2D hard mask material; defect identification; extreme photonic packaging.
Researchers from Penn State University and University of Chemistry and Technology Prague propose using the 2D material chromium oxychloride (CrOCl) as a hard mask, because its layered structure is resistant to plasma etching and enables it to be an effective mask at smaller thicknesses.
“This 2D material is like lasagna. It’s a layer-by-layer structure,” said Ziheng Chen, Penn State doctoral candidate in engineering science and mechanics, in a statement. “When the plasma is bombarding the surface, it will form a passivation layer. That layer becomes chemically inert and shields the material underneath from further reaction.”
The team found that 2D chromium oxychloride can be patterned separately and then transferred onto delicate materials such as flexible plastics or glass. Additionally, the surface became smoother after repeated plasma exposures, resulting in sharper, more vertical structures.
“Any bombardment you have will result in different regions having different etch rates, making it difficult to create sharp, vertical features,” said Pranavram Venkatram, Penn State doctoral candidate in engineering science and mechanics, in a statement. “With chromium oxychloride, however, bombardment effectively peels away rough regions and reveals a smoother surface beneath. Since we now have a smoother layer, redeposition of byproducts does not really happen, does not really affect the etching process and does not result in any micro-masking.”
So far, the researchers have experimented using small, exfoliated flakes of material, and note that it would need to be grown uniformly across an entire wafer to be useful for industrial manufacturing. [1]
Researchers from MIT and Oak Ridge National Laboratory built an AI model capable of classifying and quantifying defects using data from a noninvasive neutron-scattering technique. Trained on 2,000 different semiconductor materials, the model can detect up to six kinds of point defects in a material simultaneously.
The foundational model covers 56 elements in the periodic table. “The model leverages the multihead attention mechanism, just like what ChatGPT is using. It similarly extracts the difference in the data between materials with and without defects and outputs a prediction of what dopants were used and in what concentrations,” said Mouyang Cheng, a PhD candidate in the Department of Materials Science and Engineering at MIT, in a press release.
“To the human eye, these defect signals would look essentially the same,” said Mingda Li, associate professor of nuclear science and engineering at MIT, in a press release. “But the pattern recognition of AI is good enough to discern different signals and get to the ground truth. Defects are this double-edged sword. There are many good defects, but if there are too many, performance can degrade. This opens up a new paradigm in defect science.”
The researchers note that the measurement technique they used would not be easy for companies to deploy, so they plan to train a similar model using Raman spectroscopy data. They also intend to extend the method to detect features larger than point defects, such as grains and dislocations. [2]
Researchers at the National Institute of Standards and Technology (NIST) developed a photonic chip packaging process that can withstand extreme environments, including deep space, nuclear reactors, ultrahigh vacuum systems, and both extremely hot and cold temperatures.
The method utilizes hydroxide catalysis bonding (HCB), which uses a small amount of a sodium hydroxide solution to fuse the optical fiber and photonic chip surfaces at the molecular level, forming an inorganic, glasslike chemical bond.
“Our study marks a major step toward bringing the speed and efficiency of photonics into environments where conventional semiconductor chips powered by electric current and photonics chips packaged using traditional methods have not been able to operate,” said Nikolai Klimov, a NIST physicist, in a statement. “This approach creates a bond that is as resilient as the optical fiber itself. It allows photonic integrated circuits to go places they simply couldn’t go before.”
Currently, the bonding process takes several days to complete, but the researchers believe it can be dramatically shortened to be suitable for large-scale manufacturing. [3]
[1] P. Venkatram, Z. Chen, K. Mukhopadhyay, et al. Two-dimensional crystalline hard masks for high-aspect-ratio nanofabrication. Nat. Mater. (2026). https://doi.org/10.1038/s41563-026-02524-7
[2] M. Cheng, C. Fu, B. Yu, et al. A foundation model for non-destructive defect identification from vibrational spectra. Matter, 2026. https://doi.org/10.1016/j.matt.2026.102728
[3] S. H. Robinson, CH. S. S. Pavan Kumar, A. S. Rao, et al. Photonic Chip Packaging for Extreme Environments. Photon. Res. 14, 1505-1516 (2026). https://doi.org/10.1364/PRJ.565679
 |
 |
 |
 |
 |  |
 |  |
 |  |
Leave a Reply