Faster, Better Feedback Can Accelerate Materials Commercialization

November 13, 2024

Blog

In the race to commercialize products (chips, batteries, sensors, etc.) founded on new advanced materials platforms, feedback is essential. The process of optimizing materials to deliver ever greater performance is complex and tedious, requiring advanced techniques for measuring and characterizing properties at the nanoscale. By speeding up the feedback loop, we can help engineers make better decisions and accelerate the development and time-to-market of novel materials.

A Slow Path to Materials Commercialization

Bringing new materials to market has historically been a slow process. Once “commercialized”, materials often go through cycles of incremental improvement rather than transformative innovation.

Timeline from discovery to commercialization

This incremental approach stems from the extensive trial-and-error involved in developing even small changes. Unknown interactions between synthesis equipment, materials, and recipes means each iteration risks introducing unexpected variables. Improved feedback is necessary to shorten the time to optimization and accelerate the development cycle.

Materials Engineers Share the Need to Measure

Developing new materials and bringing them to market requires optimizing across many dimensions that depend on the target application:

Material Properties: atomic structure, composition, microstructure, and interfaces between materials.
Performance Metrics: resistance, frequency response, optical response, operating ranges, and more.
Commercialization Factors: scalability, repeatability, tolerance, cost-effectiveness and ability to synthesize with production-scale equipment.

Relying solely on computer-aided design to address these dimensions isn’t possible as real-world synthesis is challenged by incomplete physical knowledge, uncontrolled variables, and unpredictable complexities that first-principles computational models cannot account for.As a result, materials engineers depend on specialized measurement techniques to refine the synthesis process as they work towards commercial viability. While the materials goals may vary widely by application, the need for effective feedback is universal. Measuring the state of a material to produce this feedback is colloquially known as characterization.

The Complexity of Feedback at the Nanoscale

Optimizing materials properties at the atomic level requires advanced characterization techniques that are inherently “narrow” in the data they provide, as each is only sensitive to specific properties. For instance, electron microscopy might reveal structural details, while X-ray spectroscopy resolves aggregate chemical composition.Interpreting the results requires domain expertise, and the analysis tools often require significant manual input. In practice, this means that feedback loops remain technically complex, time-intensive, and challenging to scale.Due to limited time, scientists and engineers typically extract only the minimum information required from data collected, leaving valuable data unused. Additionally, the “narrowness” of the data from certain techniques necessitates integration of multiple data streams to form a comprehensive understanding of the material or device. This integration of information has historically been accomplished by the engineer, placing them firmly “in-the-loop” and creating barriers to applying data-driven computational models. Improving this feedback loop, and freeing the engineer to do higher level interpretation work, is essential for accelerating the development of new materials.

Faster and Fewer Iterations: The Key to Accelerating Development

Reducing the time and number of iterations required for material optimization is key to accelerating the commercialization process. This is why we’re focused on two goals:

Providing Feedback Faster: Quicker feedback allows researchers to adjust parameters in near real-time, cutting down the time spent waiting for data and results.
Improving Decision-Making: With better feedback, engineers can make informed decisions about what to try next. A data-driven approach to experimentation can reduce the guesswork and help teams converge on effective synthesis strategies faster.

With faster, better feedback, materials engineers can make more informed decisions earlier in the development cycle. This will not only accelerate commercialization but also unlock the potential for more innovative materials that meet modern needs for efficiency, sustainability, and performance.

Unlocking the Next Generation of Materials

Ultimately, faster and better feedback isn’t just about making incremental improvements in synthesis. It’s about empowering scientists and engineers with data-driven insights to make smarter, faster decisions. With the right tools, we can unlock the full potential of nano-engineered materials and transform how industries approach material innovation.As we move towards more automated, real-time characterization methods and bring siloed techniques into integrated workflows, advanced materials industries have an opportunity to achieve unprecedented speeds in commercialization. The faster we can refine feedback loops and minimize iteration cycles, the sooner we can bring advanced materials to market, driving innovation across industries.Follow Atomic Data Sciences and check out our case studies to see how we are accelerating materials feedback and working to improve decision-making. Reach out to schedule a demo of our platform or to discuss your feedback needs.