Production & Supply Chain

Electrocatalysts are capable of transforming water into hydrogen oxygen and therefore into energy in an environmentally friendly and sustainable manner. However the limitations in the research of high performance catalysts act as an obstructer in the development of using water as green energy. Here we report on a delicate method to prepare novel bimetallic metal organic framework derived electrocatalysts (C–NiCu–BDC–GO–CC) using graphene oxide (GO) modified carbon cloth as a 3D flexible and conductive substrate. The resultant electrocatalyst C–NiCu–BDC– GO–CC exhibited very low electron transfer resistance which benefited from its extremely thin 3D sponge-like morphology. Furthermore it showed excellent oxygen evolution reaction (OER) activity achieving 10 mA/cm2 at a low overpotential of 390 mV in 1 M KOH electrolyte with a remarkable durability of 10 h.

Development of efficient and affordable photocatalysts is of great significance for energy production and environmental sustainability. Transition metal chalcogenides (TMCs) with particle sizes in the 1–100 nm have been used for various applications such as photocatalysis photovoltaic and energy storage due to their quantum confinement effect optoelectronic behavior and their stability. In particular TMCs and their heterostructures have great potential as an emerging inexpensive and sustainable alternative to metal-based catalysts for hydrogen evolution. Herein the methods used for the fabrication of TMCs characterization techniques employed and the different methods of solar hydrogen production by using different TMCs as photocatalyst are reviewed. This review provides a summary of TMC photocatalysts for hydrogen production.

The study is focused on the technology and manipulation of production strategies for the cultivation of biomass from four strains of microalgae. Species of microalgae studied are: Chlorella vulgaris Dunaliella Scenedesmus quadricauda and Synechococcus spp. The effects of the rate and amount of CO₂ removal from the atmosphere and sequestration with dissolved oxygen on lipid production from accumulated biomass were studied. Also the rate of sequestration of both total and dissolved carbon was  investigated. Daily measurements of total organic and inorganic carbon sequestrated optical densities proximate analysis and kinetic parameters of the growing and cultivated microalga were monitored and carried out during the two phases of cultivation: dark and light phases. The values of maximum rate of carbon (IV) oxide removed rmax varied from 11.73 mg L ^-1 min ^-1 to 18.84 mg L ^-1 min ^-1 from Chlorella vulgaris to Synechoccocus spp. Important parameters such as biomass productivity maximum pH values obtained at cultivation lipid content of the produced biomass and the hydraulic detection time for all four strains of microalgae were considered and presented in comparison and with their individual and collective effects. The ratios of the rate of CO₂ absorption constant and the constant for the CO₂ desorption rate (k1/k2) occurred highest in Dunaliella suggesting that with a high uptake of CO₂ the algal strain is more effective in CO₂ CO2 sequestration. The best biomass producer in this study was the C. vulgaris (Xmax = 5400 mg L^-1 and Px = 35.1 mg L h ^-1) where biomass productivity is Px and the maximum cellular concentration is Xmax. C. vulgaris has the highest lipids productivity of 27% while Synechoccocus has the least (11.72%). In general biomass productivity may be inversely related; this fact may be explained by greater metabolic involvement of lipid biosynthesis. This pioneer study may be advanced further to developing models for strategic manipulation and optimisation approach in micro algal biomass cultivation.

Iron oxide has been widely used as an oxygen carrier material (OCM) for hydrogen production by chemical looping due to its favourable thermodynamic properties. In spite of this iron oxide loses much of its activity after redox cycling mainly due to sintering and agglomeration. Perovskites such as La_0.7Sr_0.3FeO_3-d (LSF731) have been suggested as potential candidate OCMs for hydrogen production due to their excellent oxygen transport properties and stability under cycling. However hydrogen production per cycle for a similar carrier weight is lower than with iron oxide. This work proposes the use of composite OCMs made of iron oxide clusters embedded in an LSF731 matrix. The perovskite matrix facilitates oxygen transport to the iron oxide clusters while preventing agglomeration. Two preparation methods mechanical mixing and a modified Pechini method were used to obtain composite materials with different iron oxide weight fractions 11 and 30 wt.%. The reactivity of these OCMs was studied in a thermogravimetric analyser. Hydrogen production and carrier stability were investigated in a microreactor over 25 redox cycles while periodically feeding carbon monoxide and water in order to produce carbon dioxide and hydrogen in separate streams. Hydrogen production was stable over 25 cycles for LSF731 and the composite OCM with 30 wt.% iron oxide produced by the modified Pechini method but iron oxide particles alone underwent a decrease in the hydrogen production with cycling. The hydrogen production during the 25th cycle was eight times higher for the composite material than for iron oxide alone and four times higher than for LSF731. The hydrogen production was therefore also higher than that expected from a simple combination of the iron oxide and LSF731 alone indicating a synergetic effect whereby the LSF731 may have a higher effective oxygen capacity when in the form of the composite material.

Our gas network is one of the best developed in the world providing safe secure affordable energy to homes and businesses across the UK.<br/><br/>To meet the biggest energy challenge of our generation – making deep cuts to carbon emissions by 2050 – it needs to embrace new technology which builds on these strengths and delivers the integrated flexible network of the future. This briefing sets out how it is already doing that. Take a look at our Gas Futures Messages booklet attached.

