transformation is applied to the transport operator prior to the discretization. The key result is the proof of the V-ellipticity and continuity of the scaled least-squares bilinear form with constants that are independent of the total cross section and the absorption cross section. For a variety of least-squares finite-element discretizations this leads to error bounds that remain valid in diffusive regimes. Moreover, for problems in slab geometry a full multigrid solver is presented with V(1, 1)-cycle convergence rates approximately equal to 0.1, independent of the size of the total cross section and the absorption cross section.
This article presents a Co phase segregation strategy for creating stable Co cluster catalytic sites on TiO 2 , enabling selective CO 2 hydrogenation to CO. Through oxidative calcination, pre-synthesized Co-doped brookite TiO 2 nanorods transform into a mixed TiO 2 phase, leading to the phase segregation of Co species. The resulting Co clusters, stabilized by strong Co-TiO 2 interactions during reductive CO 2 hydrogenation, effectively suppress the formation of larger nanoparticles. The undercoordinated sites of these clusters promote a high CO production rate with near-unit selectivity, contrasting with Co nanoparticles, which favor CH 4 formation under identical conditions. In-situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis indicates that the weakened CO adsorption on Co clusters is key to their enhanced CO selectivity, highlighting this method as a promising approach for efficient CO 2 utilization.
Techniques used to explain the nature of the optical effects of clouds on the light produced by lightning include a Monte Carlo simulation, an equivalent medium approach, and methods based on Boltzmann transport theory. A cuboidal cloud has been considered using transform methods and a diffusion approximation. Many simplifying assumptions have been used by authors to make this problem tractable. In this report, the cloud will have a spherical shape and its interior will consist of a uniform distribution of identical spherical water droplets. The source will be modeled as a Hertz dipole, electric or magnetic, inside or outside the cloud. An impulsive source is used. Superposition may be employed to obtain a sinusoid within an envelope which describes a lightning event. The problem is investigated by transforming to the frequency domain, obtaining Green's functions, and then using the Cagniard-DeHoop method to symbolically recover the time domain solution.