Improved multivariate calibration models for corn stover feedstock and dilute-acid pretreated corn stover

We have studied rapid calibration models to predict the composition of a variety of biomass feedstocks by correlating near-infrared (NIR) spectroscopic data to compositional data produced using traditional wet chemical analysis techniques. The rapid calibration models are developed using multivariate statistical analysis of the spectroscopic and wet chemical data. This work discusses the latest versions of the NIR calibration models for corn stover feedstock and dilute-acid pretreated corn stover. Measures of the calibration precision and uncertainty are presented. No statistically significant differences (p = 0.05) are seen between NIR calibration models built using different mathematical pretreatments. Finally, two common algorithms for building NIR calibration models are compared; no statistically significant differences (p = 0.05) are seen for the major constituents glucan, xylan, and lignin, but the algorithms did produce different predictions for total extractives. A single calibration model combining the corn stover feedstock and dilute-acid pretreated corn stover samples gave less satisfactory predictions than the separate models.     

Assessing corn stover composition and sources of variability via NIRS

Corn stover, the above-ground, non-grain portion of the crop, is a large, currently available source of biomass that potentially could be collected as a biofuels feedstock. Biomass conversion process economics are directly affected by the overall biochemical conversion yield, which is assumed to be proportional to the carbohydrate content of the feedstock materials used in the process. Variability in the feedstock carbohydrate levels affects the maximum theoretical biofuels yield and may influence the optimum pretreatment or saccharification conditions. The aim of this study is to assess the extent to which commercial hybrid corn stover composition varies and begin to partition the variation among genetic, environmental, or annual influences. A rapid compositional analysis method using near-infrared spectroscopy/partial least squares multivariate modeling (NIR/PLS) was used to evaluate compositional variation among 508 commercial hybrid corn stover samples collected from 47 sites in eight Corn Belt states after the 2001, 2002, and 2003 harvests. The major components of the corn stover, reported as average (standard deviation) % dry weight, whole biomass basis, were glucan 31.9 (2.0), xylan 18.9 (1.3), solubles composite 17.9 (4.1), and lignin (corrected for protein) 13.3 (1.1). We observed wide variability in the major corn stover components. Much of the variation observed in the structural components (on a whole biomass basis) is due to the large variation found in the soluble components. Analysis of variance (ANOVA) showed that the harvest year had the strongest effect on corn stover compositional variation, followed by location and then variety. The NIR/PLS rapid analysis method used here is well suited to testing large numbers of samples, as tested in this study, and will support feedstock improvement and biofuels process research.     

Hydrogen Production by Chemical Looping Gasification of Corn Stalk Driven by a tert-Butanol Solution

The purpose of this work is to convert organic wastewater into oxidants(H₂O and CO₂) to promote biomass gasification during the chemical looping process to achieve high-H₂/CO-ratio syngas. A tert-butanol solution was selected as the model organic wastewater to generate enough H₂O and CO₂ to promote corn stalk chemical looping gasification(CLG). A series of CLG experiments was conducted at 850℃ under various degrees of oxygen excess(Ω). An Ω of approximately 0.9 led to the highest hydrogen yield and fixed carbon conversion compared with the other cases. Chemometrics and thermodynamic analysis further validated the possibility of corn stalk CLG using a tert-butanol solution. The results show that CLG of biomass-organic wastewater can both treat organic waste and promote chemical looping processes.     

Development of High Performance Heterogeneous Catalysts for Selective Cleavage of C−O and C−C Bonds of Biomass‐Derived Oxygenates

