Aluminerie Alouette Inc.

Sept-Iles, Canada

Aluminerie Alouette Inc.

Sept-Iles, Canada
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News Article | May 8, 2017

SHERBROOKE, Quebec, May 08, 2017 (GLOBE NEWSWIRE) -- THYMOX™, the breakthrough, botanically-derived disinfectant, has announced the closing of a $4.6 million Series B financing round. The round was led by current investors, Cycle Capital Management and Desjardins Innovatech, and attracted new investors including Germain Benoit from Gercanoit. The funds will primarily be used to accelerate international commercial expansion of THYMOX™ as a disinfectant for animal health and crop protection, and into institutional and retail markets. “We are entering a very exciting phase of our company's growth,” said Frank Palantoni, CEO of Laboratoire M2, the makers of THYMOX™. “We’re extremely pleased to welcome our new investors to this round, and also to see our current investors, Desjardins Innovatech and Cycle Capital Management, participate. We now have the resources to globally commercialize our greentech disinfecting technology platform." "Bringing a new biological solution with such broad applications into new markets is a significant challenge. We’re proud to partner with a great entrepreneurial team to meet the challenge and pursue commercial growth,” added Andrée-Lise Méthot, Founder and Managing Partner at Cycle Capital Management. Citing the company's expanding commercial frontiers, Jacques Perreault, Vice President of Desjardins Innovatech, commented, "We are enthusiastic about partnering with the management team and the shareholders of Laboratoire M2 to support their next phase of growth and development. They have a strong business plan, their product, Thymox, is innovative, and they are evolving in a fast growing market close to Desjardin’s values." Desjardins Group is one of Canada's leading cooperative financial groups with more than $200 billion in assets. 2017 represents a major milestone year for THYMOX™, as the company successfully pivots from technology development to full scale commercial expansion on three continents. "We remain on track in developing THYMOX sales momentum in our Animal Health business, and we are launching new products for our surface disinfecting markets," Palantoni added, "and of course, our robust pipeline of innovation includes products to meet the ever increasing demand for botanically derived crop protection products. With our accelerating commercial momentum, we expect to continue to attract partnership interest from major strategic players in the Animal Health sector." THYMOX is a highly effective, biodegradable, non-toxic, concentrated disinfectant which is instantaneously dilutable and stable in water, an important advantage for all commercial applications. The effectiveness of THYMOX is based on the action of thymol, a botanically derived, active ingredient found in the plant thyme. THYMOX has strong anti-microbial properties and kills pathogenic microorganisms on surfaces and in agricultural settings without harming living tissue or the environment. About Laboratoire M2 Laboratoire M2, based in Sherbrooke, Canada, has a well-respected reputation for product innovation and expertise in environmentally sustainable, green disinfection and bio-security technology under the trademark THYMOX™. The company currently markets a range of leading propriety, biodegradable, anti-microbial products which are environmentally compliant (UL Ecologo2794). Its line of animal health products includes THYMOX HOOF® (also sold as THYMOX FOOTBATH™) which is used on dairy cows as an aid to control digital dermatitis (DD). The company estimates that the use of THYMOX™ will remove millions of pounds of toxic chemicals from the farm workplace and the environment as it replaces toxic and heavy metal compound based products. THYMOX™ also distributes products and ingredients under private label agreements in institutional, retail, and crop protection markets. For more information about THYMOX™ visit: Cycle Capital Management is the most active cleantech venture capital firm in Canada. Cycle Capital invests in companies developing and commercializing clean technologies and striving to reduce greenhouse gas emissions, optimizing resource use and improving process efficiency throughout a product’s life cycle. With assets of $231M under management, Cycle Capital invests in Quebec and across North America. Cycle Capital Management, which is based in Montreal with an office in Toronto and points of presence in New York, Seattle and Qingdao in China, regroups seasoned investment professionals, strategic advisors and industrial partners with in-depth knowledge of the sector. Cycle Capital Management has a special relationship with its strategic partners, notably Brookfield Renewable Energy, Rio Tinto Alcan, Cascades, Group M3, Lonza, Gaz Métro, Systemex Énergies, Aluminerie Alouette, and Hydro-Québec. For more information on Cycle Capital Management visit: Founded in 2005 and managed by Desjardins Business Capital régional et coopératif, Desjardins–Innovatech was formed through a joint initiative of the Québec government and Capital régional et coopératif Desjardins. With commitments of over $55 million in nearly 40 companies and funds, Desjardin–Innovatech’s primary mission is to promote and support venture capital financing for Québec companies working in technology development or industrial innovation, and business succession for Québec innovation entrepreneurs. To fulfil its mission, Desjardins–Innovatech partners with other technology players specialized investment funds, entrepreneurs, angel investors, technology enterprise accelerators to provide even greater outreach to SMEs with promising prospects for driving job creation and economic development.

