Curve Fitting Demands Engineering Judgment

In material characterization, curve fitting is not a cosmetic post-processing step — it is where physical meaning is extracted from experimental data.

Material behavior is often nonlinear, parameter-sensitive, and multidimensional. Selecting an appropriate model, defining meaningful parameter bounds, and ensuring numerical stability are critical to obtaining reliable results.

Small changes in initial guesses or constraints can lead to vastly different outcomes. At the same time, experts must continuously assess whether a fit reflects real material behavior or merely an over-parameterized numerical solution.

Curve fitting is therefore a highly iterative, interpretative task that demands continuous visual feedback and flexible control over the model.

Slow Iteration, Low Confidence

In practice, advanced curve fitting is rarely supported by a single, purpose-built environment. Material experts rely on a patchwork of self-built Excel sheets, custom scripts, and generic online tools to get the job done.

While these approaches can work for simple cases, they break down as soon as models become nonlinear, parameter-sensitive, or multi-dimensional.

As a result:

• Model definition, parameter tuning, and visualization are spread across disconnected tools
• Parameter changes require manual updates, reruns, and re-interpretation
• Custom or established material models are re-implemented repeatedly
• Knowledge about “what works” remains implicit, individual, and hard to transfer
• This leads to slow iteration cycles and forces experts to spend more time managing tools than interpreting material behavior.

The impact is not abstract. It shows up as delayed conclusions, reduced confidence in fitted parameters, and increased risk that non-physical fits propagate into simulations, design decisions, and material databases.

What should be a focused, insight-driven task becomes an error-prone, trial-and-error process — limiting both the scalability and the reliability of material characterization work.

Flexible Curve Fitting Interface Built for Material Experts

The Flex Curve Fitter in MatLytics is designed specifically for the realities of material analysis.

Fits are shown interactively and live within the plot, allowing experts to immediately see how parameter changes affect model behavior. Initial values, bounds, and fixed parameters can be defined explicitly, ensuring numerical stability and physically meaningful solutions.

Material experts can:

• interactively adjust parameters with instant visual feedback
• fix or constrain parameters to enforce physical validity
• define custom multidimensional model functions without sacrificing usability
• reuse established material models from the MatLytics model library

Curve fitting becomes an integrated, transparent process — not a disconnected numerical step.

Faster Insight, More Reliable Parameters, Lower Risk

By turning curve fitting into a visual, expert-controlled workflow, MatLytics delivers clear business value:

• Faster convergence through interactive iteration
• Higher confidence in extracted material parameters
• Consistent reuse of validated material models
• No navigating spreadsheets or scripting, therefore lower maintenance effort
• More reliable inputs for simulation, design, and decision-making

MatLytics enables experts to focus on interpreting material behavior — while the organization benefits from speed, reliability, and scalability.

Experience Curve Fitting with Full Flexibility

Curve fitting is too critical to be treated as a black box.

Book a demo to see the Flex Curve Fitter of MatLytics in action.