Concentrated solar CO2 reduction in H2O vapour with >1% energy conversion efficiency.

H2O dissociation plays a crucial role in solar-driven catalytic CO2 methanation, demanding high temperature even for solar-to-chemical conversion efficiencies <1% with modest product selectivity. Herein, we report an oxygen-vacancy (Vo) rich CeO2 catalyst with single-atom Ni anchored around its surface Vo sites by replacing Ce atoms to promote H2O dissociation and achieve effective photothermal CO2 reduction under concentrated light irradiation. The high photon flux reduces the apparent activation energy for CH4 production and prevents Vo from depletion. The defects coordinated with single-atom Ni, significantly promote the capture of charges and local phonons at the Ni d-impurity orbitals, thereby inducing more effective H2O activation. The catalyst presents a CH4 yield of 192.75 µmol/cm2/h, with a solar-to-chemical efficiency of 1.14% and a selectivity ~100%. The mechanistic insights uncovered in this study should help further the development of H2O-activating catalysts for CO2 reduction and thereby expedite the practical utilization of solar-to-chemical technologies.

Integration of Co Single Atoms and Ni Clusters on Defect-Rich ZrO2 for Strong Photothermal Coupling Boosts Photocatalytic CO2 Reduction.

We report a solvothermal method for the synthesis of an oxygen vacancy-enriched ZrO2 photocatalyst with Co single atoms and Ni clusters immobilized on the surface. This catalyst presents superior performance for the reduction of CO2 in H2O vapor, with a CO yield reaching 663.84 µmol g-1 h-1 and a selectivity of 99.52%. The total solar-to-chemical energy conversion efficiency is up to 0.372‰, which is among the highest reported values. The success, on one hand, depends on the Co single atoms and Ni clusters for both extended spectrum absorption and serving as dual-active centers for CO2 reduction and H2O dissociation, respectively; on the other hand, this is attributed to the enhanced photoelectric and thermal effect induced by concentrated solar irradiation. We demonstrate that an intermediate impurity state is formed by the hybridization of the d-orbital of single-atom Co with the molecular orbital of H2O, enabling visible-light-driven excitation over the catalyst. In addition, Ni clusters play a crucial role in altering the adsorption configuration of CO2, with the localized surface plasmon resonance effect enhancing the activation and dissociation of CO2 induced by visible-near-infrared light. This study provides valuable insights into the synergistic effect of the dual cocatalyst toward both efficient photothermal coupling and surface redox reactions for solar CO2 reduction.

Mitigating ash-related alkali and heavy metals emissions in rotary kiln through oxygen-carrier-aided combustion of waste.

Rotary kiln (RK) incineration technology gains prominence in waste management, aiming to reduce pollution, recover energy, and minimize waste. Oxygen-carrier (OC)-aided incineration of waste in the RK demonstrates notable benefits by enhancing oxygen distribution uniformity and facilitating fuel conversion. However, the effects of OC on ash-related alkali and heavy metals during waste incineration in the RK remain unknown. In this study, manganese ore and ilmenite as OCs are introduced into RK during waste combustion, focusing on their effects on the bottom ashes and the behavior of alkali and heavy metals. Results show that manganese ore exhibits a decreasing reactivity due to oxygen depletion during the conversion from Mn2O3 to Mn3O4, while ilmenite maintains good reactivity due to sustained enrichment of Fe2O3 on the particles even after multiple cycles in RK. The porous structure on the surface of OCs particles verifies the cyclic reaction involving oxidation by air and reduction by fuel as OCs move between the active and passive layers of the bed. The porous OCs particles offer abundant adsorption sites for K from the gaseous phase, with surface-deposited K migrating into the particles and enhancing the OCs' capacity for K adsorption. Adding OCs promotes the formation of stable, less volatile compounds of heavy metals (As, Cr, Pb, and Zn) and enhances their retention in bottom ash while ensuring the leaching toxicity remains below Chinese national standard limits. This study enhances the understanding of OCs in incineration, guiding vital references for waste management practices and environmental sustainability.

An acetate electrolyte for enhanced pseudocapacitve capacity in aqueous ammonium ion batteries.

Ammonium ion batteries are promising for energy storage with the merits of low cost, inherent security, environmental friendliness, and excellent electrochemical properties. Unfortunately, the lack of anode materials restricts their development. Herein, we utilized density functional theory calculations to explore the V2CTx MXene as a promising anode with a low working potential. V2CTx MXene demonstrates pseudocapacitive behavior for ammonium ion storage, delivering a high specific capacity of 115.9 mAh g-1 at 1 A g-1 and excellent capacity retention of 100% after 5000 cycles at 5 A g-1. In-situ electrochemical quartz crystal microbalance measurement verifies a two-step electrochemical process of this unique pseudocapacitive storage behavior in the ammonium acetate electrolyte. Theoretical simulation reveals reversible electron transfer reactions with [NH4+(HAc)3]···O coordination bonds, resulting in a superior ammonium ion storage capacity. The generality of this acetate ion enhancement effect is also confirmed in the MoS2-based ammonium-ion battery system. These findings open a new door to realizing high capacity on ammonium ion storage through acetate ion enhancement, breaking the capacity limitations of both Faradaic and non-Faradaic energy storage.

