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A thermodynamic analysis of the reactions for the conversion of dimethyl ether into valuable products of the gas and oil industry and of propylene, formaldehyde, and 1,3-butadiene in particular was carried out. The temperature dependence of the equilibrium composition in the reaction for the production of 1,3-butadiene from dimethyl ether was determined. Calculation of the temperature dependence of the equilibrium composition in the reaction of propylene with formaldehyde with the formation of 1,3-dioxane, 1,3-butanediol, and 2-buten-1-ol showed that the main product at equilibrium is 2-buten-1-ol.

Petrochemists have recently paid special attention to the production of valuable chemical products based on dimethyl ether (DME), which is one of the main products of the Fischer-Tropsch synthesis of oxygenates from syngas.

In [1] the mechanism of the reaction for the synthesis of olefns from methanol and DME at zeolite catalysts is considered, and various mechanisms such as isomerization and synchronous mechanisms for the formation of C–C bonds in the transformation of DME as well as the role of catalysts and temperatures in these reactions are discussed. In [2] kinetic aspects of the synthesis of olefns from methanol and DME at zeolite catalysts were examined.

The dependence of the activity of zeolite MFI in the transformations of DME into hydrocarbons on the spectral and textural characteristics and acidity was studied in [3]. Comparative results obtained during the synthesis of C5+ hydrocarbons are presented. It was established that high selectivity in the hydrocarbons of the gasoline fraction is achieved with the use of a catalyst based on a sample of zeolite MFI, for which in the infrared diffuse refection spectra there are bands characteristic of the acid centers of H3 O+ .

It is interesting to note the results of studies [4], which examine the treatment of DME with associated petroleum gas in a mixture of synthetic hydrocarbons. It was established here that it is possible to obtain hydrocarbons direct from DME in a singlestage process. The presence in the vapor–gas mixture of such components as hydrogen, carbon dioxide, and water ensures high stability of the catalytic system. In [5-11] on the basis of data on the state of the intermediates formed from DME on the surface of the heterogeneous catalysts some catalytic reactions with the participation of DME were examined: methylation, ethanol synthesis, partial oxidation with the production of a series of compounds.

Highlights

Abstract

Graphical abstract

Abbreviations

Keywords

1. Introduction

2. State of the art

3. Technological opportunities and challenges

4. Educational implications

5. Economic and social challenges

6. Conclusion and future directions

Declaration of Competing Interest

Acknowledgements

References

Abstract

With the advent of digitalization and industry 4.0, education in chemical and biochemical engineering has undergone significant revamping over the last two decades. However, undergraduate students sometimes do lack industrial exposure and are unable to visualise the complexity of actual process plants. Thereby, students might graduate without adequate professional hands-on experience. Similarly, in the process industry, operator training-simulators are widely used for the training of new and skilled operators. However, conventional training-simulators often fail to simulate reality and do not provide the user with the opportunity to experience unexpected and hazardous scenarios. In these regards, virtual reality appears to be a promising technology that can cater to the needs of both academia and industry. This paper discusses the opportunities and challenges for the incorporation of virtual reality into chemical and biochemical engineering education with an emphasis on the fundamental areas of technology, pedagogy and socio-economics. The paper emphasises the need for augmenting virtual reality interfaces with mathematical models to develop advanced immersive learning applications. Further, the paper stresses upon the need for novel educational impact assessment methodologies for the evaluation of virtual-reality-based learning. Finally, an ongoing case study application is presented to briefly discuss the social and economic implications, and to identify the bottlenecks involved in the adoption of virtual reality tools across chemical and biochemical engineering education.

1. Introduction

With rapid advances in technology, digital solutions are being widely embraced for teaching and for learning purposes (Quintero et al., 2019; Radianti et al., 2020). This includes the use of online learning platforms, interactive digital applications, and collaborative environments in education. Furthermore, the easy availability of portable digital devices including notebooks and smartphones fostered the digital embracement for education. Recently, immersive virtual environments are also being considered as a viable option for education and training owing to the availability, affordability, and rapid advancements in these technologies (Akkoyun, 2017; Jensen and Konradsen, 2018).

