Effect of Oxide Supports on the Activity of Pd Based Catalysts for Furfural Hydrogenation

We investigated the effect of oxide supports on the hydrogenation of furfural over Pd catalysts on various supports (Al2O3, SiO2, TiO2, CeO2, and ZrO2). Pd catalysts (5 wt%) prepared by chemical reduction on various supports. The dispersion and uniformity of Pd were affected by the properties of the support and by the nucleation and growth of Pd. The conversion of furfural was enhanced by greater Pd dispersion. The selectivity for cyclopentanone and tetrahydrofurfuryl alcohol was affected by physicochemical properties of Pd catalyst and reaction parameters. High Pd dispersion and high acidity of the catalyst led to greater C=C hydrogenation, thereby, generating more tetrahydrofurfuryl alcohol. The Pd/TiO2 catalyst showed the highest cyclopentanone yield than other catalysts. The Pd/TiO2 catalyst exhibited the >99% furfural conversion, 55.6% cyclopentanone selectivity, and 55.5% cyclopentanone yield under the optimal conditions; 20 bar of H2, at 170 °C for 4 h with 0.1 g of catalyst

Highly dispersed Pd catalysts supported on various carbons for furfural hydrogenation

Furfural (FAL), one of the important platform molecules derived from lignocellulosic biomass, can be converted into valuable chemicals such as furfuryl alcohol or cyclopentanone via hydrogenation. While carbon materials have been used as versatile catalyst supports for FAL hydrogenation, systematic studies on the structure of the catalytic performances are lacking. In this work, we prepare various types of carbon supports to investigate the impact of carbon structures for Pd-catalyzed FAL hydrogenation. Mesoporous carbons, including CMK-3, CMK-5, CMK-8, and MSU-F-C, as well as carbon nanotube and Vulcan XC are used as carbon supports. For the preparation of highly dispersed Pd-supported carbon (Pd/C) catalysts, chemical reduction by sodium borohydride is applied, in which trisodium citrate plays a critical role in anchoring small Pd clusters on the carbons. In the liquid-phase hydrogenation of FAL, CMK-5 with the largest surface area and hexagonal hollow tubular framework is proven to be the most efficient carbon support for Pd/C catalysts, with the highest conversion of FAL in both 2-propanol (100%) and water (86.4%) solvents. It is also demonstrated that the product selectivity in FAL hydrogenation over various Pd/C catalysts is changed dramatically depending on the type of solvent. The Pd/C catalysts exhibit similar fractions of product distributions containing furfuryl alcohol, cyclopentanol, tetrahydrofurfuryl alcohol, and minor products in 2-propanol. However, the production of cyclopentanone is increased when water is used as a solvent

Liquid-Phase Hydrogenation of Maleic Acid over Pd/Al₂O₃ Catalysts Prepared via Deposition–Precipitation Method

Succinic acid (SA) is a valuable raw material obtained by hydrogenation of maleic acid (MA). The product selectivity of this reaction is highly dependent on the reaction conditions. This study therefore investigated the effect of the reaction temperature, hydrogen pressure, and reaction time on the liquid-phase hydrogenation of MA by a Pd/Al₂O₃ catalyst. Complete conversion of MA and 100% selectivity for SA were achieved at a temperature of 90 °C, H₂ pressure of 5 bar, and reaction time of 90 min. Fumaric acid (FA) was formed as an intermediate material by hydrogenation of MA under nonoptimal conditions. The impact of the percentage of Pd dispersion and phase of the Al₂O₃ support (γ, θ + α, and α) was also examined. The Pd/Al₂O₃ catalyst with 29.8% dispersion of Pd and γ phase of Al₂O₃ exhibited the best catalytic performance. Thus, catalytic activity depends not only on the amount of Pd dispersion but also on the physicochemical properties of Al₂O₃.Applied Science, Faculty ofNon UBCChemical and Biological Engineering, Department ofReviewedFacult

Interfacial effect of Pd supported on mesoporous oxide for catalytic furfural hydrogenation

Highly dispersed Pd is loaded onto different types of mesoporous oxide supports to investigate the synergetic metal-support effect in catalytic furfural (FAL) hydrogenation. Ordered mesoporous Co3O4, MnO2, NiO, CeO2, and Fe2O3 are prepared by the nanocasting and the supported Pd on mesoporous oxide catalysts are obtained by the chemical reduction method. It is revealed that mesoporous oxides play an important role on Pd dispersion as well as the redox behavior of Pd, which determines the final FAL conversion. Among the catalysts used, Pd/ Co3O4 shows the highest conversion in FAL hydrogenation and distinct product selectivity toward 2-methylfuran (MF). While FAL is converted via two distinct pathways to produce either furfuryl alcohol (FA) via aldehyde hydrogenation or MF via hydrogenolysis, MF as a secondary product is derived from FA via the hydrogenolysis of C?O over the Pd/Co3O4 catalyst. It is revealed that FAL is hydrogenated to FA preferentially on the Pd surface; then the secondary hydrogenolysis to MF from FA is further promoted at the interface between Pd and Co3O4. We confirm that the reaction pathway over Pd/Co3O4 is totally different from other catalysts such as Pd/MnO2, which produces FA dominantly. The characteristics of the mesoporous oxides influence the Pd-oxide interfaces, which determine the activity and selectivity in FAL hydrogenation

