Every time you squeeze toothpaste onto your toothbrush, spray perfume on your skin, or swallow a pill, you’re using the result of a carefully crafted recipe made in a lab. These are called formulations.
Formulations aren’t just simple mixtures — they’re complex arrangements of ingredients designed to work together in specific ways.
Getting the recipe right can mean the difference between a product that sits on the shelf (or never makes it to the shelf) and one that changes lives.
Here at NIST, we’re revolutionizing how scientists create and improve formulations. We hope the result will be better products you use every day.
The process combines robotics, artificial intelligence and analysis of advanced materials. For example, we can use neutrons or X-rays to take pictures of how molecules millions of times smaller than a human hair are arranged in materials. It’s not just about making better products.
It’s about making them in ways that are faster and more efficient while leaving a lighter footprint on health and the environment.
This happens in our Autonomous Formulation Laboratory (AFL) at NIST’s campus in Gaithersburg, Maryland.
How Your Products Are Made Now
Let’s say you own a shampoo company, and a key ingredient in your shampoo is no longer available due to supply chain issues. You now have to remake your formulation to put in a replacement ingredient.
But what ingredient? How much of it? What if that new ingredient has an unintended consequence that affects other parts of the recipe?
This is the challenge of product formulation today. Reformulating a consumer product can take months of research and a lot of money. It often requires trial and error or expert know-how.
While that knowledge is valuable, experts may have difficulty adapting to new or changing ingredients.But as a scientific community, we can do better.
NIST has experts who use tools to examine the structure of materials and measure them at the smallest scales. But the sheer number of samples would make this challenging to do in a traditional formulation lab.
” We’re helping manufacturers improve a wide range of products by optimizing their structural compositions. This applies to everything from shampoos and paints to automotive fluids and cleaning detergents.”
Enter AI.
An Intelligent, Interactive Loop Here’s how this process works:
Step 1: Precision Mixing
Much like cooking, we start by gathering the ingredients. Instead of putting them in an oven, we put them into small vials about the size of a film canister and tell a computer about what they are. The computer then controls a robotic system equipped with a pipette.
This computer precisely measures and mixes tiny amounts of chemicals from different vials. The amount of mixture is minuscule — about 30 microliters, less than a dot of ink from a fine-tip pen.
Step 2: Advanced Structural Analysis
Once the sample is prepared, we analyze it at a very detailed level, using equipment that works like an advanced microscope. We call these advanced scattering techniques.
These techniques allow us to observe how different chemicals organize themselves into larger structures within the formulation. We can then make predictions about how products will behave once our “recipe” is made.
These scattering techniques usually happen at a neutron source, such as the NIST Center for Neutron Research on our Gaithersburg campus. They also sometimes happen at a machine about a half-mile long that makes incredibly bright X-rays, known as a synchrotron.
Step 3: AI-Driven Optimization and Learning
Here’s where the magic happens. During the formulation measurement process, we collect a wealth of data and feed it into an artificial intelligence system.
The AI analyzes the information, learns about it and predicts which formulation structure will work best given the manufacturer’s goals.
It then instructs the robotic system to create this new formulation based on what it’s learned from past tasks. But it doesn’t stop there.
The robot analyzes the new formulation and feeds the results back into the AI. With each iteration, the AI learns, refines its understanding and makes increasingly sophisticated predictions. It’s as if the system is thinking, learning and evolving its approach in real time.
This creates a loop of experimentation and improvement, dramatically accelerating the development process for medicines and other consumer products. What might have taken months or years of trial and error can now be accomplished in hours or days. Of course, AI is not perfect, and you can’t trust it without extensive product testing.
The companies involved in this process still test their products. AI helps them develop their “recipes” much more quickly and easily than they could before.
Real-World ImpactI
n a recent collaboration with a pharmaceutical company, the AFL tackled a complex formulation issue in just hours — a process that might have taken months using traditional methods.
By focusing on the structural arrangement of the formulation’s components and learning from each try, the team could quickly identify and resolve issues affecting the drug’s performance.But the AFL’s impact extends beyond pharmaceuticals.
We’re helping manufacturers improve a wide range of products by optimizing their structural compositions. This applies to everything from shampoos and paints to automotive fluids and cleaning detergents.
The AFL can handle pretty much any liquid formulation right now. We’re exploring ways to adapt it to analyze structured solids in the future.
▪︎From NIST