End-of-Life (EoL) technologies and strategies are needed to support the deployment of fuel cells and hydrogen (FCH) products. This article explores current and novel EoL technologies to recover valuable materials from the stacks of proton exchange membrane fuel cells and water electrolysers alkaline water electrolysers and solid oxide fuel cells. Current EoL technologies are mainly based on hydrometallurgical and pyro-hydrometallurgical methods for the recovery of noble metals while novel methods attempt to recover additional materials through efficient safe and cost-competitive pathways. Strengths weaknesses opportunities and threats of the reviewed EoL technologies are identified under techno-economic environmental and regulatory aspects. Beyond technologies strategies for the EoL of FCH stacks are defined mainly based on the role of manufacturers and recovery centres in the short- mid- and long-term. In this regard a dual role manufacturer/recovery centre would characterise long-term scenarios within a potential context of a well-established hydrogen economy.

Aqueous phase reforming of sorbitol was carried out in a 1.7 m long 320 mm ID microchannel reactor with a 5 mm Pt-based washcoated catalyst layer combined with nitrogen stripping. The performance of this microchannel reactor is correlated to the mass transfer properties reaction kinetics hydrogen selectivity and product distribution. Mass transfer does not affect the rate of sorbitol consumption which is limited by the kinetics of the reforming reaction. Mass transfer significantly affects the hydrogen selectivity and the product distribution. The rapid consumption of hydrogen in side reactions at the catalyst surface is prevented by a fast mass transfer of hydrogen from the catalyst site to the gas phase in the microchannel reactor. This results in a decrease of the concentration of hydrogen at the catalyst surface which was found to enhance the desired reforming reaction rate at the expense of the undesired hydrogen consuming reactions. Compared to a fixed bed reactor the selectivity to hydrogen in the microchannel reactor was increased by a factor of 2. The yield of side products (mainly C3 and heavier hydrodeoxygenated species) was suppressed while the yield of hydrogen was increased from 1.4 to 4 moles per mole of sorbitol fed.

Carbon dioxide capture and utilization (CCU) technology is a significant means by which China can achieve its ambitious carbon neutrality goal. It is necessary to explore the behavioral strategies of relevant companies in adopting CCU technology. In this paper an evolutionary game model is established in order to analyze the interaction process and evolution direction of local governments and coal-fired power plants. We develop a replicator dynamic system and analyze the stability of the system under different conditions. Based on numerical simulation we analyze the impact of key parameters on the strategies of stakeholders. The simulation results show that the unit prices of hydrogen and carbon dioxide derivatives have the most significant impact: when the unit price of hydrogen decreases to 15.9 RMB/kg or the unit price of carbon dioxide derivatives increases to 3.4 RMB/kg the evolutionary stabilization strategy of the system changes and power plants shift to adopt CCU technology. The results of this paper suggest that local governments should provide relevant support policies and incentives for CCU technology deployment as well as focusing on the synergistic development of CCU technology and renewable energy hydrogen production technology

The use of hydrogen as a clean and renewable alternative to fossil fuels requires a suite of flammability mitigating technologies particularly robust sensors for hydrogen leak detection and concentration monitoring. To this end we have developed a class of lightweight optical hydrogen sensors based on a metasurface of Pd nano-patchy particle arrays which fulfills the increasing requirements of a safe hydrogen fuel sensing system with no risk of sparking. The structure of the optical sensor is readily nano-engineered to yield extraordinarily rapid response to hydrogen gas (<3 s at 1 mbar H2) with a high degree of accuracy (<5%). By incorporating 20% Ag Au or Co the sensing performances of the Pd-alloy sensor are significantly enhanced especially for the Pd80Co20 sensor whose optical response time at 1 mbar of H2 is just ~0.85 s while preserving the excellent accuracy (<2.5%) limit of detection (2.5 ppm) and robustness against aging temperature and interfering gases. The superior performance of our sensor places it among the fastest and most sensitive optical hydrogen sensors.

The pressure swing adsorption (PSA) system is widely applied to separate and purify hydrogen from gaseous mixtures. The extended Langmuir equation fitted from the extended Langmuir-Freundlich isotherm has been used to predict the adsorption isothermal of hydrogen and methane on the zeolite 5A adsorbent bed. A six-step two-bed PSA model for hydrogen purification is developed and validated by comparing its simulation results with other works. The effects of the adsorption pressure the P/F ratio the adsorption step time and the pressure equalization time on the performance of the hydrogen purification system are studied. A four-step two-bed PSA model is taken into consideration and the six-step PSA system shows higher about 13% hydrogen recovery than the four-step PSA system. The performance of the vacuum pressure swing adsorption (VPSA) system is compared with that of the PSA system the VPSA system shows higher hydrogen purity than the PSA system. Based on the validated PSA model a dataset has been produced to train the artificial neural network (ANN) model. The effects of the number of neurons in the hidden layer and the number of samples used for training ANN model on the predicted performance of ANN model are investigated. Then the well-trained ANN model with 6 neurons in the hidden layer is applied to predict the performance of the PSA system for hydrogen purification. Multi-objective optimization of hydrogen purification system is performed based on the trained ANN model. The artificial neural network can be considered as a very effective method for predicting and optimizing the performance of the PSA system for hydrogen purification.