5 Nanomaterial Innovations That Didn't Deliver (Yet)

2025-05-31 - 2025-05

Despite strong early results, some nanomaterials have struggled to meet the demands of real-world use, whether due to cost, manufacturing challenges, health concerns, or limited performance outside controlled settings.

This article looks at five such cases: materials that drew attention, raised expectations, and then stalled, at least for now

Finely-tuned TiO? nanorod arrays enhance solar cell efficiency

2025-05-19 - 2025-05

A research team led by Prof. Wang Mingtai at the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a finely tuned method for growing titanium dioxide nanorod arrays (TiO2-NA) with controllable spacing without changing individual rod size and demonstrated its application in high-performance solar cells.

Their findings, published in Small Methods, offer a new toolkit for crafting nanostructures across clean energy and optoelectronics.

Single-crystalline TiO2 nanorods excel at harvesting light and conducting charge, making them ideal for solar cells, photocatalysts, and sensors. However, traditional fabrication methods link rod density, diameter, and length—if one parameter is adjusted, the others shift accordingly, often affecting device efficiency.

In this study, by carefully extending the hydrolysis stage of a precursor film, the team showed that longer "gel chains" assemble into smaller anatase nanoparticles. When the anatase film is subjected to hydrothermal treatment, those anatase nanoparticles convert in situ into rutile ones, serving as seeds for nanorod growth. The hydrolysis stage provides an effective way to control the rod density without altering the nanorod dimensions.

Using this strategy, they produced TiO2-NA films with constant rod diameter and height, even as the number of rods per area varied. When incorporated into low-temperature-processed CuInS2 solar cells, these films achieved power conversion efficiencies above 10%, peaking at 10.44 %.

Moving to autonomous experimentation: Growing thin films with machine learning

2025-04-02 - 2025-04

From cell phones to solar panels to quantum computers, thin films are essential to current and emerging technologies. But making functional thin films requires control. During hours-long processes, thin films form atom by atom. Small changes in data readouts can tell researchers when something is going wrong. Detecting defects as soon as possible may help scientists fix films while they're growing, saving time and money.

Researchers at Pacific Northwest National Laboratory (PNNL) are using machine learning (ML) to identify subtle changes in growing films that are imperceptible to humans, detailed in a paper published in the Journal of Vacuum Science & Technology A. Their ML program can pinpoint emerging differences in film growth data faster than human experts, an important initial step toward developing autonomous experimentation with instruments that can make data-based decisions without additional human input.

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5 Nanomaterial Innovations That Didn't Deliver (Yet)

Finely-tuned TiO? nanorod arrays enhance solar cell efficiency

Moving to autonomous experimentation: Growing thin films with machine learning

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