auto_awesome_motion View all 3 versions
organization

Dow

Dow Benelux B.V.
Country: Netherlands
Funder (2)
Top 100 values are shown in the filters
Results number
arrow_drop_down
12 Projects, page 1 of 3
  • Funder: EC Project Code: 607882
    Partners: Dow, Ghent University
  • Funder: UKRI Project Code: EP/P005403/1
    Funder Contribution: 937,655 GBP
    Partners: NTU, Autodesk Inc, Dow, SCG Chemicals Co. Ltd

    Polymer processing is a multi-billion pound, world-wide industry, manufacturing products used by virtually every person in the developed world (and beyond) on a daily basis. This vital sector of the UK economy will gain a significant competitive advantage from a molecular understanding of how polymers crystallise during processing, as it will enable stronger, lighter, more durable and more easily recycled plastic products. In this proposal we will overcome the key experimental, simulation and numerical issues in understanding polymer crystallisation to deliver a molecular based, predictive platform for the processing of semi-crystalline polymers. We will tightly integrate a family of progressively coarse-grained simulations and models, covering all relevant lengthscales within a single project. This will displace the current sub-optimal semi-empirical approaches in polymer processing and enable molecular design of polymer products, through choice of processing conditions. By facilitating the manufacture of polymer products with tailored properties this program will provide a critical competitive advantage to this important industry. Polymers are long-chain molecules, formed from connecting together a large number of simple molecules. These long-chain molecules are at the heart of the multi-billion pound plastics industry. Semi-crystalline polymers make up a very significant fraction of the worlds production of synthetic polymers. Unlike simple molecules, the connectivity of polymer molecules means they crystallise into a composite structure of crystalline and amorphous regions. The proportion of amorphous and crystalline material, along with the arrangement and orientation of the crystals, is collectively known as the morphology. The crystal morphology strongly influences strength, toughness, permeability, surface texture, transparency, capacity to be recycled and almost any other property of practical interest. Furthermore, polymer crystallisation is radically influenced by the flows that are ubiquitous in polymer processing. Flow drastically enhances the rate at which polymers crystallise and has a profound effect on their morphology. Flow distorts the configuration of polymer chains and this distortion breaks down the kinetic barriers to crystallisation and directs the resulting morphology. Understanding polymer crystallisation is a formidable problem. The huge range of relevant lengthscales ranges from the size of a monomer (nm) up to near macroscopic crystals (micro-metres). The range of timescales is even wider, ranging from the monomer relaxation time (ns) to nucleation (hours at low under-cooling). Our project will involve extensive multiscale modelling, supported at each level by experiments specifically designed to address key modelling issues. Our experiments will involve controlled flow geometries, the systematic variation of molecular weight and the probes of both nucleation and overall crystallisation. Close integration of experiments and all levels of modelling is a key feature. We will develop an interrelated hierarchical family of multiscale models, spanning all relevant lengthscales and delivering results where piecewise approaches have been ineffective. Each technique will be tightly integrated with its neighbours, retaining the molecular basis of the models while progressively addressing increasingly challenging systems. This will cumulate with the low-undercooling and high-molecular weights that are characteristic of polymer processing. Each simulation will use a rare event algorithm to dramatically increase the nucleation rate, the cause of the very long timescales. Insight from the most detailed models will guide the development of faster modelling. At the highest coarse-graining, the program will derive models suitable for computational modelling of polymer processing. Using these models in cutting-edge finite element code, we will compute FIC behaviour in polymer processing geometries.

