Exploring the Thermodynamic Limits of Enhanced H2 Recovery With Inherent Carbon Removal From Low Value Aqueous Biomass Oxygenate Precursors

Rational integration of chemical pathways at the molecular scale to direct thermodynamically favorable enhanced H2 production with inherent carbon removal from low-value substrates can be guided by exploring the thermodynamic limits of feasibility. The substrates of interest are biomass oxygenates that are water-soluble and uneconomical for separation from water. In this study, we investigate the thermodynamic feasibility of recovering H2 with inherent carbon removal from biomass oxygenates such as ethanol, methanol, glycerol, ethylene glycol, acetone, and acetic acid. The influence of biomass oxygenate-to-water ratios, reaction temperature of 150°C–325°C, and CaO or Ca(OH)2 as the alkalinity source on the yields of H2, CH4, CO2, and Ca-carbonate are investigated. By maintaining the fluids in the aqueous phase under pressure, energy needs associated with vaporization are circumvented. The hypothesis that enhanced alkalinity favors the preferential formation of CO (precursor for CO2 formation) over CH4 and aids the formation of calcium carbonate is investigated. The findings from these studies inform the feasibility, design of experiments, and the tuning of reaction conditions for enhanced H2 recovery with inherent carbon removal from biomass oxygenate sources.

Life Cycle Assessment of Electrodialytic Technologies to Recover Raw Materials from Mine Tailings

Currently, the development of new sustainable technologies to recover raw materials from secondary resources has shown a lack of available data on the processes and supplies involved, as well as their environmental impacts. The present research has conducted a life cycle assessment of electrodialytic (ED) technologies to improve critical raw materials recovery in the Portuguese mining industry. To critically appraise the activities from the mining sector and gather data on technical and environmental issues, three waste management scenarios were considered: (1) ED treatment with a deep eutectic solvent as an adjuvant; (2) ED treatment with simultaneous H2 recovery; and (3) ED treatment with sodium chloride as an enhancement. The data presented were based on global databases, technical reports from official sources, and peer-reviewed published experimental outcomes. The estimated results indicated that one of the constraints in applying ED technologies is energy consumption and thus the impacts are highly dependent on energy source choices. On the other hand, as a consequence of the H2 inherently produced by ED technologies, there is a direct potential for energy recovery. Therefore, considering an upscale approach of the ED reactor based on bench scale experimental results, the H2 could be reused in the ED facility or stored. Additionally, according to experimental data, 22% of the tungsten from the fine mine tailings could be recovered. Finally, the possibility to remove 63% of arsenic from mine tailings could decrease contamination risks while creating additional marketable co-products.

Hydrogen Selective SiCH Inorganic–Organic Hybrid/γ-Al2O3 Composite Membranes

Solar hydrogen production via the photoelectrochemical water-splitting reaction is attractive as one of the environmental-friendly approaches for producing H2. Since the reaction simultaneously generates H2 and O2, this method requires immediate H2 recovery from the syngas including O2 under high-humidity conditions around 50 °C. In this study, a supported mesoporous γ-Al2O3 membrane was modified with allyl-hydrido-polycarbosilane as a preceramic polymer and subsequently heat-treated in Ar to deliver a ternary SiCH organic–inorganic hybrid/γ-Al2O3 composite membrane. Relations between the polymer/hybrid conversion temperature, hydrophobicity, and H2 affinity of the polymer-derived SiCH hybrids were studied to functionalize the composite membranes as H2-selective under saturated water vapor partial pressure at 50 °C. As a result, the composite membranes synthesized at temperatures as low as 300–500 °C showed a H2 permeance of 1.0–4.3 × 10−7 mol m−2 s−1 Pa−1 with a H2/N2 selectivity of 6.0–11.3 under a mixed H2-N2 (2:1) feed gas flow. Further modification by the 120 °C-melt impregnation of low molecular weight polycarbosilane successfully improved the H2-permselectivity of the 500 °C-synthesized composite membrane by maintaining the H2 permeance combined with improved H2/N2 selectivity as 3.5 × 10−7 mol m−2 s−1 Pa−1 with 36. These results revealed a great potential of the polymer-derived SiCH hybrids as novel hydrophobic membranes for purification of solar hydrogen.

