63 research outputs found

    Nanoscale Quantification of Octahedral Tilts in Perovskite Films

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    NiO6-octahedral tilts in ultrathin LaNiO3 films were studied using position averaged convergent beam electron diffraction (PACBED) in scanning transmission electron microscopy. Both the type and magnitude of the octahedral tilts were determined by comparing PACBED experiments to frozen phonon multislice simulations. It is shown that the out-of-plane octahedral tilt of an epitaxial film under biaxial tensile stress (0.78 % in-plane tensile strain) increases by ~ 20%, while the in-plane rotation decreases by ~ 80%, compared to the unstrained bulk material.Comment: The manuscript has been accepted by Applied Physics Letters. After it is published, it will be found at: http://apl.aip.org

    Structural origins of the properties of rare earth nickelate superlattices

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    NiO6 octahedral tilts in the LaNiO3/SrTiO3 superlattices are quantified using position averaged convergent beam electron diffraction in scanning transmission electron microscopy. It is shown that maintaining oxygen octahedra connectivity across the interface controls the octahedral tilts in the LaNiO3 layers, their lattice parameters and their transport properties. Unlike films and layers that are connected on one side to the substrate, subsequent LaNiO3 layers in the superlattice exhibit a relaxation of octahedral tilts towards bulk values. This relaxation is facilitated by correlated tilts in SrTiO3 layers and is correlated with the conductivity enhancement of the LaNiO3 layers in the superlattices relative to individual films.Comment: Accepted for publication in Physical Review B (Rapid Communication

    Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss

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    Reducing bit-widths of activations and weights of deep networks makes it efficient to compute and store them in memory, which is crucial in their deployments to resource-limited devices, such as mobile phones. However, decreasing bit-widths with quantization generally yields drastically degraded accuracy. To tackle this problem, we propose to learn to quantize activations and weights via a trainable quantizer that transforms and discretizes them. Specifically, we parameterize the quantization intervals and obtain their optimal values by directly minimizing the task loss of the network. This quantization-interval-learning (QIL) allows the quantized networks to maintain the accuracy of the full-precision (32-bit) networks with bit-width as low as 4-bit and minimize the accuracy degeneration with further bit-width reduction (i.e., 3 and 2-bit). Moreover, our quantizer can be trained on a heterogeneous dataset, and thus can be used to quantize pretrained networks without access to their training data. We demonstrate the effectiveness of our trainable quantizer on ImageNet dataset with various network architectures such as ResNet-18, -34 and AlexNet, on which it outperforms existing methods to achieve the state-of-the-art accuracy

    Effects of NaOH Activation on Adsorptive Removal of Herbicides by Biochars Prepared from Ground Coffee Residues

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    In this study, the adsorption of herbicides using ground coffee residue biochars without (GCRB) and with NaOH activation (GCRB-N) was compared to provide deeper insights into their adsorption behaviors and mechanisms. The physicochemical characteristics of GCRB and GCRB-N were analyzed using Brunauer-Emmett-Teller surface area, Fourier transform infrared spectroscopy, scanning electron microscopy, and X-ray diffraction and the effects of pH, temperature, ionic strength, and humic acids on the adsorption of herbicides were identified. Moreover, the adsorption kinetics and isotherms were studied. The specific surface area and total pore volume of GCRB-N (405.33 m(2)/g and 0.293 cm(3)/g) were greater than those of GCRB (3.83 m(2)/g and 0.014 cm(3)/g). The GCBR-N could more effectively remove the herbicides (Q(e,exp) of Alachlor = 122.71 mu mol/g, Q(e,exp) of Diuron = 166.42 mu mol/g, and Q(e,exp) of Simazine = 99.16 mu mol/g) than GCRB (Q(e,exp) of Alachlor = 11.74 mu mol/g, Q(e,exp) of Diuron = 9.95 mu mol/g, and Q(e,exp) of Simazine = 6.53 mu mol/g). These results suggested that chemical activation with NaOH might be a promising option to make the GCRB more practical and effective for removing herbicides in the aqueous solutions

    Optimal battery electric bus planning and its economic and environmental impacts

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    Battery electric buses (BEB) have attracted attention as future eco-friendly public transit. However, planning a large-scale BEB system is challenging, with additional constraints related to charging facilities and batteries. We present a bi-objective decision-making framework to minimize the overall cost and greenhouse gas emissions, robust to operational uncertainty and applicable to various real-world scenarios. We propose a tractable queuing-theoretic solution method to determine three optimal planning factors: charging infrastructure, fleet size, and battery capacity. We demonstrate the proposed method in a numerical example and derive the following practical insights. First, sharing chargers among BEBs assigned to different routes is beneficial, but pooling BEB fleets does not always guarantee economic and environmental benefits. Second, the optimal BEB system, while not the most economically preferable option, provides the maximum environmental benefit compared to conventional non-fully-electrified systems. Additionally, through a sensitivity study, we show the necessity of accurately evaluating electricity consumption stochasticity
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