Compression sensing can help build a microscope that can image molecular vibrations with higher resolution and in less time than conventional methods allow, creating a powerful new tool for chemists to study interfaces and image biomolecular structures. Compression is generally thought of as something to do to data after it has been collected. For instance, when people email large photos to one another, they often compress the images, removing redundant information and reducing file size, and mathematicians recently figured out a way to apply similar principles to drastically reduce the amount of data that needs to be gathered in the first place. Scientists from the University of Houston and Rice University have built a microscope that images molecular vibrations faster and with higher resolutions than are available with traditional methods, all thanks to compression sensing. The main concept behind compressive sensing is sparsity. If something is sparse, the most important information is concentrated in select parts of the signal, with the rest containing redundant information that is mathematically represented as zero or near-zero numbers. The researchers’ sparse signal came from a sum frequency generation (SFG) microscope, which shines two different-frequency lasers at a surface and then measures the return signal to gather information about the vibration and orientation of the molecules at the surface boundary. Traditional SFG microscopes scan a sample by systematically moving across it, but their resolution is limited. Unlike SFG microscopes, the compressive sensing microscope gathers a set of pseudo-randomly positioned sampling points. If the important information was captured in the sample, a series of mathematical steps could be used to construct the image in its entirety. The researchers tested their microscope by imaging stripes of gold deposited on a silicon background and then coated with a chemical bond called octadecanethiol. The device was able to sense the stretch of carbon-hydrogen bonds in the chemical layer and created images with 16 times more pixel density than was possible with traditional scanning methods. The team is pursuing a variety of systems to further the research, looking at self-assembled monolayers on dielectric surfaces like glass and oxides. The researchers also are interested in chemical systems that form patterns on surfaces such as phase transformations in Gibbs monolayers, said Steven Baldelli of the University of Houston. The research appeared online Nov. 17 in the Journal of Chemical Physics (doi: 10.1063/1.3660202).