Techno-economic feasibility assessment of sorption enhanced gasification of municipal solid waste for hydrogen production

Waste-to-fuel coupled with carbon capture and storage is forecasted to be an effective way to mitigate the greenhouse gas emissions, reduce the waste sent to landfill and, simultaneously, reduce the dependence of fossil fuels. This study evaluated the techno-economic feasibility of sorption enhanced gasification, which involves in-situ CO₂ capture, and benchmarked it with the conventional steam gasification of municipal solid waste for H₂ production. The impact of a gate fee and tax levied on the fossil CO₂ emissions in economic feasibility was assessed. The results showed that the hydrogen production was enhanced in sorption enhanced gasification, that achieved an optimum H₂ production efficiency of 48.7% (T = 650 °C and SBR = 1.8). This was 1.0% points higher than that of the conventional steam gasification (T = 900 °C and SBR = 1.2). However, the total efficiency, which accounts for H₂ production and net power output, for sorption enhanced gasification was estimated to be 49.3% (T = 650 °C and SBR = 1.8). This was 4.4% points lower than the figure estimated for the conventional gasification (T = 900 °C and SBR = 1.2). The economic performance assessment showed that the sorption enhanced gasification will result in a significantly higher levelised cost of hydrogen (5.0 €/kg) compared to that estimated for conventional steam gasification (2.7 €/kg). The levelised cost of hydrogen can be reduced to 4.5 €/kg on an introduction of the gate fee of 40.0 €/t_MSW. The cost of CO₂ avoided was estimated to be 114.9 €/tCO₂ (no gate fee and tax levied). However, this value can be reduced to 90.1 €/tCO₂ with the introduction of an emission allowance price of 39.6 €/tCO₂. Despite better environmental performance, the capital cost of sorption enhanced gasification needs to be reduced for this technology to become competitive with mature gasification technologies.     

Economic competitiveness of compact steam methane reforming technology for on-site hydrogen supply: A Foshan case study

On-site hydrogen production through steam-methane reforming (SMR) from city gas or natural gas is believed to be a cost-effective way for hydrogen-based infrastructure due to high cost of hydrogen transportation. In recent years, there have been a lot of on-site hydrogen fueling stations under design or construction in China. This study introduces current developments and technology prospects of skid-mounted SMR hydrogen generator. Also, technical solutions and economic analysis are discussed based on China's first on-site hydrogen fueling station project in Foshan. The cost of hydrogen product from skid-mounted SMR hydrogen generator is about 23 CNY/kg with 3.24 CNY/Nm³ natural gas. If hydrogen price is 60 CNY/kg, IRR of on-site hydrogen fueling station project reaches to 10.8%. While natural gas price fall to 2.3 CNY/Nm³, the hydrogen cost can be reduced to 18 CNY/kg, and IRR can be raised to 13.1%. The conclusion is that skid-mounted SMR technology has matured and is developing towards more compact and intelligent design, and will be a promising way for hydrogen fueling infrastructures in near future.     

Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

Volatile and non-volatile compound profiles of commercial sweet pickled mango and its correlation with consumer preference

Sweet pickled mango named Ma-Muang Bao Chae-Im is a traditional preserved mango from Hat Yai, Thailand. This study investigated (I) volatile and non-volatile compound profiles of commercial Ma-Muang Bao Chae-Im and (II) their relationship to consumer preference. Untargeted metabolomics profiling was performed by gas chromatography-mass quadrupole-time of flight analysis. There were 117 volatile and 44 non-volatile compounds annotated in six commercial brands of Ma-Muang Bao Chae-Im. Furthermore, 46 volatile and 19 non-volatile compounds’ discriminant markers were found by Partial least square discriminant analysis. Among those markers, sorbic and benzoic acid were observed in several brands; moreover, the combination of both compounds altered the volatile profile, especially the ester group. Partial least square regression revealed that overall consumer liking is correlated to 1-heptanol; 1-octanol; acetoin; acetic acid, 2-phenylethyl ester; D-manitol; terpenes and terpenoids, while firmness to sucrose and L-(-)-sorbofuranose. On the other hand, most ester compounds were not related to consumer preference.     

Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

Investigation of stress fields for non-standard sized glass plates loaded by ring-on-ring

A ring-on-ring (ROR) test is a prevailing test method for evaluating the equi-biaxial strength of glass materials. However, current ROR test standards limit the strength and size of glass to prevent a nonlinear behavior. In this study, the feasibility of ROR testing for non-standard, high-strength glass, such as tempered or ion-exchanged rectangular glass is investigated. To this end, ROR simulation based on theory and experiment is conducted for thirty non-standard glasses with widths of 100–300 mm and aspect ratios of 1.0–2.0. As a result, the maximum measurable stress was about 215.6 MPa for 100 × 200 mm glass and 481.3 MPa for 300 × 600 mm glass with a 3% deviation, which is well above the strength of regular tempered glass. The main purpose of this work is to understand the range of aspect ratio of horizontal and vertical widths of a glass plate that can be evaluated by the standard ROR test.     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Eco-friendly tape casting of borosilicate glass/Al2O3 sheets for LTCC applications

This work reports the innovative development of a borosilicate glass/Al₂O₃ tape for LTCC applications using an eco-friendly aqueous tape casting slurry. Polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) were the respective dispersants, while carboxymethyl cellulose (CMC) and styrene acrylic emulsion (SA) were the respective binders. The results showed that PVP was more suitable than PAA as the dispersant for the aqueous casting slurry, and that 1.5 wt% PVP would achieve well dispersion of CABS glass/Al₂O₃ powder in the aqueous slurry. Moreover, a small amount of 2.0 wt% CMC binder could yield smooth CABS glass/Al₂O₃ tapes crack free. A high-quality CABS glass/Al₂O₃ tape with a smooth surface was made from an aqueous slurry containing 1.5 wt% PVP dispersant, 2.0 wt% CMC binder, and 2.0 wt% PEG-400 plasticizer. The density, tensile strength, and surface roughness of the green tape were 2.05 g/cm³, 0.87 MPa, and 148 nm, respectively. The resulting CABS glass/Al₂O₃ composites sintered at 875 °C exhibited a bulk density of 3.14 g/cm³, a dielectric constant of 8.09, a dielectric loss of 1.0 × 10^?3, a flexural strength of 213 MPa, a thermal expansion coefficient of 5.30 ppm/^°C, and a thermal conductivity of 3.2 W m^?1 K^?1, thus demonstrating its broad prospects in LTCC applications.     

The production of Indo-Pacific monochrome drawn glass beads in the Sasanian Empire: Insights from Xinjiang,northwest China

Indo-Pacific glass beads are produced by the drawn technique, which originates from South Asia, and their chemical compositions are unique in South and Southeast Asia. However, a small number of Indo-Pacific beads with Sassanian glass compositions are excavated in Asia and Africa after the 3rd c. CE, and their production sites in South/Southeast Asia or in the Sassanian region remain controversial. In this study, 15 drawn glass beads with various colours from Astana necropolis (ca. the 4th-8th c. CE) in Xinjiang, northwest China were investigated by using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), Scanning Electron Microscope, Raman spectroscopy and visible to near-infrared spectroscopy to characterize the production technology and origins. The results show that most Astana glass beads share similar chemical compositions with the glassware from Veh Arda?īr, a famous Sasanian site. Furthermore, Sasanian glass compositions predominate in Indo-Pacific beads in Xinjiang during the 4th-8th c. CE, while popular glass recipes in contemporary South/Southeast Asia are infrequently found; thus, it is deduced that the drawn method should have been mastered by Sasanian craftsmen. Moreover, the cobalt materials in Sasanian glass were imported from further western regions and changed over time. The popular Sasanian glass across central Eurasia reflects the trade monopoly of Sasanian in West and Central Asia, and the land glass bead trade is distinct from the contemporary maritime trade in the Indian and Pacific Oceans.     

Ammonia production using iron nitride and water as hydrogen source under mild temperature and pressure

Ammonia generation was studied in the reaction between water and nitrogen-containing iron at 323 K and atmospheric pressure. Similar to metallic Fe, the interstitial compound Fe₃N reduced water through Fe oxidation to produce hydrogen gas, while the N combined with atomic hydrogen to produce ammonia as a byproduct. The addition of carbon dioxide to this system accelerated the reaction with concomitant consumption of carbon dioxide. The promoted ammonia production upon addition of carbon dioxide can be attributed to the generation of atomic hydrogen from the redox reaction of carbonic acid and Fe, as well as removal of used Fe from the reaction system through the formation of a soluble carbonato complex. When carbonate was added to the reaction system, the production rates of ammonia and hydrogen increased further. The results here confirmed that ammonia can be synthesized from iron nitride under mild conditions by utilizing carbon dioxide.