Review of Novel Catalysts for Biomass Tar Cracking and Methane Reforming

A review of the literature was conducted to examine the performance of catalysts other than conventional nickel catalysts, and alkaline earth and olivine based catalysts for treating hot raw product gas from a biomass gasifier to convert methane and tars into synthesis gas. Metal catalysts other than Ni included precious metals Rh, Ru, Ir, Pt, and Pd, as well as Cu, Co, and Fe in limited testing. Nickel catalysts promoted with Rh, Zr, Mn, Mo, Ti, Ag, or Sn were also examined, as were Ni catalysts on Ce2O3, TiO2, ZrO2, SiO2, and La2O3. In general, Rh stood out as a consistently superior metal catalyst for methane reforming, tar cracking, and minimizing carbon buildup on the catalyst. Ru and Ir also showed significant improvement over Ni for methane reforming. Ceria stood out as good support material and particularly good promoter material when added in small quantities to another support material such as alumina, zirconia, or olivine. Other promising supports were lanthana, zirconia, and titania

Bifidobacterium longum subsp. infantis in experimental necrotizing enterocolitis: alterations in inflammation, innate immune response, and the microbiota.

BackgroundProbiotics decrease the risk of necrotizing enterocolitis (NEC). We sought to determine the impact of Bifidobacterium longum subsp. infantis (B. infantis) in the established rat model of NEC.MethodsRat pups delivered 1 d prior to term gestation were assigned to one of three groups: dam fed (DF), formula fed (FF), or fed with formula supplemented with 5 × 10(6) CFU B. infantis per day (FF+Binf). Experimental pups were exposed to hypoxia and cold stress. Ileal tissue was examined for pathology and expression of inflammatory mediators, antimicrobial peptides, and goblet-cell products. Ceca were assessed for bacterial composition by analysis of the 16S rRNA sequence.ResultsAdministration of B. infantis significantly reduced the incidence of NEC, decreased expression of Il6, Cxcl1, Tnfa, Il23, and iNOS, and decreased expression of the antimicrobial peptides Reg3b and Reg3g. There was significant microbial heterogeneity both within groups and between experiments. The cecal microbiota was not significantly different between the FF and FF+Binf groups. Bifidobacteria were not detected in the cecum in significant numbers.ConclusionIn the rat model, the inflammation associated with NEC was attenuated by administration of probiotic B. infantis. Dysbiosis was highly variable, precluding determination of the precise role of the microbiota in experimental NEC

Human Apprenticeship Learning via Kernel-based Inverse Reinforcement Learning

It has been well demonstrated that inverse reinforcement learning (IRL) is an effective technique for teaching machines to perform tasks at human skill levels given human demonstrations (i.e., human to machine apprenticeship learning). This paper seeks to show that a similar application can be demonstrated with human learners. That is, given demonstrations from human experts inverse reinforcement learning techniques can be used to teach other humans to perform at higher skill levels (i.e., human to human apprenticeship learning). To show this two experiments were conducted using a simple, real-time web game where players were asked to touch targets in order to earn as many points as possible. For the experiment player performance was defined as the number of targets a player touched, irrespective of the points that a player actually earned. This allowed for in-game points to be modified and the effect of these alterations on performance measured. At no time were participants told the true performance metric. To determine the point modifications IRL was applied on demonstrations of human experts playing the game. The results of the experiment show with significance that performance improved over the control for select treatment groups. Finally, in addition to the experiment, we also detail the algorithmic challenges we faced when conducting the experiment and the techniques we used to overcome them.Comment: 31 pages, 23 figures, Submitted to Journal of Artificial Intelligence Research, "for source code, see https://github.com/mrucker/kpirl-kla

Collaborative multidisciplinary learning : quantity surveying students’ perspectives

The construction industry is highly fragmented and is known for its adversarial culture, culminating in poor quality projects not completed on time or within budget. The aim of this study is thus to guide the design of QS programme curricula in order to help students develop the requisite knowledge and skills to work more collaboratively in their multi-disciplinary future workplaces. A qualitative approach was considered appropriate as the authors were concerned with gathering an initial understanding of what students think of multi-disciplinary learning. The data collection method used was a questionnaire which was developed by the Behaviours4Collaboration (B4C) team. Knowledge gaps were still found across all the key areas where a future QS practitioner needs to be collaborative (either as a project contributor or as a project leader) despite the need for change instigated by the multi-disciplinary (BIM) education revolution. The study concludes that universities will need to be selective in teaching, and innovative in reorienting, QS education so that a collaborative BIM education can be effected in stages, increasing in complexity as the students’ technical knowledge grows. This will help students to build the competencies needed to make them future leaders. It will also support programme currency and delivery

