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A disturbance of reactive oxygen species (ROS) homeostasis may cause the pathogenesis of many diseases. Inspired by natural photosynthesis, this work proposes a photo-driven H2-evolving liposomal nanoplatform (Lip NP) that comprises an upconversion nanoparticle (UCNP) that is conjugated with gold nanoparticles (AuNPs) via a ROS-responsive linker, which is encapsulated inside the liposomal system in which the lipid bilayer embeds chlorophyll a (Chla). The UCNP functions as a transducer, converting NIR light into upconversion luminescence for simultaneous imaging and therapy in situ. Functioning as light-harvesting antennas, AuNPs are used to detect the local concentration of ROS for FRET biosensing, while the Chla activates the photosynthesis of H2 gas to scavenge local excess ROS. The results thus obtained indicate the potential of using the Lip NPs in the analysis of biological tissues, restoring their ROS homeostasis, possibly preventing the initiation and progression of diseases. Hydrogen can be used to reduce the concentration of reactive oxygen species (ROS), but its delivery to diseased tissues is challenging due to its low solubility. Here the authors develop a photosynthesis-inspired FRET nanocomplex to detect and scavenge local excess of ROS in the tissue using photocatalytic hydrogen production. [ABSTRACT FROM AUTHOR]

SUMMARY In order to evaluate quantitatively the effect of syngas cooling modes of slurry feed gasification on the hydrogen production process, two processes of gasification for hydrogen with petcoke as the feedstock were developed in the paper, which were petcoke water slurry + total quench + high water/dry gas (W/G) and petcoke water slurry + radiant syngas cooler + quench + low W/G, named by cases 1 and 2, respectively. The two processes were simulated by using Aspen Plus. The results show that with the operating parameters used by the system, the energy conversion efficiency of cases 1 and 2 are the same, which is 74%. The exergy efficiency of case 2 is higher than that of case 1, which are 62% and 61%, respectively. The water consumption of cases 1 and 2 are almost the same. However, the proportion of high-quality steam produced in case 2 is higher, and the quantity of high-quality steam is larger than that of case 1. The system profit of case 2 is better than that of case 1. Thus, case 2 is better than case 1 and is more suitable for petcoke gasification for hydrogen taking the gasification performance, energy utilization analysis, system water utility analysis, and system performance yield rate into account. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: A full factorial design was conducted to investigate the combined effects of temperatures and initial pH on fermentative hydrogen production by mixed cultures in batch tests. The experimental results showed that the modified Logistic model can be used to describe the progress of cumulative hydrogen production in the batch tests of this study. The modified Ratkowsky model can be used to describe the combined effects of the temperatures and initial pH on the substrate degradation efficiency, hydrogen yield and average hydrogen production rate. The temperatures and initial pH had interactive impact on fermentative hydrogen production. The maximum substrate degradation efficiency, the maximum hydrogen yield and the maximum average hydrogen production rate was predicted at the temperature of 37.8°C and the initial pH of 7.1, 37.4°C and 6.9, and 38.2°C and 7.2, respectively. In general, the optimal temperature for the fermentative hydrogen production was around 37.8°C and the optimal initial pH for the fermentative hydrogen production was around 7.1. [Copyright &y& Elsevier]

Abstract: The kinetic models were developed and applied for fermentative hydrogen production. They were used to describe the progress of a batch fermentative hydrogen production process, to investigate the effects of substrate concentration, inhibitor concentration, temperatures, pH, and dilution rates on the process of fermentative hydrogen production, and to establish the relationship among the substrate degradation rate, the hydrogen-producing bacteria growth rate and the product formation rate. This review showed that the modified Gompertz model was widely used to describe the progress of a batch fermentative hydrogen production process, while the Monod model was widely used to describe the effects of substrate concentration on the rates of substrate degradation, hydrogen-producing bacteria growth and hydrogen production. Arrhenius model was used a lot to describe the effects of temperature on fermentative hydrogen production, while modified Han–Levenspiel model was used to describe the effects of inhibitor concentration on fermentative hydrogen production. The Andrew model was used to describe the effects of H+ concentration on the specific hydrogen production rate, while the Luedeking–Piret model and its modified form were widely used to describe the relationship between the hydrogen-producing bacteria growth rate and the product formation rate. Finally, some suggestions for future work with these kinetic models were proposed. [Copyright &y& Elsevier]

