Catalytic Production of Fuels and Chemicals from Biomass-derived Oxygenated Hydrocarbons

2008 ◽  
Vol 80 (9) ◽  
pp. 1233-1233
Author(s):  
J. A. Dumesic
Author(s):  
R. T. K. Baker ◽  
R. D. Sherwood

The catalytic gasification of carbon at high temperature by microscopic size metal particles is of fundamental importance to removal of coke deposits and conversion of refractory hydrocarbons into fuels and chemicals. The reaction of metal/carbon/gas systems can be observed by controlled atmosphere electron microscopy (CAEM) in an 100 KV conventional transmission microscope. In the JEOL gas reaction stage model AGl (Fig. 1) the specimen is positioned over a hole, 200μm diameter, in a platinum heater strip, and is interposed between two apertures, 75μm diameter. The control gas flows across the specimen and exits through these apertures into the specimen chamber. The gas is further confined by two apertures, one in the condenser and one in the objective lens pole pieces, and removed by an auxiliary vacuum pump. The reaction zone is <1 mm thick and is maintained at gas pressure up to 400 Torr and temperature up to 1300<C as measured by a Pt-Pt/Rh 13% thermocouple. Reaction events are observed and recorded on videotape by using a Philips phosphor-television camera located below a hole in the center of the viewing screen. The overall resolution is greater than 2.5 nm.


2020 ◽  
Author(s):  
Artur Schweidtmann ◽  
Jan Rittig ◽  
Andrea König ◽  
Martin Grohe ◽  
Alexander Mitsos ◽  
...  

<div>Prediction of combustion-related properties of (oxygenated) hydrocarbons is an important and challenging task for which quantitative structure-property relationship (QSPR) models are frequently employed. Recently, a machine learning method, graph neural networks (GNNs), has shown promising results for the prediction of structure-property relationships. GNNs utilize a graph representation of molecules, where atoms correspond to nodes and bonds to edges containing information about the molecular structure. More specifically, GNNs learn physico-chemical properties as a function of the molecular graph in a supervised learning setup using a backpropagation algorithm. This end-to-end learning approach eliminates the need for selection of molecular descriptors or structural groups, as it learns optimal fingerprints through graph convolutions and maps the fingerprints to the physico-chemical properties by deep learning. We develop GNN models for predicting three fuel ignition quality indicators, i.e., the derived cetane number (DCN), the research octane number (RON), and the motor octane number (MON), of oxygenated and non-oxygenated hydrocarbons. In light of limited experimental data in the order of hundreds, we propose a combination of multi-task learning, transfer learning, and ensemble learning. The results show competitive performance of the proposed GNN approach compared to state-of-the-art QSPR models making it a promising field for future research. The prediction tool is available via a web front-end at www.avt.rwth-aachen.de/gnn.</div>


Reactions ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 130-146
Author(s):  
Yali Yao ◽  
Baraka Celestin Sempuga ◽  
Xinying Liu ◽  
Diane Hildebrandt

In order to explore co-production alternatives, a once-through process for CO2 hydrogenation to chemicals and liquid fuels was investigated experimentally. In this approach, two different catalysts were considered; the first was a Cu-based catalyst that hydrogenates CO2 to methanol and CO and the second a Fisher–Tropsch (FT) Co-based catalyst. The two catalysts were loaded into different reactors and were initially operated separately. The experimental results show that: (1) the Cu catalyst was very active in both the methanol synthesis and reverse-water gas shift (R-WGS) reactions and these two reactions were restricted by thermodynamic equilibrium; this was also supported by an Aspen plus simulation of an (equilibrium) Gibbs reactor. The Aspen simulation results also indicated that the reactor can be operated adiabatically under certain conditions, given that the methanol reaction is exothermic and R-WGS is endothermic. (2) the FT catalyst produced mainly CH4 and short chain saturated hydrocarbons when the feed was CO2/H2. When the two reactors were coupled in series and the presence of CO in the tail gas from the first reactor (loaded with Cu catalyst) significantly improves the FT product selectivity toward higher carbon hydrocarbons in the second reactor compared to the standalone FT reactor with only CO2/H2 in the feed.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
James Kirby ◽  
Gina M. Geiselman ◽  
Junko Yaegashi ◽  
Joonhoon Kim ◽  
Xun Zhuang ◽  
...  

