Frustratingly complex: Why is growing electronic grade 2D materials so difficult?

Despite their game-changing potential, electronic-grade 2D materials like graphene and MoS₂ still can’t be reliably grown at scale. The core issue lies in the chemical vapor deposition (CVD) process, which functions like a black box: external controls (temperature, gas flow, pressure) don’t guarantee predictable or repeatable results inside the reactor. Without a clearer understanding of what’s happening during growth, reproducibility remains elusive, and until that changes, the promise of 2D materials transforming technology will stay just out of reach.

Two-dimensional (2D) materials are ultrathin sheets just one to a few atoms thick that are poised to transform everything from flexible electronics to quantum devices. Among them, graphene may be the poster child, but materials like molybdenum disulfide (MoS₂) and hexagonal boron nitride (h-BN) are just as exciting, offering unique electronic, optical, and mechanical properties.

But there’s a problem: we still can’t reliably grow them, or at least not the defect-free, electronic-grade films essential for next-gen optoelectronic devices. Even in the same lab, using the same recipe and equipment, researchers often get inconsistent results. This unpredictability is more than a minor inconvenience, it's one of the biggest barriers to scaling up 2D materials for real-world applications.

The CVD Reactor: A Scientific Black Box

Most high-quality 2D materials are synthesized using chemical vapor deposition (CVD), a process where gases react on a heated surface to form thin layers. In principle, it's a powerful technique. In practice, it's a mystery.

The issue? The internal environment of a CVD reactor is complex, uneven, and largely unmeasurable. Unlike a stirred flask where conditions like temperature and concentration are fairly uniform and easy to track, a CVD system exhibits steep spatial gradients. What's happening inside the chamber where the actual growth occurs is difficult to probe directly.

We can control external variables like furnace temperature, pressure, and gas flow, but the relationship between these knobs and the true reaction conditions is nonlinear and poorly understood. So while the system looks controlled on the outside, it behaves unpredictably on the inside.

Reproducibility Grinds to a Halt

Without insight into the growth mechanism (the sequence of atomic events during material formation) and growth kinetics (how fast they occur), we're flying blind. We can't optimize the process. We can't replicate it. And we certainly can't scale it.

This opacity doesn't just slow down research, it makes it fragile. New ideas can't be reliably tested. Published methods can't be trusted without extensive trial and error. Progress stalls because every experiment starts from scratch.

Still Stuck in Edison's Lab

What we're left with is a modern version of an old problem: trial-and-error science, or what some call the ‘Edisonian’ approach. It wastes chemicals, energy, time and brainpower. In an era where materials discovery is accelerating through AI, automation, and big data, this kind of inefficient, analog workflow is unsustainable.

From Black Box to Glass Box

To fix this, we need to transform the CVD reactor from a black box into a glass box, not literally, but figuratively. We need a clear understanding of what's happening inside during growth and how it responds to the dials we can control. That could mean developing better sensors and smarter simulations, ones that learn from experiments and, in turn, help guide them.

Until then, the reproducibility crisis will persist. And with it, the dream of seamlessly integrating 2D materials into the next generation of technology will stay just out of reach.

A Path Forward

We believe reproducibility in 2D materials growth shouldn't be an afterthought: it should be the foundation. If you're working on CVD modeling, in-situ diagnostics, or AI for materials synthesis, let's talk. We're actively seeking collaborators, data partners, and others who share this vision. Check out the references below to explore the scientific basis behind these challenges, and, the opportunities they create.

References

@The disruptive promise from novel materials systems such as graphene and 2D systems is often discouraged by poor reproducibility from growth and processing

@An industry view on two-dimensional materials in electronics

@2D materials for future heterogeneous electronics

@Research on scalable graphene faces a reproducibility gap

@Repeatability and Reproducibility in the Chemical Vapor Deposition of 2D Films: A Physics-Driven Exploration of the Reactor Black Box

@2024 LinkedIn poll on reproducibility of 2D materials synthesis

@2025 LinkedIn poll on reproducibility of 2D materials synthesis