Atomic layer deposition (ALD) is a vapor-phase deposition technique that has attracted increasing attention from both experimentalists and theoreticians in the last few decades. ALD is well-known to produce conformal, uniform, and pinhole-free thin films across the surface of substrates. Due to these advantages, ALD has found many engineering and biomedical applications. However, drawbacks of ALD should be considered. For example, the reaction mechanisms cannot be thoroughly understood through experiments. Moreover, ALD conditions such as materials, pulse and purge durations, and temperature should be optimized for every experiment. It is practically impossible to perform many experiments to find materials and deposition conditions that achieve a thin film with desired applications. Additionally, only existing materials can be tested experimentally, which are often expensive and hazardous, and their use should be minimized. To overcome ALD limitations, theoretical methods are beneficial and essential complements to experimental data. Recently, theoretical approaches have been reported to model, predict, and optimize different ALD aspects, such as materials, mechanisms, and deposition characteristics. Those methods can be validated using a different theoretical approach or a few knowledge-based experiments. This review focuses on recent computational advances in thermal ALD and discusses how theoretical methods can make experiments more efficient.

This work presents a mathematical model for the simultaneous optimisation of water and energy usage in hydraulic fracturing using a continuous time scheduling formulation. The recycling/reuse of fracturing water is achieved through the purification of flowback wastewater using thermally driven membrane distillation (MD). A detailed design model for this technology is incorporated within the water network superstructure in order to allow for the simultaneous optimisation of water, operation, capital cost, and energy used. The study also examines the feasibility of utilising the co-produced gas that is traditionally flared as a potential source of energy for MD. The application of the model results in a 22.42% reduction in freshwater consumption and 23.24% savings in the total cost of freshwater. The membrane thermal energy consumption is in the order of 244 × 10³ kJ/m³ of water, which is found to be less than the range of thermal consumption values reported for membrane distillation in the literature. Although the obtained results are not generally applicable to all shale gas plays, the proposed framework and supporting models aid in understanding the potential impact of using scheduling and optimisation techniques to address flowback wastewater management.

An ecoindustrial park (EIP) is a state-of-the-art concept in which a group of industries located in proximity share their products, byproducts, and waste in a symbiotic manner to conserve natural resources and enhance sustainability. To design a hydrocarbon-processing EIP, a carbon-hydrogen-oxygen symbiosis network (CHOSyN) that involves the use of multiscale atomic-based targeting, tracking, combination, separation, and allocation can be used. A major challenge in the multicompany implementation of an EIP is the uncertainty associated with the exchanged streams. The flow rate and characteristics of the streams are subject to fluctuations because of the variability in the performance of the participating plants. Concerns for reliable quantity and quality of streams exchanged among the different plants can largely impact the decision of a company to be integrated in an EIP. This article addresses the challenge of the fluctuating performances of participating plants by addressing the uncertainty of the exchanged streams in a CHOSyN. A stochastic approach is used for stream characterization and reliability assessment of an EIP. Performance functions are generated using response surface methodology. Next, a reliability analysis is performed with limit state function, or gradient-based methods, like the first-order reliability method, is used for analysis under relevant constraints. With the performance indexes, the variables are iteratively adjusted to achieve design and performance targets that meet sustainability criteria (e.g., economic, environmental). To illustrate the applicability of the proposed approach, a five-plant CHOSyN case study is solved.