Ultra-Pure Hydrogen via Co-Valorization of Olive Mill Wastewater and Bioethanol in Pd-Membrane Reactors

Olive mill wastewater (OMW) presents high environmental impact due to the fact of its elevated organic load and toxicity, especially in Mediterranean countries. Its valorization for simultaneous pollutants degradation and green energy production is receiving great attention, mainly via steam reforming for hydrogen generation. Following previous works, the present research goes into detail about OMW valorization, particularly investigating for the first time the potential benefits of OMW–bioethanol mixtures co-reforming for ultra-pure hydrogen production in Pd-membrane reactors. In this manner, the typical large dilution of OMW and, hence, excess water can be used as a reactant for obtaining additional hydrogen from ethanol. Fresh OMW was previously conditioned by filtration and distillation processes, analyzing later the effect of pressure (1–5 bar), oxidizing conditions (N2 or air as carrier gas), gas hourly space velocity (150–1500 h−1), and alcohol concentration on the co-reforming process (5–10% v/v). In all cases, the exploitation of OMW as a source of environmentally friendly hydrogen was demonstrated, obtaining up to 30 NmL·min−1 of pure H2 at the most favorable experimental conditions. In the membrane reactor, higher pressures up to 5 bar promoted both total H2 production and pure H2 recovery due to the increase in the permeate flux despite the negative effect on reforming thermodynamics. The increase of ethanol concentration also provoked a positive effect, although not in a proportional relation. Thus, a greater effect was obtained for the increase from 5% to 7.5% v/v in comparison to the additional improvement up to 10% v/v. On the contrary, the use of oxidative conditions slightly decreased the hydrogen production rate, while the effect of gas hourly space velocity needs to be carefully analyzed due to the contrary effect on potential total H2 generation and pure H2 recovery.

Heritability Coverage of Standard Biometric Models under various Phenotypic Architectures

The behavioural scientist who requires an estimate of narrow heritability, h2, will conduct a twin study, and input the resulting estimated covariance matrices into a particular mode of estimation, the latter derived under supposition of the standard biometric model (SBM). It is now widely acknowledged that the standard biometric model can be expected to misrepresent, in manifold ways, the phenotypic (genetic) architecture of human traits. The impact of this misrepresentation on the accuracy of h2 estimation is unknown. Herein, we aimed to shed some light on this general issue, by undertaking three simulation studies. In each, the parameter recovery performance of five modes- Falconer's coefficient and the SEM models, ACDE, ADE, ACE, and AE- was investigated when they encountered a constructed, non-SBM, architecture, under a particular informational input. In study 1, the architecture was single-locus with dominance effects and genetic-environment covariance, and the input was { ΣMZ,T, ΣDZ,T, ΣMZ,A, ΣDZ,A}; in study 2, the architecture was identical to that of study 1, but the informational input was { ΣMZ,T, ΣDZ,T}; and in study 3, the architecture was multi-locus with dominance effects, genetic-environment covariance, and epistatic interactions. The informational input was {ΣMZ,T, ΣDZ,T, ΣMZ,A, ΣDZ,A}. The results suggest that conclusions regarding the coverage of h2 must be drawn conditional on a) the general class of generating architecture in play; b) specifics of the architecture’s parametric instantiations; c) the informational input into a mode of estimation; and d) the particular mode of estimation employed. In general, the results showed that more complicated the generating architecture, the poorer a mode’s h2 recovery performance. Random forest analyses furthermore revealed that, depending on the genetic architecture, h2, the dominance and locus additive parameter, and proportions of alleles were involved in complex interaction effects impacting on h2 parameter recovery performance of a mode of estimation. Data and materials: https://osf.io/aq9sx/

Membrane-Based Processes: Optimization of Hydrogen Separation by Minimization of Power, Membrane Area, and Cost

This work deals with the optimization of two-stage membrane systems for H2 separation from off-gases in hydrocarbons processing plants to simultaneously attain high values of both H2 recovery and H2 product purity. First, for a given H2 recovery level of 90%, optimizations of the total annual cost (TAC) are performed for desired H2 product purity values ranging between 0.90 and 0.95 mole fraction. One of the results showed that the contribution of the operating expenditures is more significant than the contribution of the annualized capital expenditures (approximately 62% and 38%, respectively). In addition, it was found that the optimal trade-offs existing between process variables (such as total membrane area and total electric power) depend on the specified H2 product purity level. Second, the minimization of the total power demand and the minimization of the total membrane area were performed for H2 recovery of 90% and H2 product purity of 0.90. The TAC values obtained in the first and second cases increased by 19.9% and 4.9%, respectively, with respect to that obtained by cost minimization. Finally, by analyzing and comparing the three optimal solutions, a strategy to systematically and rationally provide ‘good’ lower and upper bounds for model variables and initial guess values to solve the cost minimization problem by means of global optimization algorithms is proposed, which can be straightforward applied to other processes.