Entropic Control of HD Exchange Rates over Dilute Pd-in-Au Alloy Nanoparticle Catalysts

Hoeven, Jessi E. S. van der; Ngan, Hio Tong; Taylor, A.H.; Eagan, Nathaniel M.; Aizenberg, Joanna; Sautet, Philippe; Madix, Robert J.; Friend, C. M.

doi:10.1021/acscatal.1c01400

Cited by 39 publications

(76 citation statements)

References 43 publications

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“…These substantial differences in the pre-exponential factor are qualitatively similar to the experimental values (Table 3), suggesting entropic control of the H-D exchange rate on the Ti-doped Cu. Similar entropic contributions have been reported by changing the active site ensemble size in dilute alloy catalysts 29 or by introducing confinement effects in zeolites. 60 It is useful to briefly compare the nature of the earth abundant npTiCu catalyst with the previously studied PdAu raspberry-colloid-templated (RCT) supported catalyst.…”

Section: Catalytic Performance Of H 2 -D 2 Exchange Reactionsupporting

confidence: 79%

Facilitating Hydrogen Dissociation over Dilute Nanoporous Ti-Cu Catalysts

Lee

Foucher

et al. 2022

Preprint

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The dissociation of H2 is an essential elementary step in many industrial chemical transformations, typically requiring precious metals. Here, we report a hierarchical nanoporous Cu catalyst doped with small amounts of Ti (npTiCu) that increases the rate of H2-D2 exchange by approximately one order of magnitude compared to the undoped nanoporous Cu (npCu) catalyst. The promotional effect of Ti was measured via steady-state H2-D2 exchange reaction experiments under atmospheric pressure flow conditions in the temperature range of 300─523 K. Pretreatment with flowing H2 is required for stable catalytic performance and two temperatures, 523 K and 673 K, were investigated. The experimentally-determined H2-D2 exchange rate is 5-7 times greater for npTiCu vs. the undoped Cu material under optimized pretreatment and reaction temperatures. The H2 pretreatment leads to full reduction of Cu oxide and partial reduction of surface Ti oxide species present in the as-prepared catalyst as demonstrated using in-situ ambient pressure X-ray photoelectron spectroscopy and X-ray absorption spectroscopy. The apparent activation energy and pre-exponential factors measured for H2-D2 exchange are substantially different for Ti-doped vs. undoped npCu catalysts. DFT calculations suggest that isolated, metallic Ti atoms on the surface of the Cu host can act as the active surface sites for hydrogen recombination. The increase in the rate of exchange above that of pure Cu is caused primarily by a shift in the rate-determining step from dissociative adsorption on Cu to H/D atom recombination on Ti-doped Cu, with the corresponding decrease in activation entropy that it produces.

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Section: Catalytic Performance Of H 2 -D 2 Exchange Reactionsupporting

confidence: 79%

Facilitating Hydrogen Dissociation over Dilute Nanoporous Ti-Cu Catalysts

Lee

Foucher

et al. 2022

Preprint

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“… 19 So far, the catalytic performance of well-defined mono- and bimetallic Au, Pd, Pt, and Ag nanoparticles on silica and alumina RCT materials have been investigated for selective oxidation and hydrogenation reactions ( Figure 7 e). 20 , 24 , 44 , 57 , 61 Furthermore, mono- and bimetallic Pd-based RCTs were used as oxidation catalysts for CO 20 , 24 and volatile organic compounds at lower temperatures compared to their commercial counterparts and at significantly reduced metal loadings. 24 A common problem of commercial catalysts performing at high temperatures and/or high air flows is that the NPs can migrate and sinter or leach, which reduces the activity of the catalyst.…”