  • Project . 2012 - 2012
    Funder: UKRI Project Code: EP/J013420/1
    Funder Contribution: 193,289 GBP
    Partners: JM, Cardiff University, Fusion, Sasol Technology, Dow

    The aim is to exploit a recent discovery concerning a new catalytic route for methanol production based on using bio-renewable feedstocks as starting materials. This new process and associated catalysts has been protected by a patent filing. The key feature is that the process opens up a wholly new route for the manufacture of methanol which is a key commodity chemical. Funding is requested to complete patent exemplification and to ensure commercial exploitation can be achieved.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 721027
    Overall Budget: 3,957,420 EURFunder Contribution: 3,957,420 EUR
    Partners: Dow, MEGARA RESIN INDUSTRY ANASTASIOS FANIS SA, FHG, UNILEVER U.K. CENTRAL RESOURCES LIMITED, ETH Zurich, ENTHOUGHT LTD, Granta Design (United Kingdom), ES, IBM RESEARCH GMBH, University of Patras

    The FORCE consortium is a 10 pan-European expert partnership with the objective to develop a integrated Business Decision Support System (BDSS) based on open standards for industries engaged in formulating chemical ingredients. The generic BDSS is an open framework that connects any existing or future materials models at various levels of complexity and discretion (electronic, atomistic, mesoscopic, continuum and empirical), experimental data sets, and structured and unstructured commercial information (e.g. on cost, forecasting, intellectual property (IP)). In combination with multi-criteria (objective) optimizers (MCO) for key performance indicators (KPI’s) the BDSS generates data driven formulation and product options for facilitating business decision making. The project has a generic focus but targets 3 specific important industrial sectors as main demonstrators, namely Personal Care (liquid detergents), Insulating Rigid PolyUrethane (PU) based Foams and Industrial Inks (PU-based) for the purpose of focus and generating a real ready to use BDSS available to large, medium and small enterprises alike. The proposed options are tailored for use into problem specific Apps. These provide an additional level of tailored user-friendliness and a data driven operational tool for product optimization, development and quality checks including faster and tailored customer services for the formulators and the providers of formulation components. Accordingly the project is positioning materials modeling as an integrated part of a business decision process. The consortium strives to change the modus operandi of mainly empiricism-based formulation industries into a science and technology and data driven industry by taking advantage of materials modelling and advanced computational learning methodologies for handling “big data”. The partners subscribe to the activities of the European Materials Modelling Council (EMMC).

  • Open Access mandate for Publications
    Funder: EC Project Code: 723706
    Overall Budget: 6,878,400 EURFunder Contribution: 6,878,400 EUR
    Partners: CNRS, JZHC, POLITECNICO DI MILANO, T.EN Netherlands B.V., CERFACS, SCHMIDT+CLEMENS GMBH + CO.KG, AYMING, Dow, AVGI, CRESS...

    The objective of the project IMPROOF is to drastically improve the energy efficiency of steam cracking furnaces by at least 20%, in a cost effective way, while simultaneously reducing emissions of greenhouse gasses and NOx per ton ethylene produced by at least 25%. One important way to reduce the energy input in steam cracking furnaces is to reduce coke formation on the reactor wall. The use of either advanced coil materials, combined with 3D reactor designs, improved process control, and more uniform heat transfer will increase run lengths, reducing simultaneously CO2 emissions and the lifetime of the furnaces. Biogas and bio-oil will be used as alternative fuels because they are considered renewable, and hence, decrease net CO2 production. Application of high emissivity coatings on the external surface of the radiant coils will further substantially improve the energy consumption. Less firing is required to reach the same process temperatures in the radiant coils. This will reduce fuel gas consumption and CO2 emissions by 10 to 15%. IMPROOF will demonstrate the advantage of combining all these technological innovations with an anticipated increase of the time on stream with a factor 3. To select the correct technologies for sustainable implementation in complex plant-wide and industrial data-intensive process systems, all the technology will be implanted in real-plant conditions at TRL6 in DOW. The strongly industrial oriented consortium is composed of 7 industrial partners, including 2 SME completed by 2 RTO and 2 university. This partnership shows a clear and strong path to the industrial and economical world with the involvement of all actors of the furnaces business. The financial resources mobilized by the partners represent a total grant of 6 878 401,25 € with a global effort of 538 person.month.