(Funded by the U.S. Department of Energy and the U.S. National Science Foundation)
For more than 100 years, scientists have used a method called crystallography to determine the atomic structure of materials, but this technique only works well when researchers have large, pure crystals. For a powder of nanocrystals, the method only hints at the unseen structure. Now, scientists at Columbia Engineering have created a machine learning algorithm that can observe the pattern produced by a powder of nanocrystals to infer their atomic structures. The scientists began with a dataset of 40,000 crystal structures and jumbled their atomic positions until they were indistinguishable from random placement. Then, they trained a deep neural network to connect these almost randomly placed nanocrystals with their associated X-ray diffraction patterns. Lastly, the algorithm was able to determine the atomic structure from nanocrystals of various shapes in the powder.

(Funded by the U.S. Department of Energy and the U.S. National Science Foundation)
Hydrogen fuel cells rely on proton exchange membranes to conduct protons while preventing the unwanted crossover of hydrogen molecules. Thinner membranes can improve performance but also allow more hydrogen molecules to leak through, reducing overall efficiency. So, researchers from Vanderbilt University, along with international collaborators, have developed a way to improve fuel cell efficiency without reducing its performance. By incorporating a monolayer of graphene – an ultra-thin material just one atom thick – into proton exchange membranes, the team significantly reduced hydrogen crossover by more than 50% while maintaining high proton conductivity. Part of the research work was performed at the Vanderbilt Institute of Nanoscale Science and Engineering.

(Funded by the U.S. Department of Energy and the U.S. National Science Foundation)
Researchers have long recognized that quantum communication systems would transmit quantum information better and be unaffected by certain forms of error if nonlinear optical processes were used. But past efforts at using such processes could not operate with the very low light levels required for quantum communication. Now, researchers at the University of Illinois Urbana-Champaign have improved the technology by basing the nonlinear process on an indium-gallium-phosphide nanophotonic platform. The result requires much less light and operates all the way down to single photons, the smallest units of light.

(Funded by the U.S. Department of Energy and the U.S. National Science Foundation)
Scientists at Penn State have developed a new design for thermogels – materials that can be injected as a liquid and turn into a solid inside our bodies – that further improves these materials’ properties. The newly designed thermogels are made with nanoparticles that have sticky spots, similar to arms reaching out and giving the nanoparticles places to connect with one another and form a structure. The method may be especially appealing for soft tissue reconstruction, in which case thermogels could serve as structures that provide a framework for cells to stick to and form new, healthy tissue.

(Funded by the U.S. Department of Energy)
Modern electron microscopes can capture incredibly detailed images of materials down to the atomic level, but they require a skilled operator and can only focus on very small areas at a time. Now, researchers from the U.S. Department of Energy’s (DOE) Lawrence Berkeley National Laboratory (Berkeley Lab) and the University of California, Berkeley, have created a n automated workflow that overcomes these limitations by allowing large amounts of data to be collected over wide areas without human intervention and then quickly transferred to supercomputers for real-time processing. Much of the work was done at The Molecular Foundry and the National Energy Research Scientific Computing Center, two DOE Office of Science user facilities at Berkeley Lab.