In academia, growing student numbers combined with the limited availability of physical resources is leading educational institutions to explore novel teaching alternatives that are, primarily, cost-effective in nature. Moreover, force-majeure situations such as the COVID-19 pandemic advocates for more educational robustness and distance learning options. Similarly, in industry, with increased automation and complexity of modern process plants, advanced training methods are becoming more desirable for the effective training of operators. In this regard, three-dimensional (3D) virtual reality environments, similar to those being used in the gaming and film industry, can be effectively utilised to generate learning environments (Schofield, 2012). Even though virtual reality is not a new technology, recent advancements have aroused increased interest among scholars (Akbulut et al., 2018). With the arrival of low-budget head-mounted displays (HMDs), immersive virtual environments are becoming more accessible for the purpose of education (Jensen and Konradsen, 2018).

Highlights

Abstract

Graphical abstract

Keywords

Nomenclature

1. Introduction

2. Why focusing on LIB risk management and safety issues?

2. Contextualising the relative levels of risk of electric vehicle LIBs

3. Potential failure mechanisms of LIBs

4. Origins and categorisation of risks associated with LIBs

5. End of Life LIB incidents

6. Safety measures, regulatory gaps and discussions

7. Conclusions

Credit author statement

Declaration of competing interest

Acknowledgments

References

Abstract

Lithium-ion Batteries (LIB) are an essential facilitator of the decarbonisation of the transport and energy system, and their high energy densities represent a major technological achievement and resource for humankind. In this research, it has been argued that LIBs have penetrated everyday life faster than our understanding of the risks and challenges associated with them. The current safety standards in the car industry have benefited from over 130 years of evolution and refinement, and Electric Vehicle (EV) and LIB are comparably in their infancy. This paper considers some of the issues of safety over the life cycle of batteries, including: the End of Life disposal of batteries, their potential reuse in a second-life application (e.g. in Battery Energy Storage Systems), recycling and unscheduled End of Life (i.e. accidents). The failure mechanism and reports from a range of global case studies, scenarios and incidents are described to infer potential safety issues and highlight lessons that can be learned. Therefore, the safety risks of LIBs were categorised, and the regularity requirements to create and inform a wider debate on the general safety of LIBs were discussed. From the analysis, a range of gaps in current approaches have been identified and the risk management systems was discussed. Ultimately, it is concluded that robust educational and legal processes are needed to understand and manage the risks for first responders and the public at large to ensure a safe and beneficial transition to low carbon transportation and energy system.

1. Introduction

Lithium-ion batteries (LIBs) have penetrated deeply into society, finding a wide range of applications in personal electronic devices since their discovery and development in the 1980s and 90s, and more recently in larger energy systems for traction and energy storage. This is mainly owing to the unique characteristics of LIB technology, i.e. high energy densities, high voltage, good stability, low self-discharge rate, long-life cycle and availability of a wide range of chemistries with diverse electrode designs [1,2]. LIBs are incorporated into ever widening application areas and are to be found at scales as diverse as their usages. This is evidenced by the growth in the uptake of LIBs having increased eight fold between 2010 and 2018 to 160 GWh [3] and the steady increase in annual sales of LIBs which are predicted to be upwards of 4 TWh by 2040 [4]. In the UK, it is forecast that the number of LIBs reaching the end of their life from automotive applications would have reached approximately 75,000 units, or 28,000 t by 2025 [5]. The advent of lithium-ion technology and the paradigm shift in the energy and power density capabilities that it represents, are perceived as the enabling technology for an extremely broad range of energy storage applications. Accordingly, LIBs are increasingly recognised as essential and integral to enable the large-scale temporary storage of electrical energy from renewable energy sources.

