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“Proton and Li-Ion permeation through graphene with eight-atom-ring defects”. Griffin E, Mogg L, Hao G-P, Kalon G, Bacaksiz C, Lopez-Polin G, Zhou TY, Guarochico V, Cai J, Neumann C, Winter A, Mohn M, Lee JH, Lin J, Kaiser U, Grigorieva I V, Suenaga K, Ozyilmaz B, Cheng H-M, Ren W, Turchanin A, Peeters FM, Geim AK, Lozada-Hidalgo M, Acs Nano 14, 7280 (2020). http://doi.org/10.1021/ACSNANO.0C02496
Abstract: Defect-free graphene is impermeable to gases and liquids but highly permeable to thermal protons. Atomic-scale defects such as vacancies, grain boundaries, and Stone-Wales defects are predicted to enhance graphene's proton permeability and may even allow small ions through, whereas larger species such as gas molecules should remain blocked. These expectations have so far remained untested in experiment. Here, we show that atomically thin carbon films with a high density of atomic-scale defects continue blocking all molecular transport, but their proton permeability becomes similar to 1000 times higher than that of defect-free graphene. Lithium ions can also permeate through such disordered graphene. The enhanced proton and ion permeability is attributed to a high density of eight-carbon-atom rings. The latter pose approximately twice lower energy barriers for incoming protons compared to that of the six-atom rings of graphene and a relatively low barrier of similar to 0.6 eV for Li ions. Our findings suggest that disordered graphene could be of interest as membranes and protective barriers in various Li-ion and hydrogen technologies.
Keywords: A1 Journal article; Engineering sciences. Technology; Condensed Matter Theory (CMT)
Impact Factor: 17.1
Times cited: 34
DOI: 10.1021/ACSNANO.0C02496
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“Efficient first principles simulation of electron scattering factors for transmission electron microscopy”. Susi T, Madsen J, Ludacka U, Mortensen JJ, Pennycook TJ, Lee Z, Kotakoski J, Kaiser U, Meyer JC, Ultramicroscopy 197, 16 (2019). http://doi.org/10.1016/J.ULTRAMIC.2018.11.002
Abstract: Electron microscopy is a powerful tool for studying the properties of materials down to their atomic structure. In many cases, the quantitative interpretation of images requires simulations based on atomistic structure models. These typically use the independent atom approximation that neglects bonding effects, which may, however, be measurable and of physical interest. Since all electrons and the nuclear cores contribute to the scattering potential, simulations that go beyond this approximation have relied on computationally highly demanding all-electron calculations. Here, we describe a new method to generate ab initio electrostatic potentials when describing the core electrons by projector functions. Combined with an interface to quantitative image simulations, this implementation enables an easy and fast means to model electron scattering. We compare simulated transmission electron microscopy images and diffraction patterns to experimental data, showing an accuracy equivalent to earlier all-electron calculations at a much lower computational cost.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 3
DOI: 10.1016/J.ULTRAMIC.2018.11.002
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“3D imaging of nanomaterials by discrete tomography”. Batenburg KJ, Bals S, Sijbers J, Kübel C, Midgley PA, Hernandez JC, Kaiser U, Encina ER, Coronado EA, Van Tendeloo G, Ultramicroscopy 109, 730 (2009). http://doi.org/10.1016/j.ultramic.2009.01.009
Abstract: The field of discrete tomography focuses on the reconstruction of samples that consist of only a few different materials. Ideally, a three-dimensional (3D) reconstruction of such a sample should contain only one grey level for each of the compositions in the sample. By exploiting this property in the reconstruction algorithm, either the quality of the reconstruction can be improved significantly, or the number of required projection images can be reduced. The discrete reconstruction typically contains fewer artifacts and does not have to be segmented, as it already contains one grey level for each composition. Recently, a new algorithm, called discrete algebraic reconstruction technique (DART), has been proposed that can be used effectively on experimental electron tomography datasets. In this paper, we propose discrete tomography as a general reconstruction method for electron tomography in materials science. We describe the basic principles of DART and show that it can be applied successfully to three different types of samples, consisting of embedded ErSi2 nanocrystals, a carbon nanotube grown from a catalyst particle and a single gold nanoparticle, respectively.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 220
DOI: 10.1016/j.ultramic.2009.01.009
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