Symmetry and optical selection rules in graphene quantum dots

Graphene quantum dots (GQD's) have optical properties which are very different from those of an extended graphene sheet. In this Article we explore how the size, shape and edge--structure of a GQD affect its optical conductivity. Using representation theory, we derive optical selection rules for regular-shaped dots, starting from the symmetry properties of the current operator. We find that, where the x- and y-components of the current operator transform with the same irreducible representation (irrep) of the point group - for example in triangular or hexagonal GQD's - the optical conductivity is independent of the polarisation of the light. On the other hand, where these components transform with different irreps - for example in rectangular GQD's - the optical conductivity depends on the polarisation of light. We find that GQD's with non-commuting point-group operations - for example dots of rectangular shape - can be distinguished from GQD's with commuting point-group operations - for example dots of triangular or hexagonal shape - by using polarized light. We carry out explicit calculations of the optical conductivity of GQD's described by a simple tight--binding model and, for dots of intermediate size, \textcolor{blue}{($10 \lesssim L \lesssim 50\ \text{nm}$)} find an absorption peak in the low--frequency range of the spectrum which allows us to distinguish between dots with zigzag and armchair edges. We also clarify the one-dimensional nature of states at the van Hove singularity in graphene, providing a possible explanation for very high exciton-binding energies. Finally we discuss the role of atomic vacancies and shape asymmetry.Comment: 24 pages, 15 figure

Metal Organic Frameworks as Promising High Surface Area Material for Work Function Gas Sensors

AbstractFloating gate FET (FGFET) gas sensors based on work function readout allows usage of a wide range of materials to be included as sensing materials. Metal-organic frameworks (MOFs) are a new group of porous materials with extreme high inner surface area that have already shown high potential for applications in gas storage and separation, catalysis and sensing. In this work, MOFs are investigated for the first time with work function readout for gas sensing applications. The results demonstrate the high potential of MOFs for use as gas receptor materials in field- effect based gas sensors

Residency time of agonists does not affect the stability of GPCR–arrestin complexes

Background and purpose: The interaction of arrestins with G-protein coupled receptors (GPCRs) desensitizes agonist-dependent receptor responses and often leads to receptor internalization. GPCRs that internalize without arrestin have been classified as "class A" GPCRs whereas "class B" GPCRs co-internalize with arrestin into endosomes. The interaction of arrestins with GPCRs requires both agonist activation and receptor phosphorylation. Here, we ask the question whether agonists with very slow off-rates can cause the formation of particularly stable receptor-arrestin complexes. Experimental approach: The stability of GPCR-arrestin-3 complexes at two class A GPCRs, the β2 -adrenoceptor and the μ opioid receptor, was assessed using two different techniques, fluorescence resonance energy transfer (FRET) and fluorescence recovery after photobleaching (FRAP) employing several ligands with very different off-rates. Arrestin trafficking was determined by confocal microscopy. Key results: Upon agonist washout, GPCR-arrestin-3 complexes showed markedly different dissociation rates in single-cell FRET experiments. In FRAP experiments, however, all full agonists led to the formation of receptor-arrestin complexes of identical stability whereas the complex between the μ receptor and arrestin-3 induced by the partial agonist morphine was less stable. Agonists with very slow off-rates could not mediate the co-internalization of arrestin-3 with class A GPCRs into endosomes. Conclusions and implications: Agonist off-rates do not affect the stability of GPCR-arrestin complexes but phosphorylation patterns do. Our results imply that orthosteric agonists are not able to pharmacologically convert class A into class B GPCRs

Electrostatic extraction of cold molecules from a cryogenic reservoir

We present a method which delivers a continuous, high-density beam of slow and internally cold polar molecules. In our source, warm molecules are first cooled by collisions with a cryogenic helium buffer gas. Cold molecules are then extracted by means of an electrostatic quadrupole guide. For ND$_3$ the source produces fluxes up to $(7 \pm ^{7}_{4}) \times 10^{10}$ molecules/s with peak densities up to $(1.0 \pm ^{1.0}_{0.6}) \times 10^9$ molecules/cm$^3$. For H$_2$CO the population of rovibrational states is monitored by depletion spectroscopy, resulting in single-state populations up to $(82 \pm 10)$.Comment: 4 pages, 4 figures, changes to the text, updated figures and reference

Intelligent self calibration tool for adaptive few-mode fiber multiplexers using multiplane light conversion