Evaluating combustion kinetics and quantifying fuel-N conversion tendency of shoe manufacturing waste.

Combustion is an effective and cost-efficient thermochemical conversion method for solid waste, showing promise for the resource utilization of shoe manufacturing waste (SMW). However, SMW is generally composed of different components, which can lead to unstable combustion and excessive pollutant emissions, especially NOx. To date, combustion characteristics, reaction mechanism and fuel nitrogen (fuel-N) conversion of different SMW components remain unclear. In this work, the combustion behavior of typical SMW components combustion was investigated using Thermogravimetric coupled with Fourier transform infrared spectrum (TG-FTIR). A simplified single-step reaction mechanism was proposed according to the temperature interval to estimate reaction mechanism of SMW. Additionally, the relationship between fuel-N conversion tendency and fuel properties was established. The results indicate that the values for the comprehensive combustion performance index (S) and flammability index (C) range from 1.65 to 0.44 and 3.98 to 1.37, respectively. This demonstrates the significant variability in combustion behavior among different SMW components. Cardboard, leather and sponge have higher values of S and C, suggesting a better ignition characteristic and a stable combustion process. During the combustion of SMW, nitrogen oxides (NO and N2O) are the main nitrogen-containing compounds in the flue gases, with NO being the major contributor, accounting for over 82.97 % of the nitrogen oxides. NO has a negative correlation with nitrogen content, but it is opposite for N2O, HCN and NH3. Furthermore, the conversion of NO, N2O and NH3 is proportional to logarithmic values of O/N, while its conversion to HCN is proportional to logarithmic values of VM/N. These findings facilitate the prediction of the fuel-N conversion of solid waste combustion. This work might shed light on combustion optimization and in-situ pollutant emission control in solid waste combustion.

Leveraging Machine Learning for Metal-Organic Frameworks: A Perspective.

Metal-organic frameworks (MOFs) have attracted tremendous interest because of their tunable structures, functionalities, and physiochemical properties. The nearly infinite combinations of metal nodes and organic linkers have led to the synthesis of over 100,000 experimental MOFs and the construction of millions of hypothetical counterparts. It is intractable to identify the best candidates in the immense chemical space of MOFs for applications via conventional trial-to-error experiments or brute-force simulations. Over the past several years, machine learning (ML) has substantially transformed the way of MOF discovery, design, and synthesis. Driven by the abundant data from experiments or simulations, ML can not only efficiently and accurately predict MOF properties but also quantitatively derive structure-property relationships for rational design and screening. In this Perspective, we summarize recent achievements in leveraging ML for MOFs from the aspects of data acquisition, featurization, model training, and applications. Then, current challenges and new opportunities are discussed for the future exploration of ML to accelerate the development of new MOFs in this vibrant field.

Human health risk identification of petrochemical sites based on extreme gradient boosting.

Petrochemical industry is a key industry of soil pollution, which presents great effects on human health and the ecological environment. It is of great significance to achieve rapid, economic and efficient health risk identification for petrochemical industry in China. In this work, an efficient method was developed based on extreme gradient boosting (XGBoost) algorithm for human health risk identification, which is different from the traditional health risk assessment with complicated procedures. In this methodology, an index system of 13 indicators was established from the perspective of "sources - pathways - receptors" for risk identification. The 10-fold cross validation was used to assess the generalization performance, and the accuracy, precision and recall were employed to evaluate the performance of the algorithms. Wilcoxon signed-rank test was conducted to analyze the differences between XGBoost and other models for statistical support. The results showed that XGBoost significantly presented a better performance for health risk identification over multilayer perceptron neural network with error backpropagation training (BPNN), support vector machine (SVM), gradient boosting decision tree (GBDT) and light gradient boosting machine (LightGBM), with an accuracy of 0.783. The most important features contributing to the risk identification were determined with the sequence of site location (in the industrial zone or not), site planning and production period. Great attention should be given to the petrochemical sites that are not located in the industrial zone with long production period and sensitive receptors in the health risk identification. This method has important reference significance for relevant departments to carry out soil contamination screening and health risk assessment of petrochemical sites.

Accurate Control of Cage-Like CaO Hollow Microspheres for Enhanced CO2 Capture in Calcium Looping via a Template-Assisted Synthesis Approach.