Highlights

Abstract

Keywords

Nomenclature

1. Introduction

2. The proposed SA-MODDE algorithm

3. Numerical experiments

4. Chemical engineering processes optimization

5. Conclusion

CRediT authorship contribution statement

Declaration of Competing Interest

Appendix A. Supplementary data

References

Abstract

This paper proposes a new multi-objective dynamic differential evolution algorithm with parameter self-adaptive strategies, named SA-MODDE. All components of the algorithm are synergically designed to reach its full potential, containing parental selection, mutation strategy, parameter setting, survival selection, constraint handling, and termination criteria. The improvement measures emphasize exploiting Pareto dominance information more efficiently. Particularly, parameter adaptation schemes are introduced based on both prior knowledges of current individual and feedback information on previous promising solutions, and their effectiveness is validated by comparison with three fixed-parameter combinations. Extensive numerical tests are conducted on multiple test suites with five state-of-the-art peer competitors. The statistical results demonstrated that the SA-MODDE exhibits good proximity and diversity in dealing with benchmark functions with various characteristics. Three industrial (bio)chemical processes, including two optimal control and one reformulated constrained tri-objective, are investigated to show the feasibility and robustness of the SA-MODDE.

1. Introduction

Engineering problems always require the simultaneous optimization of several competing objectives of interests. So far, multi-objective optimization (MOO) has been an active research field in process systems engineering [1,2]. Particularly, various multi-objective evolutionary algorithms (MOEAs), such as NSGAII, GDE3, and MOPSO, have been widely used to solve both academic and industrial MOO problems [3–5]. Usually, MOEAs have two main advantages: (1) As many diverse non-dominated solutions as possible can be found in a single run; (2) Various types of MOO problems can be handled without assumptions on objective functions and their mathematical characteristics [6].

The algorithm structure and search operator jointly affect the performance of MOEAs. The algorithm structure can be classified into two main categories: Pareto-based [3,7] and decompositionbased [8,9]. The former provides detailed Pareto dominance information of the population to facilitate individual comparison. The latter decomposes MOO problems into a set of scalar aggregation subproblems, each of which is optimized using the current information from neighboring subproblems. The two methods have their own advantages on different types of problems and are considered to be evenly matched [10]. In terms of search operator, differential evolution (DE) is simple to implement with only a few control parameters, i.e., scale factor (F ) and crossover rate (CR). Except for multi-objective DE (MODE) algorithms, many classic MOEAs also replaced the original evolutionary operators with DE and their performance was significantly enhanced, such as NSGAII-DE, SPEA2-DE, IBEA-DE, and MOEA/D-DE [11,12]. Through updates by dynamic population rather than generation to generation, Qing [13] presented the dynamic DE (DDE) operator, superior in efficiency, robustness, and storage requirements to the conventional DE. That is, each new individual that performs better than or similar to the corresponding old counterpart will immediately participate in the current population to provide information for subsequent evolution. This makes DDE more responsive to changes in population status. Despite of researches on multi-objective DDE (MODDE) algorithms [14,15], it is still very inadequate compared to MODE. Herein, we propose several improvement measures on the MODDE under Pareto-based structure. For convenience, the background of MOO problems and DDE operators are given in Supplementary Materials.

Highlights

Abstract

Graphical abstract

Keywords

1. Introduction

2. Methods

3. Results and discussion

4. Conclusion

Declaration of Competing Interest

Acknowledgements

Appendix A. Supplementary data

References

Abstract

In this work, we fabricate perovskite-type Ca1−x−yLaxSryMnO3 thermoelectric materials using co-precipitation method, followed by cold pressing and hot sintering. The La/Sr dual doping modifies chemical composition and bonding properties of CaMnO3, resulting in improved electrical transport properties with tunable carrier concentration, carrier mobility and effective mass. Meanwhile, the phonon transport properties are also influenced, reflected by the reduced lattice thermal conductivity of Ca1−x−yLaxSryMnO3. As a result, Ca0.94La0.02Sr0.04MnO3 shows significantly enhanced power factor up to 374 μW·m−1·K−2 and figure of merit up to ~0.22 at 973 K, which is ~144% higher than those of pristine CaMnO3. This study rationalizes a potential strategy to improve the thermoelectric performance of CaMnO3-based materials.

