High-silica CHA zeolite membranes are highly desired for natural gas upgrading because of their separation performance in combination with superior mechanical and chemical stability. However, the narrow synthesis condition range significantly constrains scale-up preparation. Herein, we propose a facile interzeolite conversion approach using the FAU zeolite to prepare SSZ-13 zeolite seeds, featuring a shorter induction and a longer crystallization period of the membrane synthesis on hollow fiber substrates. The membrane thickness was constant at ~3 μm over a wide span of synthesis time (24-96 h), while the selectivity (separation efficiency) was easily improved by extending the synthesis time without compromising permeance (throughput). At 0.2 MPa feed pressure and 303 K, the membranes showed an average CO2 permeance of (5.2±0.5)×10−7 mol m−2 s−1 Pa−1 (1530 GPU), with an average CO2/CH4 mixture selectivity of 143±7. Minimal defects ensure a high selectivity of 126 with a CO2 permeation flux of 0.4 mol m−2 s−1 at 6.1 MPa feed pressure, far surpassing requirements for industrial applications. The feasibility for successful scale-up of our approach was further demonstrated by the batch synthesis of 40 cm-long hollow fiber SSZ-13 zeolite membranes exhibiting CO2/CH4 mixture selectivity up to 400 (0.2 MPa feed pressure and 303 K) without using sweep gas.@en

The successful testing of non-Abelian statistics not only serves as a milestone in fundamental physics but also provides a quantum-gate operation in topological quantum computation. An accurate and efficient readout scheme of a topological qubit is an essential step toward the experimental confirmation of non-Abelian statistics. In the current work, we propose a protocol to read out the quantum state of a Majorana vortex qubit on a topological superconductor island. The protocol consists of four Majorana zero modes trapped in spatially well-separated vortex cores on the two-dimensional surface of a Coulomb blockaded topological superconductor. Our proposed measurement is implemented by a pair of weakly coupled Majorana modes separately in touch with two normal-metal leads and the readout is realized by observing the conductance-peak location in terms of the gate voltage. Using this protocol, we can further test the non-Abelian statistics of Majorana zero modes in the two-dimensional platform. A successful readout of a Majorana qubit is a crucial step toward the future application of topological quantum computation. In addition, this Coulomb-blockaded setup can distinguish Majorana zero modes from Caroli-de Gennes-Matricon modes in vortex cores.

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Sensor arrays also known as Electronic Noses (ENs) have been used to analyse the Volatile Organic Compounds (VOCs) of both healthy and infected tomato (Solanum lycopersicum) crops. Statistical and intelligent systems techniques were employed to process the data collected by an EN. Principal Component Analysis (PCA), K-Means clustering and Fuzzy C-Mean (FCM) clustering were applied to visualise any clusters within the dataset. Furthermore, Multi-Layer Perceptron (MLP), Learning Vector Quantization (LVQ) and Radial Basis Function (RBF) based Artificial Neural Network (ANNs) were used to learn to classify and hence categorise the datasets. Using the RBF, MLP and LVQ techniques we achieved 94, 96 and 98% classification accuracy for the healthy, powdery mildew (Oidium lycopersicum) and spider mite infected plants respectively. From these results it is evident that EN is capable of discriminating between the healthy and artificially infected tomato plants and hence may be deployed as a potential early disease detection tool for tomato crops in commercial greenhouses.@en