Catalysis with Metal Nanoparticles Immobilized within the Pores of Metal–Organic Frameworks

Metal–organic frameworks (MOFs) are highly ordered crystalline porous materials prepared by the self-assembly of metal ions and organic linkers having low-density framework structures of diversified topologies with tunable pore sizes and exceptionally large surface areas. Other than outstanding gas/molecule storage properties, loading of metal nanoparticles (MNPs) into the pores of MOFs could afford heterogeneous catalysts having advantages of controlling the particle growth to a nanosize region, resulting in highly active sites and enhanced catalytic performances, and these entrapped MNPs within MOF pores could be accessed by reactants for chemical transformations. This is a rapidly developing research area, and this Perspective addresses current achievements and future challenges for diverse MOF-immobilized MNPs within their pores, focusing especially on their preparation, characterization, and application as heterogeneous catalysts

Plant-Wide Scheduling for Profitable Emission Reduction in Petroleum Refineries

Emission reduction becomes increasingly important for petroleum refineries nowadays. Cost-effective solution strategies require emission reductions to be addressed from the entire plant point of view, where emission source generations and reutilizations should be well balanced. This, however, presents a big challenge to refineries due to their large-scale complex manufacturing systems with hundreds of units and thousands of process streams. In this paper, a greedy concept of profitable emission reduction (PER) has been proposed, bearing merits of being economically attractive, environmentally benign, and technologically viable for emission reduction and control in petroleum refineries. To identify PER strategies, a methodology framework and a general plant-wide scheduling model have been developed. It couples generic production activities and characterizations of major air emissions from refineries, such as CO₂, volatile organic compounds (VOCs), nitrogen oxides (NO_X), and particulate matter (PM). A case study has demonstrated the efficacy of the PER concept and the developed methodologies

From Metal–Organic Framework to Nitrogen-Decorated Nanoporous Carbons: High CO₂ Uptake and Efficient Catalytic Oxygen Reduction

High-surface-area N-decorated nanoporous carbons have been successfully synthesized using the N-rich metal–organic framework ZIF-8 as a template and precursor along with furfuryl alcohol and NH₄OH as the secondary carbon and nitrogen sources, respectively. These carbons exhibited remarkable CO₂ adsorption capacities and CO₂/N₂ and CO₂/CH₄ selectivities. The N-decoration in these carbons resulted in excellent activity for the oxygen reduction reaction. Samples NC900 and NC1000 having moderate N contents, high surface areas, and large numbers of mesopores favored the four-electron reduction pathway, while sample NC800 having a high N content, a moderate surface area, and a large number of micropores favored the two-electron reduction process

Screening of a panel of normal tissues and tumor-derived cell lines using RT–PCR

<p><b>Copyright information:</b></p><p>Taken from "Evidence that public database records for many cancer-associated genes reflect a splice form found in tumors and lack normal splice forms"</p><p>Nucleic Acids Research 2005;33(16):5026-5033.</p><p>Published online 7 Sep 2005</p><p>PMCID:PMC1201329.</p><p>© The Author 2005. Published by Oxford University Press. All rights reserved</p> RT–PCR was performed on cDNAs from normal, non-cancerous tissues (lettered in black) and from tumor-derived cell lines (lettered in red). 2% agarose gels were run, and bands visualized by ethidium bromide staining. denotes the band corresponding to the novel splice form, and denotes the band corresponding to the known splice form. The genes shown are (upper gel) and (lower gel)

Immobilizing Metal Nanoparticles to Metal–Organic Frameworks with Size and Location Control for Optimizing Catalytic Performance

AuNi alloy nanoparticles were successfully immobilized to MIL-101 with size and location control for the first time by double solvents method (DSM) combined with a liquid-phase concentration-controlled reduction strategy. When an overwhelming reduction approach was employed, the uniform 3D distribution of the ultrafine AuNi nanoparticles (NPs) encapsulated in the pores of MIL-101 was achieved, as demonstrated by TEM and electron tomographic measurements, which brings light to new opportunities in the fabrication of ultrafine non-noble metal-based NPs throughout the interior pores of MOFs. The ultrafine AuNi alloy NPs inside the mesoporous MIL-101 exerted exceedingly high activity for hydrogen generation from the catalytic hydrolysis of ammonia borane

Immobilizing Metal Nanoparticles to Metal–Organic Frameworks with Size and Location Control for Optimizing Catalytic Performance

AuNi alloy nanoparticles were successfully immobilized to MIL-101 with size and location control for the first time by double solvents method (DSM) combined with a liquid-phase concentration-controlled reduction strategy. When an overwhelming reduction approach was employed, the uniform 3D distribution of the ultrafine AuNi nanoparticles (NPs) encapsulated in the pores of MIL-101 was achieved, as demonstrated by TEM and electron tomographic measurements, which brings light to new opportunities in the fabrication of ultrafine non-noble metal-based NPs throughout the interior pores of MOFs. The ultrafine AuNi alloy NPs inside the mesoporous MIL-101 exerted exceedingly high activity for hydrogen generation from the catalytic hydrolysis of ammonia borane