1. Introduction

The increasing consumption of fossil fuels and the deteriorating environmental pollution have driven researchers to explore alternative and sustainable energy-supply technologies [1-3]. Thermoelectric materials and devices enable the direct conversion between heat and electricity [4], showing great potential in improving energy efficiency and recovering waste heat from diverse heat sources. Their conversion efficiency is dominated by the dimensionless figure-of-merit (zT) [5-8], defined as zT = S 2σT/κ, where S, σ, κ and T are the Seebeck coefficient, electrical conductivity, thermal conductivity and absolute temperature, respectively. Accordingly, an ideal thermoelectric material relies on a large power factor (PF = S2σ) and a low κ, while PF and κ are strongly coupled by the carrier concentration (n).

Currently, thermoelectric materials with zT values exceeding 1 have been extensively obtained [3, 9-15]. However, the high cost, instability in air atmosphere or toxicity may limit their applications [16-18]. Oxides-based thermoelectric ceramics with advantages of chemical and structural stability, low cost and low toxicity have been regarded as potential thermoelectric materials for applications above 800 K [19, 20]. As one of the promising candidates, n-type perovskite CaMnO3 with intrinsically high |S| (550 μV K-1 at room temperature) has received much interest due to its unique structure, magnetic and topological properties [21-30]. However, its high electrical resistivity () and κ lead to low zT values. Previous studies have revealed that the substitutions of trivalent rare earth elements such as La, Ce or Pr on the Ca-site of CaMnO3 can simultaneously reduce  and κ, along with a moderate decrease of |S| [31- 33]. Moreover, theoretical calculations [34, 35] indicate that Sr-doping can contribute to larger effective mass of carriers (m*), enhanced density of states (DOS) near the Fermi level, and complicated phonon frequency modes, which is essential to optimize the thermoelectric parameters of CaMnO3. Therefore, applying a dual doping strategy of rare earth elements and Sr on CaMnO3 could be a key to achieve synergistically improved thermoelectric properties.

Highlights

Abstract

Keywords

1. Introduction

2. Digitalization in the Chemical Industry

3. The thread of automation

4. Digitization in the chemical engineering profession

5. Learning & education

6. Conclusion

Declaration of Competing Interest

Acknowledgements

References

Abstract

This paper highlights the importance of digitalization in chemical engineering industries, in the frame of Industry 4.0, and the consequences on the employability and profession of chemical engineers. Training content must necessarily evolve to meet industry expectations and maintain the level of innovation required to meet the challenges of the future such as competitiveness, global warming, or depletion of resources. Higher Education Institutions must evolve, and digitalization also makes it possible to provide new training methods and tools that will help the teachers to face these challenges.

1. Introduction

Digitization transforms the Chemical Industry rapidly across its entire value chain. Early examples of what is nowadays often called “Industry 4.0” were predictive maintenance and process automation. In 2017 Cefic recognized a rapid transformation of the entire horizontal value chain of the chemical industry due to digitalization, see (Winter, 2017). Today one experiences end-to-end supply chain integration and digitization of customer experience. Advanced analytics, often named “big data”, sets out to change the way the engineering profession views the information it gathers and the interfaces a Chemical Engineer must manage.

Digitization, Digitalization, and Digital Transformation are often used almost interchangeably. While they are certainly similar in their dependence on computer power, they are distinguishable variations in the use of digital tools in the economic environment. “Digitization”, as the most basic of the three concepts, simply refers to doing something in the digital space which has previously been done without computers. Examples are digital photography initiated in 1989 by Kodak’s first digital camera, which replaces the paper photo by a digitally stored image or the transfer of a paper-based process from an analogue to a digital format. “Digitalization” requires a digitized format and adds (business) operations which are only available since the digital data is available. Examples might be the instantaneous access to e-mail via a smart watch introduced by Apple in 2016. True “Digital Transformation” changes the business behaviour and requires digitalization en route to a different product. Examples may be found in the information business where not only the form of delivery has changed, but also archiving and search are now part of the business offering of the information provider.

