Software platforms of predictive multi-level modeling (M3T) for

modern materials, processes and devices

Problems and current trendsProblems and current trends

Industry demands pressure on the development of new materials Industry demands pressure on the development of new materials is becoming formidableis becoming formidable

Boeing 787 Dreamliner - 50% of composites for constructionBoeing 787 Dreamliner - 50% of composites for construction•20% more fuel efficient•20% less emissions

• Every technology is intimately related to a particular materials set and its performance under given conditions

• Changing the materials set in an established technology must be considered as a revolution

“The high-throughput highway to computational materials design”, Nature Materials, February 2013

Problems and current trendsProblems and current trends

Substances available to date in CAS Substances available to date in CAS registry of substances (www.cas.org)registry of substances (www.cas.org)•3 million experimentally characterized•61 million predicted and theoretically characterized

Usual Usual approachapproach: experiments

with trials and errors

Usual Usual approachapproach: experiments

with trials and errors

Integrated Integrated approachapproach,

based on predictive modeling

Integrated Integrated approachapproach,

based on predictive modeling

idea prototype testingdevice

technology

Expensive Expensive Long Long Not related with fundamental scienceNot related with fundamental science

Role of modeling: Role of modeling: interpolation of available datainterpolation of available data

idea prototype testingdevice

technology

Reduce cost and time Reduce cost and time Reduce risks of the developmentReduce risks of the development

Prototype development is preceded by modeling, based on fundamental Prototype development is preceded by modeling, based on fundamental understanding and description of mechanisms of phenomena/processes understanding and description of mechanisms of phenomena/processes

modelingmodeling

Multi-scale Multi-physics Modeling Technology – MMulti-scale Multi-physics Modeling Technology – M33TT

Simulation Workflow and Simulation Workflow and Collaboration ManagementCollaboration Management

ScientistScientist

Process/material Process/material designerdesigner

Engineer/DesignerEngineer/Designer

Atomic scale:Atomic scale:Quantum chemistryQuantum chemistry

Meso-scale:Meso-scale:Chemical kinetics, …Chemical kinetics, …

Continuum scale:Continuum scale:FEM, CFD, FDTDFEM, CFD, FDTD

Molecular Dynamics,Monte-Carlo

Micro-kinetic theory

Kinetic mechanism reduction,Principle component analysis

Surrogate modeling

Computational Computational ModulesModules

InfrastructureInfrastructureToolsTools

Databases of material Databases of material propertiesproperties

HPC capabilitiesHPC capabilities

Unique featuresUnique features

Set of computational models based on 15 year of successful Set of computational models based on 15 year of successful industrial R&Dindustrial R&D•Atomistic and micro-scale models for recovery of material properties•Robust and fully automated methods of data transformation and assimilation across the physical levels•Device-tailored computational models for engineering design and process simulation with generated materials properties•Uncertainty propagation across the physical levels and continuous model improvement based on new experimental data

Complete set of infrastructure toolsComplete set of infrastructure tools•Enterprise-level database of materials•Computational workflow and collaboration management•HPC support, tailored to a range of architectures

MarketMarket

Reactive systemsReactive systems

US$ 200MUS$ 200M

Energy storageEnergy storage

US$ 200MUS$ 200M

Optical meta-materialsOptical meta-materials

US$ 450MUS$ 450M

Composite materialsComposite materials

US$ 450MUS$ 450M

US$ 1.3BUS$ 1.3B

R&D Markets by industry to be served by the technology/productR&D Markets by industry to be served by the technology/product

“…ROI for investments into modeling infrastructure and methods achieve $9 for $1 spent ”

Analytic report, IDC, 2004

“…ROI for investments into modeling infrastructure and methods achieve $9 for $1 spent ”

Analytic report, IDC, 2004

First Focus R&D Market – Reactive systemsFirst Focus R&D Market – Reactive systems

US$ 200MUS$ 200M•US$ 100M by software•US$ 100M by services

Revenue among Revenue among focus customer industries, %focus customer industries, %

Driving factors for modeling Driving factors for modeling in product life cyclein product life cycle

• Time-to-market

• Cost of pilot testing

• Environment

TeamTeam

• More than 70% of people have PhD and Dr.Sc. degrees• Completed more than 80 projects in multi-scale modeling R&D projects with leading

industrial companies• Developed software for steps of multi-scale modeling: Chemical Workbench, KintechDB,

Khimera, FDTD-II, MD-kMC, IDeA

ExperienceExperience

Uwe Riedel, professor, head of the kinetics division of a DLR Institute of

combustion technology, Germany

Michael Frenklach, professor, California Institute of Technology, USA. Author of GRI-

Mech, internet-service PrIMe

Boris Potapkin, CEO and founder of Kintech Lab Ltd., co-founder of GRASYS Ltd. – Eastern Europe leading

manufacturer of gas-separation systems

TeamTeam

Sales strategy and planSales strategy and plan

Sales strategySales strategy• Software license sales. R&D labs of industrial companies, Universities, National labs.• Software as a Service (SaaS). Cloud web access to company project server and full set of computational models, databases, hardware.• Software distribution through vendors. Cooperate with major CFD and FEM software vendors, where synergetic effect after coupled use of M3T and CFD/FEM is achieved• R&D service. The developed software will be used as a tool to carry out contract R&D projects, which contribute ~50% into market share.

Sales planSales plan•Start of sales – End 2013•First pilot sales – mid 2014•Web-sales – web-site promotion, free and paid webinars on software, free and paid webinars on case-studies and service of the company•Direct sales directions for 2013 - 2014

• Russia and Europe (3 representatives = 1 sales office)• USA (2 representative =1 sales office)• Japan and China (distribution agreement)

•Goal• Market share 10% in 3 – 5 years• Revenue US$ 30 – 40 M

Investment and Exit strategyInvestment and Exit strategy

Exit strategy for investorExit strategy for investor1.Sale of part of the business (developed platform) to strategic investor

• Software vendor (CFD&FEM software, Scientific data management software)• Industrial company

2.Company M&A by big market player• Software vendor (CFD&FEM software, Scientific data management software)

InvestmentsInvestmentsUS$8-10 М in 3 years including•50% investment share by Skolkovo foundation at the product development•25% Skolkovo share at commercialization stage