Dion L.,University of Quebec at Chicoutimi | Marks J.,J. Marks & Associates LLC | Kiss L.I.,University of Quebec at Chicoutimi | Poncsak S.,University of Quebec at Chicoutimi | Lagace C.-L.,Aluminerie Alouette Inc.
Journal of Cleaner Production | Year: 2017

Significant amounts of greenhouses gases are produced annually by aluminium smelters around the globe. Most of these emissions are carbon dioxide but perfluorocarbons are nonetheless an essential part of GHG inventories for aluminium smelters. The total mass of perfluorocarbons declared is estimated using a linear relationship between some process parameters and a specific emission coefficient. However, this linear method does not accurately represent the observed behaviour of PFC emissions. Continuous gas measurements were performed using a Fourier-transformed infrared spectrometer connected to the gas treatment centre for several days. With the data collected from individual high voltage anode effects, four new models are proposed to estimate the emissions of tetrafluoromethane, along with three new models to estimate hexafluoroethane emissions. These non-linear models are compared to the existing methods and the overall accuracy of each model is calculated in comparison to in-situ measurements. The accuracy of each model to predict emissions associated to individual anode effects have been investigated as well and the results indicate that tetrafluoromethane emissions can be more accurately predicted by the proposed non-linear models. Models proposed to predict hexafluoroethane emissions are optimistic, but further refinements are necessary to optimise the accuracy of individual predictions. © 2017 Elsevier Ltd

Desmeules J.-F.,Dynamic Concept | Neron J.B.,Dynamic Concept | Tremblay M.,Aluminerie Alouette Inc.
TMS Light Metals | Year: 2016

In the aluminium electrolysis process, metal is retrieved from the cells using a tapping tube connected to a crucible in which vacuum is made to initiate and maintain molted metal flow. Care must be taken not to contaminate the aluminium with electrolyte during the tapping operation. Continuous improvement of cell performance, including reduction of the metal layer depth, increases the challenges related to the tapping operation. Reduction of the metal flow helps reducing the electrolyte quantity that is tapped, however this increases the duration of the operation and poses scheduling problems. A novel patent pending tapping control method and equipment have been designed and tested in the Alouette smelter, in order to minimize contamination while maintaining or reducing the tapping operation duration. Metal flow control is improved thanks to optimized software. Analysis of the process indicators show that a significant reduction in tapped electrolyte is obtained. The purpose of this paper is not to describe in detail the design and control algorithm of the control unit, which is proprietary, but rather to describe the results on various performance indicators. Some of these results were unexpected and in first appearance, showing downsides to the improved control. Further analysis shows that these apparent downsides are consequences of improved performance. Introduction.

Oumarou N.,University of Quebec at Chicoutimi | Kocaefe D.,University of Quebec at Chicoutimi | Kocaefe Y.,University of Quebec at Chicoutimi | Morais B.,Aluminerie Alouette Inc.
Applied Thermal Engineering | Year: 2016

One important step of the primary aluminum production, is anode manufacturing and its baking is the most expensive step of anode manufacturing process. The challenge for the anode industry is to produce good quality baked anodes while keeping the energy consumption, environmental emissions, and cost to a minimum. A mathematical model can be a useful tool to overcome these challenges and achieve the objectives for the industry. A transient process model of a horizontal anode baking furnace has been developed. The model represents all the important phenomena such as fuel combustion, generation and combustion of volatiles (tar, methane, and hydrogen), air infiltration, and heat losses to the atmosphere and the foundation. The model consists of two coupled sub-models (flue sub-model and the pit) was validated using the plant data. It simulates the transient behavior of the open ring furnace and predicts furnace operation and performance. In this article, the modelling is described, and the results are presented for an industrial furnace. © 2016 Elsevier Ltd

Bhattacharyay D.,University of Quebec at Chicoutimi | Kocaefe D.,University of Quebec at Chicoutimi | Kocaefe Y.,University of Quebec at Chicoutimi | Morais B.,Aluminerie Alouette Inc. | Gagnon M.,Aluminerie Alouette Inc.
TMS Light Metals | Year: 2013

Carbon anodes are a major part of the cost of primary aluminum production. The focus of the industry is to minimize the consumption of anodes by improving their quality. Therefore, the determination of the impact of quality of raw materials as well as process parameters on baked anode properties is important. The plants have a large data base which, upon appropriate analysis, could help maintain or improve the anode quality. However, it is complex and difficult to analyze these data using conventional methods. The artificial neural network (ANN) is a mathematical tool that can handle such complex data. In this work, Matlab software was used to develop a number of ANN models. Using published data, linear multi-variable analysis and ANN were applied to assess the advantages of custom multilayered feed-forward ANN. Results are presented which show a number of industrial applications.