This paper is based on a presentation given at the joint Education Session of the 12th EUROPEAN CONGRESS OF CHEMICAL ENGINEERING and the 5th EUROPEAN CONGRESS OF APPLIED BIOTECHNOLOGY in Florence, Italy. It looks at examples of digitization and digitalization in the Chemical Industry, the thread of automation, what digitalization changes in the chemical engineering profession and how it impacts learning and education.

Highlights

Abstract

Keywords

1. Introduction

2. Methods

3. Results

4. Discussion and conclusions

CRediT authorship contribution statement

Declaration of Competing Interest

References

Abstract

Mathematical models are useful in epidemiology to understand COVID-19 contagion dynamics. We aim to demonstrate the effectiveness of parameter regression methods to calibrate an established epidemiological model describing infection rates subject to active, varying non-pharmaceutical interventions (NPIs). We assess the potential of established chemical engineering modelling principles and practice applied to epidemiological systems. We exploit the sophisticated parameter regression functionality of a commercial chemical engineering simulator with piecewise continuous integration, event and discontinuity management. We develop a strategy for calibrating and validating a model. Our results using historic data from 4 countries provide insights into on-going disease suppression measures, while visualisation of reported data provides up-to-date condition monitoring of the pandemic status. The effective reproduction number response to NPIs is non-linear with variable response rate, magnitude and direction. Our purpose is developing a methodology without presenting a fully optimised model, or attempting to predict future course of the COVID-19 pandemic.

1. Introduction

COVID-19 is currently a global pandemic affecting around 213 countries around the world. As of 31 August 2020, 25.6 million cases, with 17.9 million recovered patients and 859,550 deaths have been reported (Worldometer, 2020). To control the pandemic, most governments have issued recommendations such as intensified hand hygiene and have taken measures such as closing borders, enforcing lockdowns, etc. These NPIs reduce infection rates, keeping the number of severe cases below hospital capacity limit, a strategy popularly referred to as ‘flattening the curve’. A significant challenge is to identify and efficiently evaluate the effect that active and varying NPIs have on the disease transmission rate. This is particularly important as countries begin to relax NPIs after successfully flattening the curve of active cases.

1.1. The effective reproduction number

Key parameters used to quantify contagion are the basic and effective reproduction numbers. These dimensionless numbers describe the average number of expected secondary infections generated by each infected person in the absence and presence of controlled interventions. Current opinion suggests that the COVID-19 has a basic reproduction number ~2–3. Although a recent review (Liu et al., 2020) compared twelve studies published from the 1st of January to the 7th of February 2020 which reported a range of values for the COVID-19 basic reproduction number between 1.5 and 6.68. This apparent disparity arises because the reported number depends on country, culture, the stage of the outbreak and calculation method used. NPIs aim to slow the spread of the virus and reduce the effective reproduction number to a sustained value less than one so that the pandemic will eventually die out. Scientists and governments in many countries around the world use the effective reproduction number as an illustrative metric to explain and justify the introduction and relaxation of NPIs (Fauci et al., 2020).

Highlights

Abstract

Keywords

Nomenclature

1. Introduction

2. Choice of the recycling strategy

3. Materials and methods

4. Results and discussions

5. Conclusions

Declaration of Competing Interest

Acknowledgements

References

Abstract

Though synthetic plastics are indispensable in our everyday life, the uncertainty surrounding the sustainability of fossil reserves has led to the development of a novel class of plastics, referred to as bio-based plastics. Poly(lactic) acid (PLA) is the most frequently used member of this family. However, due to the lack of a holistic recycling strategy, its large scale utilization can turn out to be an acute source of plastic pollution in the future. Unlike other attempts directed towards chemical recycling of PLA which violate the basic principles of green chemistry, the following research establishes an eco-friendly recycling concept aimed at the production of a valuable lactate ester through solvent assisted transesterification of PLA waste. The scope of this research is not only limited to the selection of an appropriate system (solvent, nucleophile and catalyst) but also extends to analysing the selectivity of the solvent towards the PLA fraction in a commingled stream and the effect of the concentration of nucleophile and different PLA substrates on the yield of the lactate ester. It was observed that, irrespective of the source of PLA, a high yield of ethyl lactate (approx. 80%) with complete retention of stereochemistry was obtained for a molar ratio of nucleophile per mole repeat unit of PLA (nnuc:nrpu) equivalent to 3. Thus, this work represents an attempt towards instituting circular bio-economy by overcoming the engineering and environmental challenges associated with PLA-waste management and production of ethyl lactate; while strictly adhering to the principles of green chemistry and sustainable chemical engineering.