The environmental impact of CO₂ emissions via the use of fossil resources as chemical feedstock and fuels has stimulated research to utilize renewable biomass feedstock. The biogenic compounds such as polyols are highly oxygenated and their valorization requires the new methods to control the oxygen to carbon ratio of the chemicals. The catalytic cleavage of C?O bonds and C?C bonds is promising methods, but the conventional catalyst systems encounter the difficulty to obtain the high yields of the desired products. This review describes our recent development of the high performance heterogeneous catalysts for the valorization of the biogenic chemicals such as glycerol, furfural, and levulinic acid via selective cleavage of C?O bonds and C?C bonds in the liquid‐phase. Selective C?O bond cleavage by hydrogenolysis enables production of various diols useful as engineering plastics, antifreeze, and cosmetics in high yields. The success of the selective C?C bond scission of levulinic acid can be applied to a wide range of the biogenic oxygenates such as carboxylic acids, esters, lactones, and primary alcohols, in which the selective C?C bond scission at adjacent to the oxygen functional groups are achieved. Furthermore, valorization of glycerol by selective acetylation and acetalization, and of levulinic acid by hydrogenation is described. Our catalysts show excellent performance compared to the reported catalysts in the aforementioned valorization.     

Catalytic Synthesis of 2,5‐Furandicarboxylic Acid from Concentrated 2,5‐Diformylfuran Mediated by N‐hydroxyimides under Mild Conditions

Producing polyester monomer 2,5‐furandicarboxylic acid (FDCA) from biomass as an alternative to fossil‐derived terephthalic acid has drawn much attention from both academy and industry. In this work, an efficient FDCA synthesis was proposed from 10.6 wt % 2,5‐diformylfuran (DFF) in acetic acid using a combined catalytic system of Co/Mn acetate and N‐hydroxyimides. The intermediate product of 5‐formyl‐2‐furandicarboxylic acid (FFCA) possesses the least reactive formyl group. N‐hydroxysuccinimide was found to be superior to N‐hydroxyphthalimide in catalyzing the oxidation of the formyl group in FFCA intermediate, affording a near 95 % yield of FDCA under mild conditions of 100 °C. Trace maleic anhydride was detected as by‐product, which mainly came from the oxidative cleavage of DFF via furfural, furoic acid and 5‐acetoxyl‐2(5H)‐furanone as intermediates.     

Cost‐Effective Biomass Carbon/Calix[4]Quinone Composites for Lithium Ion Batteries

Searching for new cheap encapsulating materials to decrease the solubility of organic small molecules as the cathode materials in electrolytes and improve the performance of organic lithium‐ion batteries (LIBs) is very important and highly desirable. In this research, we found that a novel cheap biomass carbon (named as PPL), prepared by pyrolyzing calyxes of Physalis Peruviana L, can efficiently encapsulate calix[4]quinone to form composites, which can be used as cathodes in LIBs. The initial discharge capacity of the as‐fabricated battery was 437 mAh g^?1 and could maintain 228 mAh g^?1 after 100 cycles. Even at 1 C, the discharge capacity was still 217 mAh g^?1.     

不同LED光质对枳壳幼苗生长发育的影响

重庆是全国唯一的柑橘黄龙病非疫区及首创“柑橘良种无病毒三级繁育体系”的产区。但是,由于重庆年均日照时数少且年内分配不均,使其柑橘育苗周期显著长于其他产区,严重制约了重庆柑橘苗木产业的发展速度。利用新型节能光源发光二极管(LED)进行秋冬季补光,可缩短柑橘育苗周期,加快优质无毒柑橘新品苗木的繁育。为了阐明不同LED光质及配比对枳壳幼苗生长发育的影响,以砂培枳壳幼苗为试验材料,采用6种LED光处理(红光、蓝光、红蓝1∶1、红蓝4∶1、红黄蓝4∶1∶1 和白光),统计、测定了植株的表型和生物量指标, 为缩短柑橘砧木及新品种苗木繁育周期提供理论和实验依据。结果表明：与荧光灯相比较,不同的LED复合光均显著促进了根伸长、茎增粗(除红蓝1∶1外)、叶变窄;LED红蓝1∶1和红蓝4∶1复合光抑制茎伸长、叶片数形成,促进叶增厚,且后者的叶长被促进、叶面积增大;而红黄蓝4∶1∶1复合光促进茎伸长、叶形成、叶伸长、叶变薄和叶面积增大。相对于单色光来说LED白光及高比例红光的复合光更有利于枳壳幼苗物质合成以及其地上、地下物质分配量;且LED红黄蓝4∶1∶1复合光下枳壳幼苗地上部分的生物量最大,而根冠比最小。因此,LED红黄蓝4∶1∶1复合光最适宜于枳壳幼苗的物质合成与地上部分生长,可为光照不足季节或地区(特别是重庆地区)柑橘苗木的LED精准补光技术构建提供理论依据。     

