Ref. [BCOW17] introduced a pioneering quantum approach (coined BCOW algorithm) for solving linear differential equations with optimal error tolerance. Originally designed for a specific class of diagonalizable linear ...
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To overcome the complexity and challenges of transient γ irradiation experiments, this paper adopted pulsed lasers to simulate the transient dose rate effect (TDRE) on a commercial off-the-shelf (COTS) field-programm...
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With cars becoming the primary choice of people’s daily travel, on-board OTA upgrade technology has arisen a common concern in the automotive industry. Traditional on-board OTA upgrade technology, which adopts a meth...
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The exploration towards cost-effective filler metal for ceramics joining has always been the key issues for ceramics ***,we reveal that the Al metal prefers to spread on the ZrO_(2) based ceramic under the air heating...
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The exploration towards cost-effective filler metal for ceramics joining has always been the key issues for ceramics ***,we reveal that the Al metal prefers to spread on the ZrO_(2) based ceramic under the air heating condition,due to the geometric limit effects by in-situ formed dense Al2O3 *** by this,the joining of ZrO_(2) based ceramics was realized in air with Al metal as filler,through the diffusion of Al towards ceramic *** Al element can induce obvious interfacial bonding effect on Al2O3 layer and ZrO_(2) ceramic,where the hybridization among the Al-p,Zr-d and O-p orbitals plays a key *** in-situ formed Al2O3 layer on Al filler surface is vital for forming the fine interface(shear strength of~36 MPa),which results in the relief of lattice mismatch and peak stress at ceramic-filler metal transition interface.
We study four double-gyroid (DG) grain boundaries (GBs) with different orientations numerically using the Landau–Brazovskii free energy, including the (422) twin boundary studied recently, a network switching GB, and...
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As control modules in cars become intelligent and automated, electrical systems become more complex. Dozens or even hundreds of electronic control units (ECUs) are used in many cars. In this case, the information secu...
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As an extended version of frequent itemset patterns, periodic itemset patterns concern both the frequency and periodicity of itemsets at the same time, so they contain more information than frequent itemset patterns, ...
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Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-materialbasis, primarily due to the exponential scaling of model complexity with the number of a...
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Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-materialbasis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneckwith the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness andprecision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learningand data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralowlattice thermal conductivity (<1 Wm^(−1) K^(−1)) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, aclass of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550quaternary Heuslers, respectively.
In this paper,we propose a novel Legendre neural network combined with the extreme learning machine algorithm to solve variable coefficients linear delay differential-algebraic equations with weak ***,the solution int...
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In this paper,we propose a novel Legendre neural network combined with the extreme learning machine algorithm to solve variable coefficients linear delay differential-algebraic equations with weak ***,the solution interval is divided into multiple subintervals by weak discontinuity ***,Legendre neural network is used to eliminate the hidden layer by expanding the input pattern using Legendre polynomials on each ***,the parameters of the neural network are obtained by training with the extreme learning *** numerical examples show that the proposed method can effectively deal with the difficulty of numerical simulation caused by the discontinuities.
Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scatt...
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Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scattering(SERS) are often used to analyze the composition of fine particles to determine their physical and chemical properties as well as reaction mechanisms. However, there is no comprehensive Raman spectral library of fine particles. Furthermore, various studies that used SERS for fine-particle composition analysis showed that the uniqueness of the SERS substrates and different excitation wavelengths can produce a different spectrum for the same fine-particle component. To overcome this limitation, we conducted SERS experiments with a portable Raman spectrometer using two common SERS substrates(silver(Ag) foil and gold nanoparticles(Au NPs)) and a 785 nm laser. Herein, we introduced three main particle component types(sulfate-nitrate-ammonium(SNA), organic material, and soot) with a total of 39 chemical substances. We scanned the solid Raman, liquid Raman, and SERS spectra of these substances and constructed a fine-particle reference library containing 105 spectra. Spectral results indicated that for soot and SNA, the differences in characteristic peaks mainly originated from the solid-liquid phase transition;Ag foil had little effect on this difference, while the Au NPs caused a significant red shift in the peak positions of polycyclic aromatic hydrocarbons. Moreover, with various characteristic peak positions in the three types of spectra, we could quickly and correctly distinguish substances. We hope that this spectral library will aid in the future identification of fine particles.
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