1. Introduction

Although the mass production of synthetic plastics only dates back to 1950, they have become the most abundant anthropogenic materials and serve as a geological indicator of the Anthropocene era [1]. The annual plastic production is expected to reach 1124 million tons by 2050; thereby, consuming 20% of the crude oil produced globally as opposed to 6% in 2014 [2], [3]. Though these synthetic polymers are designed for their durable performance, their rapid growth as “materials of everyday use”, indiscriminate disposal and resistance to biological degradation presents an extensive threat to the environment [4]. In lieu of rising awareness about sustainability coupled with the pressure from global climate change over the past two decades, bio-based plastics have gained impetus as novel materials synchronous to the concept of sustainable production and utilization [4], [5]. Though this class accounts for less than 1% of the global annual plastic production, its global production capacity is estimated to increase from 2.11 million tons in 2020 to 2.87 million tons in 2025 at a compounded annual growth rate of 6.3% [6], [7].

Amongst other bio-based polymers, PLA is the most promising polyester [3], [5], [8]. It is regarded as a sustainable alternative to synthetic, petrochemical plastics such as PET and PS on account of its similar mechanical properties [5]. Accounting for 62.5% of its total annual production, NatureWorks® (150,000 tons; USA) and Total Corbion PLA (75,000 tons; Thailand) are the major producers of PLA in the global market [9]. PLA has expanded itself in several markets, ranging from disposable cutlery and degradable sutures to rigid packaging and extrusion coatings [5], [10], [11], [12], [13]. This is evident from the fact that, the relative share of PLA in the total global production of bio-plastics has increased from 13.9% in 2019 to 18.7% in 2020 [7]. However, the food packaging sector continues to be the most dominant market for PLA [11], [12], [13].

Abstract

Introduction

Figures (7)

Section snippets

References (19)

Recommended articles (6)

Abstract

Implementation of student-centered learning has shown wide global acceptance within institutes of higher learning. Some methods, such as active learning, project-based learning, problem-based learning, and experiential-based learning, have significantly impacted the students’ understanding of a particular subject. However, students will still have problems integrating the materials learned from one course to other courses. Thus, this is where the proposed initiative comes in. This paper discusses the implementation of integrated project-based learning (IPBL) to assist students in integrating the knowledge gained from one course to the other for first-year chemical engineering students of Universiti Teknologi PETRONAS. The mapping of assessments and learning domains to the learning activities are also shown in detail. This study was conducted on two courses offered in the same semester, namely, Principles of Chemical Engineering and Chemical Engineering Fluid Mechanics, in January 2019. A total of 214 students grouped in 43 teams were asked to develop a Do-It-Yourself (DIY) hydraulic jack, which uses the fundamentals taught in these two courses. The results show that 100 % student was able to come up with a working prototype within 5 weeks and 90 % of the students agree that the initiative increased their understanding in chemical engineering fundamentals and developed their leadership, problem-solving, communications and time management skills.

