Simulate your chemical processes with ready-to-deploy, fully interactive models using a combination of powerful computation, statistics and optimization, instant interactivity, and built-in chemical data. One system, one integrated workflow.
Underlying the Mathematica chemical engineering solution is the world's most sophisticated differential equation solving with automatic algorithm selection, self-checking precision control, and symbolic preprocessing–everything to get accurate results efficiently.
Ready-to-use, built-in curated data on thousands of chemical compounds
A 3D, space-filling molecular plot of caffeine using built-in chemical data
Highly optimized superfunctions for differential equation solving
Mathematica superfunctions automatically select the right algorithm to obtain accurate results
Interactive computing and visualizing of chemical kinetics phenomena
A demonstration of unsteady-state diffusion, convection, and reaction in a fluid film
Automatic algorithm selection by built-in superfunctions such as NDSolve ensure accurate results to complex numerical problems in fluid mechanics, heat transfer, separation processes, and more
Integrated environment for chemical engineering model building, statistical analysis, optimization, and generation of interactive reports and applications
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Why Choose Mathematica
Key Capabilities
Why Choose Mathematica
Ways to Use
Compare Mathematica to your current tools. Do they have these advantages?
Built-in parallel computing capabilities for solving computation- or data-intensive problems on multicore computers » Competitor note: Matlab requires purchase of extra toolbox for parallel computing; all major software systems require extensive programming to parallelize processes
Seamless integration of numerics, symbolics, interactive graphics, and all other computational aspects in one document Competitor note: Not possible in other software
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Ways to Use
Key Capabilities
Why Choose Mathematica
Ways to Use
Solving coupled nonlinear differential equations for chemical kinetic modeling and applications in transport phenomena
Designing and optimizing unit operations such as distillation and adsorption processes in a chemical plant
Developing thermodynamic models to predict vapor-liquid equilibria of non-ideal mixtures
Computing Laplace transformations for process control applications
Numerical solution of transport equations, advanced heat and mass transfer problems, and other transport phenomena applications
Performing economic viability analysis for chemical plant design using built-in economic, financial, geographic, and demographic data