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Shen, Wei

Publications and source records attributed to Shen, Wei.

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Visualizing plant cell wall changes proves the superiority of hydrochloric acid over sulfuric acid catalyzed γ-valerolactone pretreatment

Thermochemical pretreatment is one of the key steps to process lignocellulosic biomass for production of biofuels and biomaterials. γ-valerolactone (GVL) has been used as a green and renewable solvent to efficiently dissolve lignin under acidic conditions and enhance subsequent enzyme digestibility. Further improvement is still required to lower the pretreatment temperature in order to reduce sugar degradation and irreversible lignin condensation, as well as the capital cost. In this study, we compared the use of HCl and H 2 SO 4 as catalysts during GVL pretreatment, and found the performance of GVL-HCl at 100 °C was comparable to that of GVL-H 2 SO 4 at 120 °C in terms of xylan and lignin removal and enzyme digestibility. We further monitored the lignin removal and cellulose accessibility in the cell walls at different pretreatment time points by imaging the changes in lignin auto-fluorescence and in CtCBM3-GFP binding with confocal laser scanning microscopy (CLSM), respectively. We found GVL-HCl pretreatment at a relative low temperature (100 °C) could rapidly remove lignin in the compound middle lamella and cell corner areas, which concurred with the increase of CtCBM3-GFP binding in these areas. Real-time imaging of cell wall degradation by cellulases further revealed that the secondary cell walls could be digested from both cell lumen and CML sides, and eventually fully deconstructed within 24 h. Furthermore, our results provide new insight into the effects of chloride anions on plant cell wall structure during GVL pretreatment, and offer potential routes to further optimize and enhance the efficiency of GVL-based pretreatment.

09 BIOMASS FUELS↗
DOE OSTI2020

On Performance Prediction of Big Data Transfer in High-performance Networks

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

Liu, Wuji↗
DOE OSTI2020

Metabolic engineering of Zymomonas mobilis for anaerobic isobutanol production

Biofuels and value-added biochemicals derived from renewable biomass via biochemical conversion have attracted considerable attention to meet global sustainable energy and environmental goals. Isobutanol is a four-carbon alcohol with many advantages that make it attractive as a fossil-fuel alternative. Zymomonas mobilis is a highly efficient, anaerobic, ethanologenic bacterium making it a promising industrial platform for use in a biorefinery. In this study, the effect of isobutanol on Z. mobilis was investigated, and various isobutanol-producing recombinant strains were constructed. The results showed that the Z. mobilis parental strain was able to grow in the presence of isobutanol below 12 g/L while concentrations greater than 16 g/L inhibited cell growth. Integration of the heterologous gene encoding 2-ketoisovalerate decarboxylase such as kdcA from Lactococcus lactis is required for isobutanol production in Z. mobilis. Moreover, isobutanol production increased from nearly zero to 100-150 mg/L in recombinant strains containing the kdcA gene driven by the tetracycline-inducible promoter Ptet. In addition, we determined that overexpression of a heterologous als gene and two native genes (ilvC and ilvD) involved in valine metabolism in a recombinant Z. mobilis strain expressing kdcA can divert pyruvate from ethanol production to isobutanol biosynthesis. This engineering improved isobutanol production to above 1 g/L. Finally, recombinant strains containing both a synthetic operon, als-ilvC-ilvD, driven by Ptet and the kdcA gene driven by the constitutive strong promoter, Pgap, were determined to greatly enhance isobutanol production with a maximum titer about 4.0 g/L. Finally, isobutanol production was negatively affected by aeration with more isobutanol being produced in more poorly aerated flasks. This study demonstrated that overexpression of kdcA in combination with a synthetic heterologous operon, als-ilvC-ilvD, is crucial for diverting pyruvate from ethanol production for enhanced isobutanol biosynthesis. Moreover, this study also provides a strategy for harnessing the valine metabolic pathway for future production of other pyruvate-derived biochemicals in Z. mobilis.

09 BIOMASS FUELS↗
NASA NTRS1987

Single-state selection system for hydrogen masers

The design and operation of a single-state selection system based on the adiabatic fast-passage technique for atomic state inversion is described. The system uses a variable-pitch dc solenoid and orthogonal four-wire RF coil to create the state-changing magnetic fields, and a half-wavelength state selection magnet to remove the inverted state atoms from the hydrogen beam. The system's performance was determined by measuring maser power as a function of line Q. The system removes more than 85 percent of undesired atoms from the beam. The potential effects of improvements in the maser on its frequency stability have been calculated. The use of single-state selection combined with increased RF coupling to the cavity and increased storage bulb collimation offers the possibility of frequency stability in the 10 to the -17th regime over intervals on the order of 60,000 s.

Mattison, Edward M.↗