Supported Pd nanoparticle catalysts with high activities and selectivities in liquid-phase furfural hydrogenation

Highly dispersed and ultrafine Pd nanoparticles (NPs) deposited on carbon, silica, and alumina supports were prepared by chemical reduction (CR) using sodium borohydride, in the presence of trisodium citrate as a stabilizer. For comparison, supported Pd catalysts were also prepared through impregnation followed by thermal reduction (TR) and capillary inclusion of the colloidal Pd NPs (CI). The activities and selectivities of the prepared catalysts were evaluated in the liquid-phase furfural (FAL) hydrogenation reaction under 20 bar H2 at 180 ??C. Under these conditions, FAL was converted via two distinct pathways to produce either furan via decarbonylation or furfuryl alcohol (FA) via aldehyde hydrogenation. Subsequently, furan and FA were converted to tetrahydrofuran and tetrahydrofurfuryl alcohol (THFA), respectively, via ring hydrogenation. 2-Methylfuran was also produced from the hydration of FAL. To verify the efficiency of the preparation methods, the size of the Pd NPs, the degree of metal dispersion, and the type of supports were correlated with the catalytic conversions and selectivities of FAL hydrogenation. It was confirmed that the 5 wt% Pd/C catalysts possessed highly dispersed small Pd NPs with large metallic Pd surface areas, which resulted in high conversions and selectivities towards THFA in the FAL hydrogenation reaction compared to conventional supported catalysts

Artificial intelligence for predicting survival following deceased donor liver transplantation: Retrospective multi-center study

© 2022 IJS Publishing Group LtdBackground: Previous studies have indicated that the model for end-stage liver disease (MELD) score may fail to predict post-transplantation patient survival. Similarly, other scores (donor MELD score, balance of risk score) that have been developed to predict transplant outcomes have not gained widespread use. These scores are typically derived using linear statistical models. This study aimed to compare the performance of traditional statistical models with machine learning approaches for predicting survival following liver transplantation. Materials and methods: Data were obtained from 785 deceased donor liver transplant recipients enrolled in the Korean Organ Transplant Registry (2014–2019). Five machine learning methods (random forest, artificial neural networks, decision tree, naïve Bayes, and support vector machine) and four traditional statistical models (Cox regression, MELD score, donor MELD score and balance of risk score) were compared to predict survival. Results: Among the machine learning methods, the random forest yielded the highest area under the receiver operating characteristic curve (AUC-ROC) values (1-month = 0.80; 3-month = 0.85; and 12-month = 0.81) for predicting survival. The AUC-ROC values of the Cox regression analysis were 0.75, 0.86, and 0.77 for 1-month, 3-month, and 12-month post-transplant survival, respectively. However, the AUC-ROC values of the MELD, donor MELD, and balance of risk scores were all below 0.70. Based on the variable importance of the random forest analysis in this study, the major predictors associated with survival were cold ischemia time, donor ICU stay, recipient weight, recipient BMI, recipient age, recipient INR, and recipient albumin level. As with the Cox regression analysis, donor ICU stay, donor bilirubin level, BAR score, and recipient albumin levels were also important factors associated with post-transplant survival in the RF model. The coefficients of these variables were also statistically significant in the Cox model (p < 0.05). The SHAP ranges for selected predictors for the 12-month survival were (−0.02,0.10) for recipient albumin, (−0.05,0.07) for donor bilirubin and (−0.02,0.25) for recipient height. Surprisingly, although not statistically significant in the Cox model, recipient weight, recipient BMI, recipient age, or recipient INR were important factors in our random forest model for predicting post-transplantation survival. Conclusion: Machine learning algorithms such as the random forest were superior to conventional Cox regression and previously reported survival scores for predicting 1-month, 3-month, and 12-month survival following liver transplantation. Therefore, artificial intelligence may have significant potential in aiding clinical decision-making during liver transplantation, including matching donors and recipients.N

Structure-dependent catalytic properties of mesoporous cobalt oxides in furfural hydrogenation

As the development of noble metal free catalysts became important in the biomass conversion, catalytic hydrogenation of furfural (FAL) is investigated over ordered mesoporous cobalt oxide (m-Co3O4). When m-Co3O4 is reduced at 350 and 500?????C in hydrogen, the original crystal structure of Co3O4 is changed to CoO and Co, respectively. Here we examine the effect of the structure, porosity, and oxidation state of m-Co3O4 to identify catalytically active species for hydrogenation of FAL. Among cobalt oxide catalysts having different crystal structures and symmetry, m-CoO having p6mm symmetry exhibits the highest activity. In product selectivity, the CoO phase induces FAL hydrogenolysis by selective production of 2-methyl furan (MF), while the Co3O4 and Co phases promote preferential hydrogenation of side chain (carbonyl group) of FAL to furfuryl alcohol. Density functional theory calculations also reveal that the adsorption of FAL on CoO(111) is higher than Co(111). Overall, these studies demonstrate that CoO as the most active phase is responsible for the high FAL conversion and the distinct pathway of FAL to MF