Dion L.,University of Quebec at Chicoutimi | Kiss L.I.,University of Quebec at Chicoutimi | Poncsak S.,University of Quebec at Chicoutimi | Lagace C.-L.,Aluminerie Alouette Inc.
JOM | Year: 2016

Greenhouse gas (GHG) generation is inherent in the production of aluminium by a technology that uses carbon anodes. Most of those GHG are composed of CO2 produced by redox reaction that occurs in the cell. However, a significant fraction of the annual GHG production is composed of perfluorocarbons (PFC) resulting from anode effects (AE). Multiple investigations have shown that tetrafluoromethane (CF4) can be generated under low-voltage conditions in the electrolysis cells, without global anode effect. The aim of this paper is to find a quantitative relationship between monitored cell parameters and the emissions of CF4. To achieve this goal, a predictive algorithm has been developed using seven cell indicators. These indicators are based on the cell voltage, the noise level and other parameters calculated from individual anode current monitoring. The predictive algorithm is structured into three different steps. The first two steps give qualitative information while the third one quantitatively describes the expected CF4 concentration at the duct end of the electrolysis cells. Validations after each step are presented and discussed. Finally, a sensitivity analysis was performed to understand the effect of each indicator on the onset of low-voltage PFC emissions. The standard deviation of individual anode currents was found to be the dominant variable. Cell voltage, noise level, and maximum individual anode current also showed a significant correlation with the presence of CF4 in the output gas of an electrolysis cell. © 2016, The Author(s).

Dion L.,Aluminerie Alouette Inc. | Lagace C.-L.,Aluminerie Alouette Inc. | Kiss L.I.,University of Quebec at Chicoutimi | Poncsak S.,University of Quebec at Chicoutimi
TMS Light Metals | Year: 2016

Primary aluminum production is generating a significant amount of greenhouse gases. CO2 is the dominant compound but during anode effects, perfluorocarbons (PFCs) are released as well. Even when no generalized anode effects are present, intermittent emissions of PFC have been reported in small concentrations but the root causes of these emissions are hardly understood. Measurements were taken at "Aluminerie Alouette" plant using Fourier-transformed Infrared Spectroscopy on individual cells to analyze the evolution of the composition of the gas collected at the duct end. By correlating the variations of the concentration for the emitted gas with cell variables (voltage, intensity, and pseudo-resistivity) and individual anode currents, it was possible to develop a predictive model to quantify the tetrafluoromethane (CF4) emissions between 10 and 1000 ppb for individual cell emissions. By analyzing the time history of the resulting data and by applying a post treatment process accordingly, it is possible to reduce the number of false predictions and increase precision of the final results.

Berends W.,Hatch Ltd. | Haley S.,Hatch Ltd. | Gagnon M.,Aluminerie Alouette Inc.
TMS Light Metals | Year: 2016

Anode assemblies suffer a significant electrical contact resistance across the cast iron to carbon interface that is inversely dependent on contact pressure and area. Industry efforts have incrementally reduced this electrical resistance by increasing stub diameter, changing iron chemistry and by improving the stubhole shape. The additional use of multiple steel conductors to bridge across the cast iron to carbon interface provides a means to further reduce the electrical resistance. The function of the conductors is independent of the iron to carbon contact pressure, the stub temperature, iron chemistry, and the stubhole shape. The steel conductors are tightly driven into the carbon anode at one end, with the other end bonded into the cast iron. This paper includes in-pot performance testing results which demonstrate the reduced resistance when using stubhole conductors. © Copyright 2016 by The Minerals, Metals & Materials Society.

Tremblay S.-O.,University of Quebec at Chicoutimi | Marceau D.,University of Quebec at Chicoutimi | Kocaefe D.,University of Quebec at Chicoutimi | Lagace C.-L.,Aluminerie Alouette Inc.
TMS Light Metals | Year: 2015

The electrical resistance of an electrolytic cell requires a voltage drop of about 4.5 V for a current of 300 kA of which 7% is attributable to the anode assembly. Reducing this voltage drop is one of the most challenging research topics for the aluminum industry. Over the past decades, there has been much research on the minimization of this loss using the same assembly configuration. In this work, a new approach, which consists of inserting elements into the carbon paste during the anode production, was developed. This approach would provide a significant reduction in the voltage drop mainly through the improvement of the contact quality at the anode connection and the current distribution in the anode. Laboratory tests simulating the baking as well as the operation of small-scale assembly were carried out to estimate the resistance. The results demonstrate that it is possible to decrease the resistance at the anode connection under the conditions similar to those used by industry.

Bhattacharyay D.,University of Quebec at Chicoutimi | Kocaefe D.,University of Quebec at Chicoutimi | Kocaefe Y.,University of Quebec at Chicoutimi | Morais B.,Aluminerie Alouette Inc.
TMS Light Metals | Year: 2015

Carbon anodes constitute a substantial part of the cost during the electrolytic production of aluminum. The industry tries to minimize the consumption of anodes by improving their quality. Therefore, a clear understanding of the impact of the quality of raw materials as well as process parameters on anode properties is important. The plants have a large collection of data, which is complex and difficult to analyze using conventional methods. In this article, linear multivariable (LMA), partial least square regression (PLS), and artificial neural network (ANN) analyses are presented and compared as tools to predict the influence of different parameters on anode properties. Published laboratory data have been processed using Matlab software to carry out the analyses. The results clearly show that ANN is the best tool for prediction purposes. Unlike other methods, ANN can handle nonlinear complex relations even if a well-defined relationship is not available.

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