Deep Tech

How a South Korean University Team Is Turning Industrial Air Into Power

A turbine-inspired generator shows how overlooked industrial airflow could quietly become a new source of usable power

Updated

February 12, 2026 4:43 PM

Campus building of Chung-Ang University. PHOTO: CHUNG-ANG UNIVERSITY

Compressed air is used across factories, data centers and industrial plants to move materials, cool systems and power tools. Once it has done that job, the air is usually released — and its remaining energy goes unused.

That everyday waste is what caught the attention of a research team at Chung-Ang University in South Korea. They are investigating how this overlooked airflow can be harnessed to generate electricity instead of disappearing into the background.

Most of the world’s power today comes from systems like turbines, which turn moving fluids into energy or solar cells, which convert sunlight into electricity. The Chung-Ang team has built a device that uses compressed air to generate electricity without relying on traditional blades or sunlight.

At the center of the work is a simple question: what happens when high-pressure air spins through a specially shaped device at very high speed?  The answer lies in the air itself. The researchers found that tiny particles naturally present in the air carry an electric charge. When that air moves rapidly across certain surfaces, it can transfer charge without physical contact. This creates electricity through a process known as the “particulate static effect.”

To use that effect, the team designed a generator based on a Tesla turbine. Unlike conventional turbines with blades, a Tesla turbine uses smooth rotating disks and relies on the viscosity of air to create motion. Compressed air enters the device, spins the disks at high speed and triggers charge buildup on specially layered surfaces inside.

What makes this approach different is that the system does not depend on friction between parts rubbing together. Instead, the charge comes from particles in the air interacting with the surfaces as they move past. This reduces wear and allows the generator to operate at very high speeds. And those speeds translate into real output.

In lab tests, the device produced strong electrical power. The researchers also showed that this energy could be used in practical ways. It ran small electronic devices, helped pull moisture from the air and removed dust particles from its surroundings.

The problem this research is addressing is straightforward.
Compressed air is already everywhere in industry, but its leftover energy is usually ignored. This system is designed to capture part of that unused motion and convert it into electricity without adding complex equipment or major safety risks.

Earlier methods of harvesting static electricity from particles showed promise, but they came with dangers. Uncontrolled discharge could cause sparks or even ignition. By using a sealed, turbine-based structure, the Chung-Ang University team offers a safer and more stable way to apply the same physical effect.

As a result, the technology is still in the research stage, but its direction is easy to see. It points toward a future where energy is not only generated in power plants or stored in batteries, but also recovered from everyday industrial processes.

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Artificial Intelligence

AI Startup BrainGrid Raises US$1M to Help Non-Technical Founders Plan and Build Software Products

Backed by Menlo Ventures, BrainGrid tackles planning gaps as AI makes software building accessible to more founders.

Updated

April 1, 2026 8:37 AM

A phone screen with app icons. PHOTO: UNPSLASH

As artificial intelligence makes it easier to write code, a different problem is starting to surface. Building software is no longer limited by technical skill alone. Increasingly, the challenge lies in deciding what to build, how to structure it, and how to turn an idea into something that actually works.

That shift sits at the centre of BrainGrid, a startup that has raised $1 million in pre-seed funding led by Menlo Ventures, with participation from Next Tier Ventures and Brainstorm Ventures. The company is building what it describes as an AI-powered planning layer for people who want to create software but may not have a technical background.

The timing reflects a broader change in how products are being built. Tools like Claude Code and Cursor have made it possible to generate working code through simple prompts. For many first-time founders, this has lowered the barrier to entry. But writing code is only one part of the process. Turning that code into a reliable product requires structure, sequencing and clarity—areas where many projects begin to fall apart.

In traditional teams, this responsibility sits with product managers who define what needs to be built and in what order. Without that layer, even well-written code can lead to products that feel disjointed or incomplete. Features may not work together, integrations can break and the final product often does not match the original idea.

BrainGrid is designed to address that gap. Instead of focusing on generating code, it helps users map out the structure of a product before development begins. The aim is to give builders a clearer starting point so that the tools they use—whether human or AI—can produce more consistent results.

The company says more than 500 builders have already used it to create software products across areas like fitness, healthcare and productivity. These range from first-time founders experimenting with new ideas to experienced developers working independently. In many cases, the products are already live and generating revenue, suggesting that the demand is not just for experimentation but for building something that can scale.

For investors, the appeal lies in the evolving role of software development. As AI takes on more of the technical work, the value shifts toward defining the problem and structuring the solution. In that sense, planning becomes less of a background task and more of a core capability.

The US$1 million raise is relatively modest, but it points to a larger trend. As more people gain access to AI tools, the number of potential builders expands. What remains limited is the ability to organise ideas into products that work in the real world. If that shift continues, the next wave of software may not be defined by who can code, but by who can plan.