Biomass fly ash deposition in an entrained flow reactor

Fly ash deposition on boiler surfaces is a major operational problem encountered in biomass-fired boilers. Understanding deposit formation, and developing modelling tools, will allow improvements in boiler efficiency and availability. In this study, deposit formation of a model biomass ash species (K₂Si₄O₉) on steel tubes, was investigated in a lab-scale Entrained Flow Reactor. K₂Si₄O₉ was injected into the reactor, to form deposits on an air-cooled probe, simulating deposit formation on superheater tubes in boilers. The influence of flue gas temperature (589 – 968°C), probe surface temperature (300 – 550°C), flue gas velocity (0.7 – 3.5?m/s), fly ash flux (10,000 – 40,000?g/m²h), and probe residence time (up to 60?min) was investigated. The results revealed that increasing flue gas temperature and probe surface temperature increased the sticking probability of the fly ash particles, thereby increasing the rate of deposit formation. However, increasing flue gas velocity resulted in a decrease in the deposit formation rate, due to increased particle rebound. Furthermore, the deposit formation rate increased with probe residence time and fly ash flux. Inertial impaction was the primary mechanism of deposit formation, forming deposits only on the upstream side of the steel tube. A mechanistic model was developed for predicting deposit formation in the reactor. Deposit formation by thermophoresis and inertial impaction was incorporated into the model, and the sticking probability of the ash particles was estimated by accounting for energy dissipation due to particle deformation. The model reasonably predicted the influence of flue gas temperature and fly ash flux on the deposit formation rate.     

Generalized two-dimensional correlation infrared spectroscopy to reveal the mechanisms of lignocellulosic biomass pyrolysis

As the initial stage of combustion, pyrolysis plays a significant role in the combustion of biomass, a typical solid fuel that contains higher volatile contents than other solid fuels. To better understand the pyrolysis mechanism, we herein employed generalized two-dimensional correlation infrared spectroscopy (2D-PCIS) to analyze the functional group evolution in bamboo chars between 250 and 600 °C, and by combination of the volatile release properties, the biomass pyrolysis process mechanism was speculated. We found that below 250 °C, the hydrogen bonding network within the biomass macromolecular structure was broken, while at 250–300 °C, the branched structures were broken during hydration and decarboxylation reactions, resulting in the formation of H₂O, acetic acids, and CO₂. The subsequent formation of various phenols between 300 and 350 °C mainly originated from rupture of the ether bridges in the lignin structure. In addition, molecular rearrangement of the intermediates from the decomposition of holocellulose resulted in aromatic ring formation. Interestingly, analysis by 2D-PCIS demonstrated that the aromatic rings bearing adjacent substituents easily formed double active sites following breakage of the branched structures. These structures then easily produced fused ring systems below 400 °C, while dehydrogenation and polycondensation at?>?400 °C promoted the formation of fused rings from aromatic rings without adjacent substituents.     

Cellulose and hemicellulose hydrolysis models for application to current and novel pretreatment processes

Acids catalyze the hydrolysis of cellulose and hemicellulose to produce sugars that organisms can ferment to ethanol and other products. However, advanced low- and no-acid technologies are critical if we are to reduce bioethanol costs to be competitive as a pure fuel. We believe carbohy drate oligomers play a key role in explaining the performance of such hydrolysis processes and that kinetic models would help us understand their role. Various investigations have developed reaction rate expressions based on an Arrhenius temperature dependence that is first order in substrate concentration and close to first order in acid concentration. In this article, we evaluate these existing hydrolysis models with the goal of providing a foundation for a unified model that can predict performance of both current and novel pretreatment process configurations.