Abstract Background Mitigation of climate change requires that new routes for the production of fuels and chemicals be as oil-independent as possible. The microbial conversion of lignocellulosic feedstocks into terpene-based biofuels and bioproducts represents one such route. This work builds upon previous demonstrations that the single-celled carotenogenic basidiomycete, Rhodosporidium toruloides, is a promising host for the production of terpenes from lignocellulosic hydrolysates. Results This study focuses on the optimization of production of the monoterpene 1,8-cineole and the sesquiterpene α-bisabolene in R. toruloides. The α-bisabolene titer attained in R. toruloides was found to be proportional to the copy number of the bisabolene synthase (BIS) expression cassette, which in turn influenced the expression level of several native mevalonate pathway genes. The addition of more copies of BIS under a stronger promoter resulted in production of α-bisabolene at 2.2 g/L from lignocellulosic hydrolysate in a 2-L fermenter. Production of 1,8-cineole was found to be limited by availability of the precursor geranylgeranyl pyrophosphate (GPP) and expression of an appropriate GPP synthase increased the monoterpene titer fourfold to 143 mg/L at bench scale. Targeted mevalonate pathway metabolite analysis suggested that 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGR), mevalonate kinase (MK) and phosphomevalonate kinase (PMK) may be pathway bottlenecks are were therefore selected as targets for overexpression. Expression of HMGR, MK, and PMK orthologs and growth in an optimized lignocellulosic hydrolysate medium increased the 1,8-cineole titer an additional tenfold to 1.4 g/L. Expression of the same mevalonate pathway genes did not have as large an impact on α-bisabolene production, although the final titer was higher at 2.6 g/L. Furthermore, mevalonate pathway intermediates accumulated in the mevalonate-engineered strains, suggesting room for further improvement. Conclusions This work brings R. toruloides closer to being able to make industrially relevant quantities of terpene from lignocellulosic biomass.


2021 ◽  
Vol 19 (4) ◽  
pp. 383-391
Author(s):  
Chenxi Zhao ◽  
Yupeng Xing ◽  
Wei Lv ◽  
Juhui Chen ◽  
Xiaogang Liu ◽  
...  

Abstract It is being considered to pyrolyze lignin-rich biomass samples (hazelnut shells, HSs) into bio-fuels and chemicals to solve energy shortages and environmental concerns, volatile products (including liquid products and gas products) were produced and characterized from HSs pyrolysis at 400–1000 °C. With the temperature increases, the maximum output of liquid products was up to 35.79% produced at 700 °C, gas products yields increased from 21.82 to 55.46%. Gas chromatography and mass spectrometry (GC–MS) study indicated that liquid products from HSs riched in phenolic compounds, exceed 42% of liquid products and increased as the temperature rises. The application experiment showed that HSs liquid products had a significant role in antioxidant activity, and revealed that not limited to phenols, all compounds containing phenolic hydroxyl structure act as antioxidant. Composition analysis of gas products showed that more combustible gases were produced at the higher temperature, resulted in the significant increase in gas products higher heating value (HHV) from 6.21 to 24.36 MJ/kg.


Proceedings ◽  
2021 ◽  
Vol 66 (1) ◽  
pp. 31
Author(s):  
Sachiko Nakamura ◽  
Norio Kurosawa

Lignocellulosic biomass comprises cellulose, hemicellulose, and lignin and is a potential source of fuels and chemicals. Although this complex biomass is persistent, it can be cooperatively decomposed by a microbial consortium in nature. In this study, a coculture of the moderately thermophilic bacteria Thermobifida fusca and Ureibacillus thermosphaericus was used for biodegradation of rice chaff. The bacterial strains were incubated in modified Brock’s basal salt medium (pH 8.0) supplemented with yeast extract and rice chaff at 50 °C for 7 days. The concentration of reducing sugars and the enzymatic activities of laccase, lignin peroxidase, cellulase, and xylanase in the supernatant of the culture medium were measured every day. The concentrations of reducing sugars in solo cultures of T. fusca and U. thermosphaericus and a mixed culture of the two strains after 7 days of incubation were 0.047, 0.040, and 0.195 mg/mL, respectively, indicating that the decomposition of rice chaff was enhanced in the coculture. Based on the results, it is thought that the lignin surrounding the cellulose was decomposed by laccase and lignin peroxidase secreted from U. thermosphaericus, resulting in cellulose and hemicellulose in the rice chaff being easily decomposed by enzymes from T. fusca.


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