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Scientists at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory have gained important new insight into how the performance of a promising semiconducting thin film can be optimized at the nanoscale for renewable energy technologies such as solar fuels.
Scientists at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory have gained important new insight into how the performance of a promising semiconducting thin film can be optimized at the nanoscale for renewable energy technologies such as solar fuels.
On Feb. 18, 2020, a team of scientists from the National Institute of Standards and Technology reported something surprising about a 2-D magnetic material: Behavior that had long been presumed to be due to vibrations in the lattice—the internal structure of the atoms in the material itself—is actually due to a wave of spin oscillations. This week, the same group describes another surprise finding in a different 2-D magnetic material: Behavior presumed to be due to a wave of spin oscillations is actually due to vibrations in the lattice.
On Feb. 18, 2020, a team of scientists from the National Institute of Standards and Technology reported something surprising about a 2-D magnetic material: Behavior that had long been presumed to be due to vibrations in the lattice—the internal structure of the atoms in the material itself—is actually due to a wave of spin oscillations. This week, the same group describes another surprise finding in a different 2-D magnetic material: Behavior presumed to be due to a wave of spin oscillations is actually due to vibrations in the lattice.
Scientists at The University of Texas at Dallas have described how the ability of twisted bilayer graphene to conduct electrical current changes in response to mid-infrared light. When the graphene layers are misaligned, a new periodic design in the mesh emerges, so the scientists determined how mid-infrared light affected the conductance of electrons in this new periodic design.
Scientists at The University of Texas at Dallas have described how the ability of twisted bilayer graphene to conduct electrical current changes in response to mid-infrared light. When the graphene layers are misaligned, a new periodic design in the mesh emerges, so the scientists determined how mid-infrared light affected the conductance of electrons in this new periodic design.
Mimicking the structure of the kidney, scientists from Lawrence Livermore National Laboratory and the University of Illinois at Chicago have created a three-dimensional nanometer-thin membrane composed of two 3D interconnected channels, which are separated by a nanometer-thin porous titanium oxide layer. This unique biomimetic 3D architecture dramatically increases the surface area, and thus the filtration area, by 6,000 times, coupled with an ultra-short diffusion distance through the 2–4 nanometer-thin selective layer.
Mimicking the structure of the kidney, scientists from Lawrence Livermore National Laboratory and the University of Illinois at Chicago have created a three-dimensional nanometer-thin membrane composed of two 3D interconnected channels, which are separated by a nanometer-thin porous titanium oxide layer. This unique biomimetic 3D architecture dramatically increases the surface area, and thus the filtration area, by 6,000 times, coupled with an ultra-short diffusion distance through the 2–4 nanometer-thin selective layer.
Two-photon lithography is a widely used 3-D nanoprinting technique that can print nanoscale features at very high resolution by focusing an intense beam of light on a precise spot within a liquid photopolymer material. Scientists at Lawrence Livermore National Laboratory and collaborators have turned to machine learning to address two key barriers to industrialization of two-photon lithography: monitoring of parts’ quality during printing and determining the right light dosage for a given material.
Two-photon lithography is a widely used 3-D nanoprinting technique that can print nanoscale features at very high resolution by focusing an intense beam of light on a precise spot within a liquid photopolymer material. Scientists at Lawrence Livermore National Laboratory and collaborators have turned to machine learning to address two key barriers to industrialization of two-photon lithography: monitoring of parts’ quality during printing and determining the right light dosage for a given material.