Herein we report the development of synthetic CaO-based sorbents for enhanced CO2 capture in calcium looping via a template-assisted synthesis approach, where carbonaceous spheres (CSs) derived from hydrothermal reaction of starch are used as the templates. Cage-like CaO hollow microspheres are successfully synthesized only using urea as the precipitant, and the formation mechanism of this unique hollow microsphere structure is discussed deeply. Moreover, cage-like CaO hollow microspheres possess an initial carbonation conversion of 98.2% and 82.5% under a mild and harsh conditions, respectively. After the 15 cycles, cage-like CaO hollow microspheres still possess a carbonation value of 49.2% and 39.7% under the corresponding conditions, exceeding the reference limestone by 85.7% and 148.1%, respectively. Two kinetic models are used to explore the mechanism of carbonation reaction for cage-like CaO hollow microspheres, which are subsequently proved to be feasible for analysis of chemical-controlled stage and diffusion-controlled stage in the carbonation process. It is found the unique hollow microsphere structure can significantly reduce the activation energy of carbonation reaction according to the kinetic calculation. Furthermore, the energy and raw material consumptions related to the synthesis of cage-like CaO hollow microspheres are analyzed by the life cycle assessment (LCA) method.

Effect of SO2 and steam on CO2 capture performance of biomass-templated calcium aluminate pellets.

Four types of synthetic sorbents were developed for high-temperature post-combustion calcium looping CO2 capture using Longcal limestone. Pellets were prepared with: lime and cement (LC); lime and flour (LF); lime, cement and flour (LCF); and lime, cement and flour doped with seawater (LCFSW). Flour was used as a templating material. All samples underwent 20 cycles in a TGA under two different calcination conditions. Moreover, the prepared sorbents were tested for 10 carbonation/calcination cycles in a 68 mm-internal-diameter bubbling fluidized bed (BFB) in three environments: with no sulphur and no steam; in the presence of sulphur; and with steam. When compared to limestone, all the synthetic sorbents exhibited enhanced CO2 capture performance in the BFB experiments, with the exception of the sample doped with seawater. In the BFB tests, the addition of cement binder during the pelletisation process resulted in the increase of CO2 capture capacity from 0.08 g CO2 per g sorbent (LF) to 0.15 g CO2 per g sorbent (LCF) by the 10th cycle. The CO2 uptake in the presence of SO2 dramatically declined by the 10th cycle; for example, from 0.22 g CO2 per g sorbent to 0.05 g CO2 per g sorbent in the case of the untemplated material (LC). However, as expected all samples showed improved performance in the presence of steam, and the decay of reactivity during the cycles was less pronounced. Nevertheless, in the BFB environment, the templated pellets showed poorer CO2 capture performance. This is presumably because of material loss due to attrition under the FB conditions. By contrast, the templated materials performed better than untemplated materials under TGA conditions. This indicates that the reduction of attrition is critical when employing templated materials in realistic systems with FB reactors.

Solid-gaseous phase transformation of elemental contaminants during the gasification of biomass.

Disposal of plant biomass removed from heavy metal contaminated land via gasification achieves significant volume reduction and can recover energy. However, these biomass often contain high concentrations of heavy metals leading to hot-corrosion of gasification facilities and toxic gaseous emissions. Therefore, it is of significant interest to gain a further understanding of the solid-gas phase transition of metal(loid)s during gasification. Detailed elemental analyses (C, H, O, N and key metal/metalloid elements) were performed on five plant species collected from a contaminated site. Using multi-phase equilibria modelling software (MTDATA), the analytical data allows modelling of the solid/gas transformation of metal(loid)s during gasification. Thermodynamic modelling based on chemical equilibrium calculations was carried out in this study to predict the fate of metal(loid) elements during typical gasification conditions and to show how these are influenced by metal(loid) composition in the biomass and operational conditions. As, Cd, Zn and Pb tend to transform to their gaseous forms at relatively low temperatures (<1000°C). Ni, Cu, Mn and Co converts to gaseous forms within the typical gasification temperature range of 1000-1200°C. Whereas Cr, Al, Fe and Mg remain in solid phase at higher temperatures (>1200°C). Simulation of pressurised gasification conditions shows that higher pressures increase the temperature at which solid-to-gaseous phase transformations takes place.

NO formation during agricultural straw combustion.

NO formation during combustion of four typical kinds of straw (wheat straw, rice straw, cotton stalk and corn stalk) which belong to soft straw and hard straw was studied in a tubular quartz fixed bed reactor under conditions relevant to grate boiler combustion. Regarding the real situation in biomass fired power plants in China, NO formation from blended straw combustion was also investigated. Nitrogen transfer during blended straw pyrolysis was performed using a thermogravimetric analyzer (TGA) coupled with a Fourier transform infrared (FTIR) spectrometer. The results show that NO conversion for the four straws during combustion is distinctive. Over 70% fuel-N converts into NO for cotton stalk, while only 37% for wheat straw under the same condition. When wheat straw and cotton stalk were mixed, N-NO conversion increases. The limestone addition promotes NO emission during cotton stalk combustion. The presence of SO(2) in atmosphere suppresses NO formation from straw combustion.