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Overview

In this mini workshop I explain what you need to know to write and effective scientific paper, simplify the review process, and expedite the acceptance of your paper. I will discuss the scientific elements you should include, the writing style you should follow, and the formatting you should adopt to compose an excellent article. I will also explain the reviewing and publication process followed by most journals.

Intended Audience

ABSTRACT:  Oil sands are a strategic resource for Canada, but despite technological advances in extraction techniques, the treatment of tailing ponds resulting from bitumen extraction is plagued by many environmental challenges. The crucial technical challenge is to separate bitumen from the sand and clay particles, then flocculate or stack the clay particles to release water that can be recycled to the bitumen extraction process. The clays can then be placed in the mine, giving rapid reclamation without forming tailing ponds that may take decades to be reclaimed.

ABSTRACT:  Process analytics play a key role in achieving the process control strategy objectives in manufacturing processes. It has the potential to enhance continued process verification and applications in real-time process monitoring and control. Process analytical methods including, near-infrared (NIR), fluorescence and Raman spectroscopy as well as high performance liquid chromatography (HPLC), are often used in the characterization of raw materials, in-process/intermediate and final product quality attributes of manufacturing processes.

ABSTRACT:  Chemical engineering models may have many reactions, many kinetic parameters, and many mass transfer and thermodynamic constants. Consequently, models that can fully describe a chemical engineering process are usually nonlinear and complex and have many unknown parameters. Additionally, chemical engineering models are not perfect and there are random disturbances from the environment that should be estimated.

ABSTRACT:  With the growing demands placed on industrial production to achieve an integrated smart plant, factories require the development of efficient and viable methods for analysing and assessing the available data. Recently, the emphasis has focused on the development of data-driven control methods that use economic key performance indices (KPIs).

 ABSTRACT:  Due to the increasing focus on energy efficiency, environmental regulations, and market competitiveness, developing technologies for innovative process operation is an active research subject in academia and industry. Process Systems Engineering (PSE) technologies play an important role in addressing these challenges. Since most of advanced PSE methodologies use model-based algorithms, developing a representative and reliable process model is a crucial step in utilizing advanced technologies in process industries.

ABSTRACT:  With the advent of the Internet of Things (IoT), smart devices and smart manufacturing, the amount of data collection has grown exponentially in a manner analogous to the Moore's law. The explosion in data availability, variety and size have enabled engineering, medicine, science and finance to heavily invest in data-based learning projects. Some of the successful learning projects, include The Human Genome Project, Google Flu Trends, Tesla Self-Driving Car Project and GE Industrial IoT.