A novel machine learning based lumping approach for the reduction of large kinetic mechanisms for plasma-assisted combustion applications
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In this paper, we present theoretically that the thermoelectric figure of merit for a semiconductor material with a small band gap can be significantly enhanced near the intrinsic doping regime at high temperatures via the suppression of bipolar thermal conductivity when the minority carriers are selectively blocked by heterostructure barriers. This scheme is particularly effective in nanostructured materials where the lattice thermal conductivity is lowered by increased phonon scatterings at the boundaries, so that the electronic thermal conductivity including the bipolar term is limiting the figure of merit $zT$. We show that $zT$ can be enhanced to above 3 for p-type PbTe, and above 2 for n-type PbTe at 900 K with minority carrier blocking, when the lattice thermal conductivity is as low as 0.3 W/m K.
For carbothermal reduction (CTR) to be an economic and clean process for magnesium metal production, operational challenges must be overcome. Strong and reactive precursor pellets are necessary to effectively and selectively produce Mg{sub (g)} from any feedstock. In this study, the effects of ore (magnesia and dolime), carbon (petroleum coke, charcoal, algal char, and carbon black), and binder (organic and inorganic) on pellet strength and reactivity, product yield and purity, and reduction selectivity were analyzed. Theoretically and experimentally, the CTR of dolime (MgO·CaO) favored MgO reduction over CaO reduction; however, with enough carbon and heat, both oxides could be reduced. CaO carbothermal reduction produced CaC{sub 2} and Ca{sub (g).} The selectivity to CaC{sub 2} remained constant (7 ± 4 pct) for all C/MgO·CaO ratios analyzed, while the selectivity to Ca{sub (g)} increased (5 pct → 40 pct) when C/MgO·CaO was increased from 0.5 to 2.0. As the overall metal yield decreased (77.6 pct → 59.7 pct) with increasing CaO reduction (38.2 pct → 78.1 pct), Ca{sub (g)} reverted faster than Mg{sub (g).} Heavy metal impurities primarily remained in the residue (< 30 pct volatilized) and, when volatilized, condensed at high temperatures (700 °C to 1450 °C), relative to light metal impurities (350 °C to 1000 °C, > 78 pct volatilized). Organic binders added reducing power to the pellets but produced frail pellets (radial crush strength = 9.1 ± 0.7 N) after pyrolysis, relative to pellets with inorganic binders (15.1 ± 3.2 N). Kinetic parameters were determined for extruded pellets to predict the reaction rate as a continuous function of pressure and temperature.
Fe surfaces have a wide range of applications due to the ability of Fe to be present in a number of different oxidation states, which can be further influenced by the presence of dopants that change the energetic and electronic surface properties. Thus, having an understanding of the elementary reduction processes of clean Fe oxide surfaces, and how dopants affect the energetics and electronics of such processes, is crucial to the science-guided design and optimization of said surfaces. In this work, we use density functional theory (DFT) to investigate the partial reduction of a-Fe2O3(0001) in the absence and presence of Pd and Pt dopants. In order to account for the strong on-site Coulombic interactions present in transition metal oxides, we used both the DFT?+?U method and 2006 Heyd-Scuseria-Ernzerhof functional and compare the results obtained from the different methods. We find that oxygen vacancies created in the clean a-Fe2O3(0001) surface prefer to diffuse into a subsurface layer, with the charge left behind from the first surface oxygen vacancy distributing between all of the near surface Fe atoms. The addition of Pd or Pt to the a-Fe2O3(0001) surface significantly decreases the energy required to create the first surface oxygen vacancy, suggesting the dopants intrinsically promote the reduction of a-Fe2O3(0001). Additionally, the presence of the dopants caused the charge left behind by the creation of the first surface oxygen vacancy to be localized on the dopant itself as well as the highest Fe atom. Overall, this work provides insight into the elementary energetic and electronic properties of the fully oxidized and partially reduced a-Fe2O3(0001) surface in the absence and presence of Pd and Pt dopants, which has potential implications for the design and optimization of doped Fe oxide surfaces.
The development of benign methylation reactions utilizing CO 2 as a one-carbon building block would enable a more sustainable chemical industry. Electrochemical CO 2 reduction has been extensively studied, but its application for reductive methylation reactions remains out of the scope of current electrocatalysis. Here, in this work, we report the first electrochemical reductive N-methylation reaction with CO 2 and demonstrate its compatibility with amines, hydroxylamines, and hydrazine. Catalyzed by cobalt phthalocyanine molecules supported on carbon nanotubes, the N-methylation reaction proceeds in aqueous media via the chemical condensation of an electrophilic carbon intermediate, proposed to be adsorbed or near-electrode formaldehyde formed from the four-electron reduction of CO 2 , with nucleophilic nitrogenous reactants and subsequent reduction. By comparing various amines, we discover that the nucleophilicity of the amine reactant is a descriptor for the C-N coupling efficacy. We extend the scope of the reaction to be compatible with cheap and abundant nitro-compounds by developing a cascade reduction process in which CO 2 and nitro-compounds are reduced concurrently to yield N-methyl amines with high mono-methylation selectivity via the overall transfer of 12 electrons and 12 protons.
