The nano-inclusion in a matrix effectively scatters phonons and the band bending effect at the interfaces can selectively scatter carriers, resulting in the enhancement of thermoelectric performance.
We propose a multiple descriptor multiple kernel (MultiDK) method for efficient molecular discovery using machine learning. We show that the MultiDK method improves both the speed and the accuracy of molecular property prediction. We apply the method to the discovery of electrolyte molecules for aqueous redox flow batteries. Using \emph{multiple-type - as opposed to single-type - descriptors}, more relevant features for machine learning can be obtained. Following the principle of the 'wisdom of the crowds', the combination of multiple-type descriptors significantly boosts prediction performance. Moreover, MultiDK can exploit irregularities between molecular structure and property relations better than the linear regression method by employing multiple kernels - more than one kernel functions for a set of the input descriptors. The multiple kernels consist of the Tanimoto similarity function and a linear kernel for a set of binary descriptors and a set of non-binary descriptors, respectively. Using MultiDK, we achieve average performance of $r^2 = 0.92$ with a set of molecules for solubility prediction. We also extend MultiDK to predict pH-dependent solubility and apply it to solubility estimation of quinone molecules with ionizable functional groups as strong candidates of flow battery electrolytes.
A new version of the well-known FSK (Frequency-Shift Keying) modulation technique for telecommunication system was proposed and verified. A simple form of ring oscillator with three inverters was adopted for the basic frequency generator. The frequency shift was realized using a ring oscillator composed of nine inverters. CMOS multiplexers were used to select one of two different oscillators, i.e., to shift between two different frequencies. Simulations were performed for the verification.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
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