Introduction

Standard STEM programs are typically offered to students through a series of courses that need to be completed in 4 years. Knowledge is imparted to the students in courses for a better understanding of the overall program. In the chemical engineering discipline, the courses were taught separately to have more focus within each intended course, such as separation, reaction, fundamentals, control, and safety. This was necessary to equip the students with an in-depth knowledge of the fundamentals in a sequential manner. Conventionally, the program requires an individual project or a team project to be given to the students. It was expected for the students to complete it and send in a report to the instructor. However, a recent trend in academia showed project-based learning and problem-based learning as alternative approaches for the projects. This initiative can be seen in subjects such as process control (Yusof et al., 2012), separation process (Calvo and Prieto, 2016), design project (Vega and Navarrete, 2019), unit operations and modeling and simulations (Ballesteros et al., 2019), reaction engineering (Azizan et al., 2018), and introduction to engineering (Sadikin et al., 2019).

However, a problem that can be seen in this approach is the failure to integrate the learning materials from one topic or course to another. Several methods have been proposed over the years, such as open-ended problems, problem-based learning, case studies, cooperative learning, and class debates (Hung et al., 2008; Hamouda and Tarlochan, 2015). Although there is still inconclusive evidence on which approach is most suited for enhancing critical thinking skills, addressing this issue only within individual courses would limit the students’ time to gain other critical skills (Huber and Kuncel, 2016).

1- Introduction

2- Experimental section

3- Result and discussion

4- Conclusions

References

Abstract 

High-efficient noble-metal-free photocatalyst is vital to realize high H2 evolution. In consideration of this, we design a CdS@NiS reinforced concrete structure derived from nickel foam (NF) via a simple one-pot oil bath strategy. The whole preparation process is started with the growth of NiS rods on NF. Subsequently, NiS rods are encased in CdS gradually under oil both conditions. After the combination of NiS rods and CdS, the photoelectrical properties of primeval CdS are greatly optimized, e.g., photoelectric responsiveness, impedance and light absorption capacity. Moreover, the H2 evolution rate of CdS@NiS is increased significantly from 2706 to 40601 μmol g−1 h−1 under visible-light irradiation (λ > 420 nm), which is about 15 times higher than that of pure CdS, thereby confirming the excellent synergistic effect between NiS rods and CdS. Additionally, the photocatalytic performance of CdS@NiS was stronger than that of CdS/NiS-NPs (6726 μmol g−1 h−1 ) and CdSNPs/NiS (1639 μmol g−1 h−1 ), highlighting the advantages of CdS (prepared using oil bath treatment) and NiS rods (originated from NF growth). Lastly, according to experiment data and DFT calculation results, a viable mechanism for CdS@NiS is tentatively proposed.

Introduction

During past few decades, photocatalytic hydrogen generation has been considered as a promising strategy to overcome energy crisis [1–8]. Since Fujishima reported the photocatalytic H2 generation phenomenon in 1972 [9], photocatalytic materials for water splitting, especially metal sulfides, has gradually been a research focus. Up to now, CdS attracted extensive attention because of the unique optical response [10], high light-harvesting efficiency [11] and narrow band gap [12]. However, pure CdS generally exhibits poor photocatalytic H2 production due to the low charge carriers separation [2,13,14]. One of the promising solutions is combining cocatalysts with CdS to refine its photocatalytic properties [15–20]. Among the various cocatalysts, nickel sulfide (NiS) has been regarded as an effective cocatalyst because of its high electrical conductivity and excellent power conversion efficiency. For instance, Xu et al. firstly reported the excellent synthetic effect between NiS and CdS for H2 production (ca. 7266 μmol h−1 g−1 , λ > 420 nm) [21]. After that, some studies about NiS/CdS hybrid photocatalysts have been carried out to develop novel fabrication strategies or further improve its H2 production [22–28]. Despite the remarkable advances, there are still great challenges and improvement space for NiS/CdS catalysts: (1) Compared with pristine CdS, the H2 production of NiS/CdS is only improved to a limited degree (ca. 25000 μmol h−1 g−1 , λ > 420 nm). Its water splitting efficiency may be further enhanced to ca. 40000 μmol h−1 g−1 via specially designed strategies; (2) Generally, CdS was first synthesized and then decorated with NiS. Thus, the as-prepared CdS needed to suffer additional reactions treatment, which may destroy the active site and weaken its light absorption capacity due to the poor physicochemical stability of CdS.