Building electrification is putting pressure on distribution grid worldwide. Peak reduction is an important concern that can help reduce the growing stress and allow to defer investments in new capacity. Water heaters represent a convenient way of reducing peak because they are less dependent on weather, and their storage volume allows for asynchronous water heating and hot water use. Previous empirical studies investigated the ability of water heaters to reduce peak through the adjustment of the temperature setpoint. However, not all equipment vendors offer this option. This study aims at understanding the feasibility of peak reduction with an alternative configuration available in the market - by adjusting the device mode rather than temperature setpoint. The peak reduction methodology is tested in an occupied 46-townhome neighborhood located in Atlanta, GA. We find that peak shifting is possible with the adjustable mode approach, with the change in the peak load by 30-60%.
There are thousands of isolated, diesel-powered microgrids that deliver energy to remote communities around the world at very high energy costs. The Remote Communities Renewable Energy program aims to help these communities reduce their fuel consumption and lower their energy costs through the use of high penetration renewable energy. As part of this program, the REopt modeling platform for energy system integration and optimization was used to analyze cost-optimal pathways toward achieving a combined 75% reduction in diesel fuel and fuel oil consumption in a select Alaskan village. In addition to the existing diesel generator and fuel oil heating technologies, the model was able to select from among wind, battery storage, and dispatchable electric heaters to meet the electrical and thermal loads. The model results indicate that while 75% fuel reduction appears to be technically feasible it may not be economically viable at this time. When the fuel reduction target was relaxed, the results indicate that by installing high-penetration renewable energy, the community could lower their energy costs by 21% while still reducing their fuel consumption by 54%.
Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or offline analysis would not be adequate to capture power system dynamic behaviors, especially the new mix of intermittent generation and intelligent consumption makes the power system more dynamic and non-linear. Real time dynamic model reduction emerges as an important need. This paper explores the use of clustering techniques to analyze real-time phasor measurements to determine generator groups and representative generators for dynamic model reduction. Two clustering techniques – graph clustering and evolutionary clustering – are studied in this paper. Various implementations of these techniques are compared and also compared with a previously developed Singular Value Decomposition (SVD)-based dynamic model reduction approach. Various methods exhibit different levels of accuracy when comparing the reduced model simulation against the original model. But some of them are consistently accurate. From this comparative perspective, this paper provides a good reference point for practical implementations.
The non-isothermal reduction kinetics and mechanism of iron during vacuum carbothermal reduction of ilmenite concentrate were investigated by X-ray diffraction, backscattered electron imaging, and energy-dispersive X-ray spectroscopy at temperatures from 1273 K to 1673 K (1000 °C to 1400 °C). The pressure dropped and the increasing trend of mass loss and metallization ratios slowed down when the temperature was higher than 1573 K (1300 °C). The reaction products were iron, Ti{sub 2}O{sub 3}, and silicate. Iron was mainly obtained by carbothermal reduction of FeTiO{sub 3} and FeTi{sub 2}O{sub 5}. The irons continued to nucleate, aggregate, and grow during the reduction process. Comprehensive consideration of Šatava–Šesták method and Coats–Redfern method, the apparent activation energy of the reduction process was 587.4 ± 2.98 kJ/mol, and the forms of both integral and differential for the mechanism function were G(a)= [(1−a){sup −1/3}−1]{sup 2} and f(a) = 3/2(1−a){sup 4/3}[(1−a)−{sup 1/3}−1]{sup −1}, respectively.
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Ad-Ni5Ga3/SiO2 catalyst, which is highly active and stable for thermal CO2 hydrogenation to methanol, was investigated to understand its surface dynamics during reaction conditions. The catalyst was prepared, tested and characterized using a multitude of techniques, including ex-situ XRD, TEM, H2-TPR, CO chemisorption and in-situ ETEM and APXPS. The formation of Ga2O3 upon air exposure was observed and the consequences on catalytic activity were investigated. Results revealed that upon air exposure Ga migrates from the subsurface region to the surface of the nanoparticles forming a Ga-oxide shell surrounding a metallic core. The oxide shell can be reduced completely at high temperatures and the temperature of the reduction activation treatment plays a crucial role on the catalytic activity. This air exposure-reduction procedure results in a redistribution of the Ga species in the surface/subsurface region, promoted by a higher Ga affinity for oxygen. XRD analysis of the post-reaction samples provide evidence for the partial transformation of a Ni5Ga3 intermetallic phase into a Ni-rich Ni3Ga phase. APXPS data indicate that the Ni-rich phase forms in the subsurface region. A Ga-rich phase exists on the surface, where the Ni/Ga ratio reaches 2/3 upon activation in hydrogen. At low reduction temperatures an amorphous Ga2O3 shell remains, indicating a promotion effect on methanol synthesis activity.