High-Throughput Screening of Sulfur-Resistant Catalysts for Steam Methane Reforming Using Machine Learning and Microkinetic Modeling.

The catalytic activity of bimetallic catalysts for the steam methane reforming (SMR) reaction was extensively studied previously. However, the performance of these materials in the presence of sulfur-containing species is yet to be investigated. In this study, we propose a novel process aided by machine learning (ML) and microkinetic modeling for the rapid screening of sulfur-resistant bimetallic catalysts. First, various ML models were developed to predict atomic adsorption energies (C, H, O, and S) on bimetallic surfaces. Easily accessible physical and chemical properties of the metals and adsorbates were used as input features. The Ensemble learning, artificial neural network, and support vector regression models achieved the best performance with R2 values of 0.74, 0.71, and 0.70, respectively. A microkinetic model was then built based on the elementary steps of the SMR reaction. Finally, the microkinetic model, together with the atomic adsorption energies predicted by the Ensemble model, were used to screen over 500 bimetallic materials. Four Ge-based alloys (Ge3Cu1, Ge3Ni1, Ge3Co1, and Ge3Fe1) and the Ni3Cu1 alloy were identified as promising and cost-effective sulfur-resistant catalysts.

A country-level assessment of the deployment potential of greenhouse gas removal technologies.

The deployment of greenhouse gas removal (GGR) technologies has been identified as an indispensable option in limiting global warming to 1.5 °C by the end of the century. Despite this, many countries are yet to include and promote this option in their long-term plans owing to factors such as uncertainty in technical potential, deployment feasibility and economic impact. This work presents a country-level assessment of the deployment potential of five GGR technologies, including forestation, enhanced weathering (EW), direct air carbon capture and storage (DACCS), bioenergy with carbon capture and storage (BECCS) and biochar. Using a multi criteria decision analysis (MCDA) approach consisting of bio-geophysical and techno-economic factors, priority regions for the deployment of these GGR technologies were identified. The extent of carbon dioxide removable by 2100 via these technologies was also estimated for each of the 182 countries considered. While the obtained results indicate the need for regional cooperation among countries, it also provides useful evidence on the need for countries to include and prioritise GGR technologies in their revised nationally determined contributions (NDCs).

Prediction of Combined Sorbent and Catalyst Materials for SE-SMR, Using QSPR and Multitask Learning.

The process of sorption enhanced steam methane reforming (SE-SMR) is an emerging technology for the production of low carbon hydrogen. The development of a suitable catalytic material, as well as a CO2 adsorbent with high capture capacity, has slowed the upscaling of this process to date. In this study, to aid the development of a combined sorbent catalyst material (CSCM) for SE-SMR, a novel approach involving quantitative structure-property relationship analysis (QSPR) has been proposed. Through data-mining, two databases have been developed for the prediction of the last cycle capacity (gCO2 /gsorbent) and methane conversion (%). Multitask learning (MTL) was applied for the prediction of CSCM properties. Patterns in the data of this study have also yielded further insights; colored scatter plots were able to show certain patterns in the input data, as well as suggestions on how to develop an optimal material. With the results from the actual vs predicted plots collated, raw materials and synthesis conditions were proposed that could lead to the development of a CSCM that has good performance with respect to both the last cycle capacity and the methane conversion.

Assessment of optimal conditions for the performance of greenhouse gas removal methods.

In this study, a comparative literature-based assessment of the impact of operational factors such as climatic condition, vegetation type, availability of land, water, energy and biomass, management practices, cost and soil characteristics was carried out on six greenhouse gas removal (GGR) methods. These methods which include forestation, enhanced weathering (EW), soil carbon sequestration (SCS), biochar, direct air capture with carbon storage (DACCS) and bioenergy with carbon capture and storage (BECCS) were accessed with the aim of identifying the conditions and requirements necessary for their optimum performance. The extent of influence of these factors on the performance of the various GGR methods was discussed and quantified on a scale of 0-5. The key conditions necessary for optimum performance were identified with forestation, EW, SCS and biochar found to be best deployed within the tropical and temperate climatic zones. The CCS technologies (BECCS and DACCS) which have been largely projected as major contributors to the attainment of the emission mitigation targets were found to have a larger locational flexibility. However, the need for cost optimal siting of the CCS plant is necessary and dependent on the presence of appropriate storage facilities, preferably geological. The need for global and regional cooperation as well as some current efforts at accelerating the development and deployment of these GGR methods were also highlighted.

Green production of a novel sorbent from kaolin for capturing gaseous PbCl2 in a furnace.

The pollution of semi-volatile heavy metals is one of the key environmental risks for municipal solid waste incineration, and in-situ adsorption of metals within the furnace by mineral sorbents such as kaolin has been demonstrated as a promising emission control method. To lessen the consumption of sorbent, a novel material of amorphous silicate was produced from kaolin through pressurised hydrothermal treatment. Its performance of gaseous PbCl2 capture was tested in a fixed bed furnace and compared with unmodified kaolin and metakaolin. With increasing temperature, the adsorption rates for all sorbents declined due to higher saturated vapour pressure, while the partitions of residual form lead increased which indicated higher stability of heavy metals in the sorbent because of melting effect. The new sorbent with a larger surface area and reformed structure presented 26% more adsorption efficiency than raw kaolin at 900 °C, and increasing the modification pressure improved these properties. Additionally, the production of this high-temperature sorbent was relatively inexpensive, required little thermal energy and no chemicals to produce and no waste effluent was generated, thus being much cleaner than other modification methods.

Hydrogen Production by Sorption Enhanced Steam Reforming (SESR) of Biomass in a Fluidised-Bed Reactor Using Combined Multifunctional Particles.

The performance of combined CO2-sorbent/catalyst particles for sorption enhanced steam reforming (SESR), prepared via a simple mechanical mixing protocol, was studied using a spout-fluidised bed reactor capable of continuous solid fuel (biomass) feeding. The influence of particle size (300⁻500 and 710⁻1000 µm), CaO loading (60⁻100 wt %), Ni-loading (10⁻40 wt %) and presence of dicalcium silicate support (22.6 wt %) on SESR process performance were investigated. The combined particles were characterised by their density, porosity and CO2 carrying capacity with the analysis by thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET), Barrett-Joyner-Halenda (BJH) and mercury intrusion porosimetry (MIP). All experiments were conducted with continuous oak biomass feeding at a rate of 0.9 g/min ± 10%, and the reactor was operated at 660 ± 5 °C, 1 atm and 20 ± 2 vol % steam which corresponds to a steam-to-carbon ratio of 1.2:1. Unsupported combined particles containing 21.0 wt % Ni and 79 wt % CaO were the best performing sorbent/catalyst particle screened in this study, when accounting for the cost of Ni and the improvement in H2 produced by high Ni content particles. SESR tests with these combined particles produced 61 mmol H2/gbiomass (122 g H2/kgbiomass) at a purity of 61 vol %. Significant coke formation within the feeding tube and on the surfaces of the particles was observed which was attributed to the low steam to carbon ratio utilised.