Abstract: A fractional factorial design was carried out to investigate the effects of temperature, initial pH and glucose concentration on fermentative hydrogen production by mixed cultures in batch tests and then the experimental data of substrate degradation efficiency, hydrogen yield and average hydrogen production rate were described by a neural network, based on which the simultaneous optimization of the three responses was performed by the method of desirability function. The analysis showed that the neural network could successfully describe the effects of temperature, initial pH and glucose concentration on the substrate degradation efficiency, hydrogen yield and average hydrogen production rate of this study. The maximum substrate degradation efficiency of 95.3%, hydrogen yield of 305.3mL/g glucose and average hydrogen production rate of 23.9mL/h were all obtained at the optimal temperature of 39.0°C, initial pH of 7.0 and glucose concentration of 24.6g/L identified by the method of desirability function based on a neural network. In sum, the method of desirability function based on a neural network was a useful tool to optimize several responses for fermentative hydrogen production processes simultaneously. [Copyright &y& Elsevier]

Abstract: This review summarized several main factors influencing fermentative hydrogen production. The reviewed factors included inoculum, substrate, reactor type, nitrogen, phosphate, metal ion, temperature and pH. In this review, the effect of each factor on fermentative hydrogen production and the advance in the research of the effect were briefly introduced and discussed, followed by some suggestions for the future work of fermentative hydrogen production. This review showed that there usually existed some disagreements on the optimal condition of a given factor for fermentative hydrogen production, thus more researches in this respect are recommended. Furthermore, most of the studies on fermentative hydrogen production were conducted in batch mode using glucose and sucrose as substrate, thus more studies on fermentative hydrogen production in continuous mode using organic wastes as substrate are recommended. [Copyright &y& Elsevier]

Abstract: A central composite design was carried out to investigate the effect of temperature, initial pH and glucose concentration on fermentative hydrogen production by mixed cultures in batch test. The modeling abilities of the response surface methodology model and neural network model, as well as the optimizing abilities of response surface methodology and the genetic algorithm based on a neural network model were compared. The results showed that the root mean square error and the standard error of prediction for the neural network model were much smaller than those for the response surface methodology model, indicting that the neural network model had a much higher modeling ability than the response surface methodology model. The maximum hydrogen yield of 289.8mL/g glucose identified by response surface methodology was a little lower than that of 360.5mL/g glucose identified by the genetic algorithm based on a neural network model, indicating that the genetic algorithm based on a neural network model had a much higher optimizing ability than the response surface methodology. Thus, the genetic algorithm based on a neural network model is a better optimization method than response surface methodology and is recommended to be used during the optimization of fermentative hydrogen production process. [Copyright &y& Elsevier]

Abstract: This review summarized the experimental design methods used to investigate the effects of various factors on fermentative hydrogen production processes, including one-factor-at-a-time design, full factorial design, Taguchi design, Plackett–Burman design, central composite design and Box–Behnken design. Each design method was briefly introduced, followed by the introduction of its analysis. In addition, the advantages and disadvantages of each design method were briefly discussed. Moreover, the application of each design method to the study of fermentative hydrogen production was analyzed and discussed. Based on the discussion in this review, an experimental design strategy for optimizing fermentative hydrogen production processes was proposed. In the end, the software packages that can carry out the above mentioned factorial design and analysis were briefly introduced. [Copyright &y& Elsevier]

Abstract: The effect of temperature, initial pH and glucose concentration on fermentative hydrogen production by mixed cultures was investigated in batch tests, and the optimization of fermentative hydrogen production process was conducted by response surface methodology with a central composite design. Experimental results showed that temperatures, initial pH and glucose concentrations had impact on fermentative hydrogen production individually and interactively. The maximum hydrogen yield of 289.8mL/g glucose was estimated at the temperature of 38.6°C, the initial pH of 7.2 and the glucose concentration of 23.9g/L. The maximum hydrogen production rate of 28.2mL/h was estimated at the temperature of 37.8°C, the initial pH of 7.2 and the glucose concentration of 27.6g/L. The maximum substrate degradation efficiency of 96.9% was estimated at the temperature of 39.3°C, the initial pH of 7.0 and the glucose concentration of 26.8g/L. Response surface methodology was a better method to optimize the fermentative hydrogen production process. Modified logistic model could describe the progress of cumulative hydrogen production in the batch tests of this study successfully. [Copyright &y& Elsevier]

Abstract: The inhibitory effect of added ethanol, acetic acid, propionic acid and butyric acid on fermentative hydrogen production by mixed cultures was investigated in batch tests using glucose as substrate. The experimental results showed that, at 35°C and initial pH 7.0, during the fermentative hydrogen production, the substrate degradation efficiency, hydrogen production potential, hydrogen yield and hydrogen production rate all trended to decrease with increasing added ethanol, acetic acid, propionic acid and butyric acid concentration from 0 to 300mmol/L. The inhibitory effect of added ethanol on fermentative hydrogen production was smaller than those of added acetic acid, propionic acid and butyric acid. The modified Han–Levenspiel model could describe the inhibitory effects of added ethanol, acetic acid, propionic acid and butyric acid on fermentative hydrogen production rate in this study successfully. The modified Logistic model could describe the progress of cumulative hydrogen production. [Copyright &y& Elsevier]

