Unlocking Syngas Synthesis from the Catalytic Gasification of Lignocellulose Pinewood: Catalytic and Pressure Insights.

Modern technologies transform biomass into commodity chemicals, biofuels, and solid charcoal, making it appear as a renewable resource rather than organic waste. The effectiveness of Mo, Fe, Co, and Ni metal catalysts was investigated during the gasification of lignocellulosic pinewood. The primary goal was to compare the performance of iron and nickel catalysts in the low- and high-pressure production of syngas from pinewood. This is the first study that has reported high-pressure gasification of pinewood without the use of an external gasifying agent, producing syngas containing hydrogen, carbon monoxide, and carbon dioxide along with considerable amounts of methane with or without a catalyst. Also, the same gasification at low pressures was compared. In this study, the iron catalyst produces syngas more efficiently at higher pressure and 800 °C, and contains 43 mol % H2, 22 mol % CO2, 26 mol % CH4, and 8 mol % CO in comparison to the nickel catalyst. High pressure produces a large amount of methane too. The nickel catalyst produces higher syngas at low pressure and 850 °C, and contains 55 mol % H2, 9 mol % CO2, 5 mol % CH4, and 30 mol % CO. Low-pressure gasification produces less amounts of CH4 and CO2. Also, the H2/CO ratio is ∼1.81 using the nickel catalyst at low pressures, which is good for utilizing syngas as a feedstock. These results highlight the importance of catalyst selection, reactor configuration, and operating circumstances in adjusting gasification product composition. The study's findings provide information about optimizing syngas production from pinewood, which is critical for the development of sustainable and efficient energy conversion technologies.

Design and Multiobjective Dynamic Optimization of Superheaters for Load-Following Operation in Pulverized Coal Power Plants.

Pulverized coal power plants are increasingly participating in aggressive load-following markets, therefore necessitating the design and optimization of primary superheaters for flexible operations. These superheaters play a critical role in maintaining the final steam temperature of the steam turbine, but their high operating temperatures and pressures make them prone to failure. This study focuses on the optimal design of future-generation primary superheaters for a fast load-following operation. To achieve this, a detailed first-principles model of a primary superheater is developed along with submodels for stress and fatigue damage. Two single-objective optimization problems are solved: one for minimizing metal mass as a measure of capital cost and another for minimizing pressure drop on the steam side as a measure of operating cost. Since these objective functions conflict, a multiobjective optimization problem is executed using a weighted metric methodology. Results from these optimization studies show that the base case design can violate stress constraints during the aggressive load-following operation. However, by optimizing the design variables, it is possible to not only satisfy tight stress constraints but also achieve the desired number of allowable cycles and adhere to the steam outlet temperature constraint. In addition, the optimized design reduces either the metal mass or the steam-side pressure drop compared to that of the base case design. Importantly, this approach is not limited to primary superheaters alone but can also be applied to similar high-temperature heat exchangers in other applications.

Ambient Carbon-Neutral Ammonia Generation via a Cyclic Microwave Plasma Process.

A novel reactor methodology was developed for chemical looping ammonia synthesis processes using microwave plasma for pre-activation of the stable dinitrogen molecule before reaching the catalyst surface. Microwave plasma-enhanced reactions benefit from higher production of activated species, modularity, quick startup, and lower voltage input than competing plasma-catalysis technologies. Simple, economical, and environmentally benign metallic iron catalysts were used in a cyclical atmospheric pressure synthesis of ammonia. Rates of up to 420.9 µmol min-1 g-1 were observed under mild nitriding conditions. Reaction studies showed that both surface-mediated and bulk-mediated reaction domains were found to exist depending on the time under plasma treatment. The associated density functional theory (DFT) calculations indicated that a higher temperature promoted more nitrogen species in the bulk of iron catalysts but the equilibrium limited the nitrogen converion to ammonia, and vice versa. Generation of vibrationally active N2 and, N2+ ions is associated with lower bulk nitridation temperatures and increased nitrogen contents versus thermal-only systems. Additionally, the kinetics of other transition metal chemical looping ammonia synthesis catalysts (Mn and CoMo) were evaluated by high-resolution time-on-stream kinetic analysis and optical plasma characterization. This study sheds new light on phenomena arising in transient nitrogen storage, kinetics, effect of plasma treatment, apparent activation energies, and rate-limiting reaction steps.

Carbon Capture Simulation Initiative: a case study in multiscale modeling and new challenges.

Advanced multiscale modeling and simulation have the potential to dramatically reduce the time and cost to develop new carbon capture technologies. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry, and universities that is developing, demonstrating, and deploying a suite of such tools, including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamics (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk-analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.