A New Proactive Scheduling Methodology for Front-End Crude Oil and Refinery Operations under Uncertainty of Shipping Delay

Crude oil planning and scheduling is crucial to petroleum refineries because of the potential for significant economic benefits. In reality, however, crude oil scheduling activities are highly vulnerable to disruptions caused by various uncertainties. In this paper, a new proactive scheduling methodology simultaneously covering crude unloading, transferring, and processing (CUTP) has been developed. The CUTP scheduling methodology is to maximize the total profit subject to various inventory, operation, transportation, and production constraints, while maintaining the refinery normal operating conditions under the uncertainty of crude shipping delays. To quantify shipping delay uncertainties, a combined feasibility index has been developed and embedded into the developed continuous-time mixed-integer nonlinear programming scheduling model, which is solved by the global solver of ANTIGONE. In addition, the relationship between the total profit and the minimum flexibility threshold is also given. The efficacy of this study has been demonstrated by industrial-scale case studies

Immobilizing Extremely Catalytically Active Palladium Nanoparticles to Carbon Nanospheres: A Weakly-Capping Growth Approach

Ultrafine palladium nanoparticles (Pd NPs) supported on carbon nanospheres have been successfully synthesized using a facile methanol-mediated weakly-capping growth approach (WCGA) with anhydrous methanol as a mild reductant and a weakly capping agent. The Pd NPs show exceedingly high catalytic activity for 100% selective dehydrogenation of aqueous formic acid (FA) at ambient temperatures. The small size and clean surface of the Pd NPs greatly improve the catalytic properties of the as-prepared catalyst, providing an average rate of CO-free H₂ generation up to 43 L H₂ g_Pd^–1 min^–1 and a turnover frequency of 7256 h^–1 at 60 °C. These values are much higher than those obtained even with the most active catalyst reported thus far for heterogeneously catalyzed dehydrogenation of FA. This remarkably facile and effective methanol-mediated WCGA provides a powerful entry into ultrafine metal NPs with clean surface to achieve enhanced performance. Moreover, the catalytic results open up new avenues in the effective applications of FA for hydrogen storage

Study of Wetting on Chemically Soften Interfaces by Using Combined Solution Thermodynamics and DFT Calculations: Forecasting Effective Softening Elements

Despite recent progress in understanding the wetting principles on soft solids, the roles of chemical bonding in the formation of interfaces have been largely ignored, because most of these studies are conducted at room temperatures. Here we propose a universal wetting principle from solution thermodynamics to account for the softening of both the solid and liquid surfaces (stable or metastable). Density functional theory (DFT) calculations are applied to evaluate the stability and electron transportation across the interfaces. We find that wetting is dominated by the system entropy changes involving not only the stable liquid alloy phase but also the metastable liquid oxide phases. The state-of-art multicomponent solution thermodynamic models and databases are applied to describe the entropy changes and predict the wetting behaviors. Our results show that by chemically softening either the liquid or the solid phase, the wetting angle reduces. And an effective soften agent/additive (either in the form of chemical elements or molecules) will weaken the bonds within the liquid (or solid) phase and promote new bonds at the interfaces, thus increasing the interface entropy. Subsequently, as an example, Ti and Zr are proposed as effective softening elements to improve the wetting of aluminum liquid on B₆Si(s). This approach provides a concept and tool to advance research in catalytic chemistry, nucleation (growth), elastowetting, and cell–substrate interactions

Dynamic Routing Optimization for Chemical Hazardous Material Transportation under Uncertainties

Chemical hazardous material (Hazmat) transportation has become a very important safety issue to human society and the environment. Great attention has been drawn to reduce potential risks and incidents. In this paper, a new methodology is proposed for the dynamic routing optimization of the chemical Hazmat transportation, which includes four major stages: (i) information collection and preparation; (ii) modeling and solving individual and system routing models; (iii) reactive routing optimization under uncertainties; and (iv) trade-off study for potential shipping delays. A novel MILP model has been developed to determine the optimal shipping path with the minimal transportation risk. This model consists of two parts: the individual and system routing models, which are designed to explore the optimal shipping path for each shipping pair and all transportation tasks, respectively. When uncertainties occur, reactive routing optimization will be performed for handling the leftover transportation tasks. In particular, if some preset shipping time limits are violated due to severe uncertainties, optimal solutions subject to different allowable shipping time (AST) will be iteratively identified, so that the relation between AST and the corresponding transportation risk can be figured out. The efficacy of the developed model has been demonstrated by three case studies. Through the developed model, a reduction of 46% and 34% on system transportation risks of studied transportation tasks can be accomplished when dealing with uncertainties. The obtained relation can be used to trade off AST and the transportation risk, so that stakeholders can be advised on their decision-making for shipping path selection