Section: Applicationsmentioning

confidence: 99%

Evaporation-Induced Self-Assembly of Metal Oxide Inverse Opals: From Synthesis to Applications

et al. 2022

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Conspectus Inverse opals (IOs) are highly interconnected three-dimensional macroporous structures with applications in a variety of disciplines from optics to catalysis. For instance, when the pore size is on the scale of the wavelength of visible light, IOs exhibit structural color due to diffraction and interference of light rather than due to absorption by pigments, making these structures valuable as nonfading paints and colorants. When IO pores are in an ordered arrangement, the IO is a 3D photonic crystal, a structure with a plethora of interesting optical properties that can be used in a multitude of applications, from sensors to lasers. IOs also have interesting fluidic properties that arise from the re-entrant geometry of the pores, making them excellent candidates for colorimetric sensors based on fluid surface tension. Metal oxide IOs, in particular, can also be photo- and thermally catalytically active due to the catalytic activity of the background matrix material or of functional nanoparticles embedded within the structure. Evaporation-induced self-assembly of sacrificial particles has been developed as a scalable method for forming IOs. The pore size and shape, surface chemistry, matrix material, and the macroscopic shape of the IO, as well as the inclusion of functional components, can be designed through the choice of deposition conditions such as temperature and humidity, types and concentrations of components in the self-assembly mixture, and the postassembly processing. These parameters allow researchers to tune the optical, mechanical, and thermal transport properties of IOs for optimum functionality. In this Account , we focus on experimental and theoretical studies to understand the self-assembly process and properties of metal oxide IOs without (bare) and with (hybrid) plasmonic or catalytic metal nanoparticles incorporated. Several synthetic approaches are first presented, together with a discussion of the various forces involved in the assembly process. The visualization of the deposition front with time-lapse microscopy is then discussed together with analytical theory and numerical simulations to determine the conditions needed for the deposition of a continuous IO film. Subsequently, we present high-resolution scanning electron microscopy (SEM) of assembled colloids over large areas, which provides a detailed view of the evolution of the assembly process, showing that the organization of the colloids is initially dictated by the meniscus of the evaporating suspension on the substrate, but that gradually all grains rotate to occupy the thermodynamically most favorable orientation. High-resolution 3D transmission electron microscopy (TEM) is then presented together with analysis of the wetting of the templating colloids by the matrix precursor to provide a detailed picture of the embedding of metallic nanoparticles at the pore–matrix interface. Finally, the resulting properties and applications in optics, wetting, and cata...

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“…In addition, because SCN introduces the following limitations, the structure is more compact and the training effect is in the same layer of quality than the RVFL. e constraint condition of network (SCN) is shown in the formula below [14].…”

Section: Applications Of the Tsvd-scn Network In An Opticalmentioning

confidence: 99%

Electronic Information Signal Recognition Based on a Stochastic Neural Network Algorithm

Wang

2022

Journal of Control Science and Engineering

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In order to improve the recognition accuracy of SCN for optical fiber data, a method of optical fiber intrusion signal recognition based on SCN (TSVD-SCN) based on truncated singular value decomposition (TSVD) is proposed in this paper. TSVD-SCN performs SVD decomposition on the hidden layer output of the network and sets a threshold to remove the smaller singular values, so as to reduce the number of conditions of the hidden layer output matrix and improve the network recognition rate. This paper uses the method of duty cycle, average amplitude difference function, and FFT to calculate the energy duty cycle for feature extraction and uses TSVD-SCN algorithm to classify and recognize different intrusion vibration feature vectors. The experimental results show that the root mean square errors of TSVD-SCN and SCN networks are significantly less than RVFL. After the hidden layer node L = 20 , the training error decline speed of RVFL tends to be gentle. When LRVFL = L max , the learning effect is the best, and RMSERVFL = 0.3 . With the continuous increase of L, the training error of SCN network and TSVD-SCN network will be reduced to very small, and the training error of TSVD-SCN network is also less than SCN. Conclusion. The accuracy of the algorithm model proposed in this paper is higher than that of the SCN model. It can accurately identify the types of optical fiber intrusion signals, which is of great significance to improve the classification accuracy of the SCN network in practical applications.

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Entropic Control of HD Exchange Rates over Dilute Pd-in-Au Alloy Nanoparticle Catalysts

Cited by 39 publications

References 43 publications

Facilitating Hydrogen Dissociation over Dilute Nanoporous Ti-Cu Catalysts

Facilitating Hydrogen Dissociation over Dilute Nanoporous Ti-Cu Catalysts

Evaporation-Induced Self-Assembly of Metal Oxide Inverse Opals: From Synthesis to Applications

Electronic Information Signal Recognition Based on a Stochastic Neural Network Algorithm

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