In this paper, the effect of Ni2+ concentration ranging from 0 to 50mg/L on fermentative hydrogen production by mixed cultures was investigated in batch test. The results showed that at 35°C and initial pH 7.0, Ni2+ was able to enhance the hydrogen production rate with increasing Ni2+ concentration from 0 to 0.2mg/L, and enhance the hydrogen production potential and hydrogen yield with increasing Ni2+ concentration from 0 to 0.1mg/L. The maximum hydrogen production potential of 288.6mL and the maximum hydrogen yield of 296.1mL/g glucose were obtained at the Ni2+ concentration of 0.1mg/L. In all tests, the major soluble metabolites produced by mixed cultures were ethanol, acetic acid and butyric acid, without propionic acid. Ni2+ had little effect on the substrate degradation efficiency with increasing concentration from 0 to 50mg/L. Ni2+ was able to enhance the biomass production yield with increasing Ni2+ concentration from 0 to 0.1mg/L. The maximum biomass production yield of 232.5mg/g glucose was obtained at the Ni2+ concentration of 0.1mg/L. In all tests, the final pH after fermentative hydrogen production was lower than the initial pH. [Copyright &y& Elsevier]

Abstract: Effect of temperatures ranging from 20°C to 55°C on fermentative hydrogen production by mixed cultures was investigated in batch tests. The experimental results showed that, at initial pH 7.0, during the fermentative hydrogen production using glucose as substrate, the substrate degradation efficiency and hydrogen production potential increased with increasing temperatures from 20°C to 40°C. The maximal substrate degradation efficiency was 98.1%, the maximal hydrogen production potential was 269.9mL, the maximal hydrogen yield was 275.1mL/g glucose and the shortest lag time was 7.0h. The temperature for fermentative hydrogen production by mixed cultures was optimized to be 40°C. The expanded Ratkowsky models could be used to describe the effect of temperatures on the hydrogen production potential, maximum hydrogen production rate and the lag time during fermentative hydrogen production. [Copyright &y& Elsevier]

The effect of ammonia concentration ranging from 0 to 10g N/L on fermentative hydrogen production by mixed cultures was investigated in batch tests using glucose as substrate at 35°C and initial pH 7.0. The experimental results showed that during the fermentative hydrogen production, the substrate degradation efficiency increased with increasing ammonia concentration from 0 to 0.01g N/L. The hydrogen production potential, hydrogen yield and average hydrogen production rate increased with increasing ammonia concentration from 0 to 0.1g N/L. The maximum hydrogen production potential of 291.4mL, maximum hydrogen yield of 298.8mL/g glucose and maximum average hydrogen production rate of 8.5mL/h were all obtained at the ammonia concentration of 0.1g N/L. [Copyright &y& Elsevier]

Abstract: Eight new diiron carbonyl dithiolate complexes, [(μ-xdt)Fe2(CO)5(L)]; xdt=bdt, L=dppmBH3 (2), dppeBH3 (2a), dppm (2b), xdt=edt, L=dppmBH3 (4), dppeBH3 (4a), xdt=Bn-adt, L=dppmBH3 (5), dppeBH3 (5a), and [(μ-bdt)Fe2(CO)4(μ-dppm)], (3), have been prepared and characterized by FTIR, NMR spectroscopy and X-ray single crystallography. Molecular structures of complexes 2–5 reveal that the Fe2 core exhibits a butterfly conformation and each Fe center is of the pseudo-square-pyramidal coordination geometry. For the mono-substituted species, the phosphine ligand is located in the axial position. For the di-substituted species, the phosphine ligand is spanned between two Fe sites, occupying the basal position. The attached borane unit exerts electronic withdrawing influence on the electron richness about the Fe center. When the phosphine pendant is not protected by borane, coordination to the adjacent Fe site occurs under the reducing condition. It allows synthesis of 3 from chemical or electrochemical reduction of 2b. Electrocatalysis of acetic acid by complexes 2–5 is studied. The bdt derivatives are reduced at a potential 300mV more positive than the edt and adt analogs. For the latter species, electrocatalytic events occur near the first reduction. In contrast, no catalysis is observed for 2 in the available electrochemical windows. The rate constant of the catalytic reaction by the species is measured. The adt derivative reveals the highest efficiency toward hydrogen production from acetic acid. [Copyright &y& Elsevier]