Suitability of litter amendments for the Australian chicken meat industry

This project focused on litter amendment products, which are used overseas during the rearing of meat chickens. Litter amendments are primarily used to manage ammonia volatilisation, especially when litter is reused, but also provide antimicrobial and environmental benefits, and increase the nutrient value of spent litter. This report summarises the outcomes of consultation with representatives and stakeholders of the Australian chicken meat industry, and summarises key findings from a literature review on litter amendments

Long-Term Testing of Rhodium-Based Catalysts for Mixed Alcohol Synthesis ? 2013 Progress Report

The U.S. Department of Energy’s Pacific Northwest National Laboratory has been conducting research since 2005 to develop a catalyst for the conversion of synthesis gas (carbon monoxide and hydrogen) into mixed alcohols for use in liquid transportation fuels. Initially, research involved screening possible catalysts based on a review of the literature, because at that time, there were no commercial catalysts available. The screening effort resulted in a decision to focus on catalysts containing rhodium and manganese. Subsequent research identified iridium as a key promoter for this catalyst system. Since then, research has continued to improve rhodium/manganese/iridium-based catalysts, optimizing the relative and total concentrations of the three metals, examining baseline catalysts on alternative supports, and examining effects of additional promoters. Testing was continued in FY 2013 to evaluate the performance and long-term stability of the best catalysts tested to date. Three tests were conducted. A long-term test of over 2300 hr duration at a single set of operating conditions was conducted with the best carbon-supported catalyst. A second test of about 650 hr duration at a single set of operating conditions was performed for comparison using the same catalyst formulation on an alternative carbon support. A third test of about 680 hr duration at a single set of operating conditions was performed using the best silica-supported catalyst tested to date

Mixed Alcohol Synthesis Catalyst Screening

National Renewable Energy Laboratory (NREL) and Pacific Northwest National Laboratory (PNNL) are conducting research to investigate the feasibility of producing mixed alcohols from biomass-derived synthesis gas (syngas). PNNL is tasked with obtaining commercially available or preparing promising mixed-alcohol catalysts and screening them in a laboratory-scale reactor system. Commercially available catalysts and the most promising experimental catalysts are provided to NREL for testing using a slipstream from a pilot-scale biomass gasifier. From the standpoint of producing C2+ alcohols as the major product, it appears that the rhodium catalyst is the best choice in terms of both selectivity and space-time yield (STY). However, unless the rhodium catalyst can be improved to provide minimally acceptable STYs for commercial operation, mixed alcohol synthesis will involve significant production of other liquid coproducts. The modified Fischer-Tropsch catalyst shows the most promise for providing both an acceptable selectivity to C2+ alcohols and total liquid STY. However, further optimization of the Fischer-Tropsch catalysts to improve selectivity to higher alcohols is highly desired. Selection of a preferred catalyst will likely entail a decision on the preferred coproduct slate. No other catalysts tested appear amenable to the significant improvements needed for acceptable STYs

Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes

SMC (Sequential Monte Carlo) is a class of Monte Carlo algorithms for filtering and related sequential problems. Gerber and Chopin (2015) introduced SQMC (Sequential quasi-Monte Carlo), a QMC version of SMC. This paper has two objectives: (a) to introduce Sequential Monte Carlo to the QMC community, whose members are usually less familiar with state-space models and particle filtering; (b) to extend SQMC to the filtering of continuous-time state-space models, where the latent process is a diffusion. A recurring point in the paper will be the notion of dimension reduction, that is how to implement SQMC in such a way that it provides good performance despite the high dimension of the problem.Comment: To be published in the proceedings of MCMQMC 201

Analysis of the Effects of Compositional and Configurational Assumptions on Product Costs for the Thermochemical Conversion of Lignocellulosic Biomass to Mixed Alcohols -- FY 2007 Progress Report

The purpose of this study was to examine alternative biomass-to-ethanol conversion process assumptions and configuration options to determine their relative effects on overall process economics. A process-flow-sheet computer model was used to determine the heat and material balance for each configuration that was studied. The heat and material balance was then fed to a costing spreadsheet to determine the impact on the ethanol selling price. By examining a number of operational and configuration alternatives and comparing the results to the base flow sheet, alternatives having the greatest impact the performance and cost of the overall system were identified and used to make decisions on research priorities