Space division multiplexing (SDM) is promising to enhance capacity limits of optical networks. Among implementation options, few-mode fibres (FMFs) offer high efficiency gains in terms of integratability and throughput per volume. However, to achieve low insertion loss and low crosstalk, the beam launching should match the fiber modes precisely. We propose an all-optical data-driven technique based on multiplane light conversion (MPLC) and neural networks (NNs). By using a phase-only spatial light modulator (SLM), spatially separated input beams are transformed independently to coaxial output modes. Compared to conventional offline calculation of SLM phase masks, we employ an intelligent two-stage approach that considers knowledge of the experimental environment significantly reducing misalignment. First, a single-layer NN called Model-NN learns the beam propagation through the setup and provides a digital twin of the apparatus. Second, another single-layer NN called Actor-NN controls the model. As a result, SLM phase masks are predicted and employed in the experiment to shape an input beam to a target output. We show results on a single-passage configuration with intensity-only shaping. We achieve a correlation between experiment and network prediction of 0.65. Using programmable optical elements, our method allows the implementation of aberration correction and distortion compensation techniques, which enables secure high-capacity long-reach FMF-based communication systems by adaptive mode multiplexing devices

Rational design of a (S)-selective-transaminase for asymmetric synthesis of (1S)-1-(1,1′-biphenyl-2-yl)ethanamine

Amine transaminases offer an environmentally sustainable synthesis route for the production of pure chiral amines. However, their catalytic efficiency toward bulky ketone substrates is greatly limited by steric hindrance and therefore presents a great challenge for industrial synthetic applications. We hereby report an example of rational transaminase enzyme design to help alleviate these challenges. Starting from the Vibrio fluvialis amine transaminase that has no detectable catalytic activity toward the bulky aromatic ketone 2-acetylbiphenyl, we employed a rational design strategy combining in silico and in vitro studies to engineer the transaminase enzyme with a minimal number of mutations, achieving an high catalytic activity and high enantioselectivity. We found that, by introducing two mutations W57G/R415A, detectable enzyme activity was achieved. The rationally designed variant, W57F/R88H/V153S/K163F/I259M/R415A/V422A, showed an improvement in reaction rate by more than 1716-fold toward the bulky ketone under study, producing the corresponding enantiomeric pure (S)-amine (enantiomeric excess (ee) value of >99%)

Deep Transfer Learning on Satellite Imagery Improves Air Quality Estimates in Developing Nations

Urban air pollution is a public health challenge in low- and middle-income countries (LMICs). However, LMICs lack adequate air quality (AQ) monitoring infrastructure. A persistent challenge has been our inability to estimate AQ accurately in LMIC cities, which hinders emergency preparedness and risk mitigation. Deep learning-based models that map satellite imagery to AQ can be built for high-income countries (HICs) with adequate ground data. Here we demonstrate that a scalable approach that adapts deep transfer learning on satellite imagery for AQ can extract meaningful estimates and insights in LMIC cities based on spatiotemporal patterns learned in HIC cities. The approach is demonstrated for Accra in Ghana, Africa, with AQ patterns learned from two US cities, specifically Los Angeles and New York

The fluvial architecture of buried floodplain sediments of the Weiße Elster River (Germany) revealed by a novel method combination of drill cores with two‐dimensional and spatially resolved geophysical measurements

The complex and non-linear fluvial river dynamics are characterized by repeated periods of fluvial erosion and re-deposition in different parts of the floodplain. Understanding the fluvial architecture (i.e. the three-dimensional arrangement and genetic interconnectedness of different sediment types) is therefore fundamental to obtain well-based information about controlling factors. However, investigating the fluvial architecture in buried floodplain deposits without natural exposures is challenging. We studied the fluvial architecture of the middle Weiße Elster floodplain in Central Germany, an extraordinary long-standing archive of Holocene flooding and landscape changes in sensitive loess-covered Central European landscapes. We applied a novel systematic approach by coupling two-dimensional transects of electrical resistivity tomography (ERT) measurements and closely spaced core drillings with spatially resolved measurements of electromagnetic induction (EMI) of larger floodplain areas at three study sites. This allowed for (i) time and cost-efficient core drillings based on preceding ERT measurements and (ii) spatially scaling up the main elements of the fluvial architecture, such as the distribution of thick silt-clay overbank deposits and paleochannel patterns from the floodplain transects to larger surrounding areas. We found that fine-grained sand and silt-clay overbank deposits overlying basal gravels were deposited during several periods of intensive flooding. Those were separated from each other by periods of reduced flooding, allowing soil formation. However, the overbank deposits were severely laterally eroded before and during each sedimentation period. This was probably linked with pronounced meandering or even braiding of the river. Our preliminary chronological classification suggests that first fine-grained sedimentation must have occurred during the Early to Middle Holocene, and the last phase of lateral erosion and sedimentation during the Little Ice Age. Our study demonstrates the high archive potential of the buried fluvial sediments of the middle Weiße Elster floodplain and provides a promising time and cost-effective approach for future studies of buried floodplain sediments