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Transparent ferroelectric crystals with ultrahigh piezoelectricity 期刊论文
NATURE, 2020, 577 (7790) : 350-+
作者:  Qiu, Chaorui;  Wang, Bo;  Zhang, Nan;  Zhang, Shujun;  Liu, Jinfeng;  Walker, David;  Wang, Yu;  Tian, Hao;  Shrout, Thomas R.;  Xu, Zhuo;  Chen, Long-Qing;  Li, Fei
收藏  |  浏览/下载:43/0  |  提交时间:2020/07/03

Transparent piezoelectrics are highly desirable for numerous hybrid ultrasound-optical devices ranging from photoacoustic imaging transducers to transparent actuators for haptic applications(1-7). However, it is challenging to achieve high piezoelectricity and perfect transparency simultaneously because most high-performance piezoelectrics are ferroelectrics that contain high-density light-scattering domain walls. Here, through a combination of phase-field simulations and experiments, we demonstrate a relatively simple method of using an alternating-current electric field to engineer the domain structures of originally opaque rhombohedral Pb(Mg1/3Nb2/3)O-3-PbTiO3 (PMN-PT) crystals to simultaneously generate near-perfect transparency, an ultrahigh piezoelectric coefficient d(33) (greater than 2,100 picocoulombs per newton), an excellent electromechanical coupling factor k(33) (about 94 per cent) and a large electro-optical coefficient gamma(33) (approximately 220 picometres per volt), which is far beyond the performance of the commonly used transparent ferroelectric crystal LiNbO3. We find that increasing the domain size leads to a higher d(33) value for the [001]-oriented rhombohedral PMN-PT crystals, challenging the conventional wisdom that decreasing the domain size always results in higher piezoelectricity(8-10). This work presents a paradigm for achieving high transparency and piezoelectricity by ferroelectric domain engineering, and we expect the transparent ferroelectric crystals reported here to provide a route to a wide range of hybrid device applications, such as medical imaging, self-energy-harvesting touch screens and invisible robotic devices.


  
Quantum entanglement between an atom and a molecule 期刊论文
NATURE, 2020, 581 (7808) : 273-+
作者:  Trisos, Christopher H.;  Merow, Cory;  Pigot, Alex L.
收藏  |  浏览/下载:44/0  |  提交时间:2020/07/03

Conventional information processors convert information between different physical carriers for processing, storage and transmission. It seems plausible that quantum information will also be held by different physical carriers in applications such as tests of fundamental physics, quantum enhanced sensors and quantum information processing. Quantum controlled molecules, in particular, could transduce quantum information across a wide range of quantum bit (qubit) frequencies-from a few kilohertz for transitions within the same rotational manifold(1), a few gigahertz for hyperfine transitions, a few terahertz for rotational transitions, to hundreds of terahertz for fundamental and overtone vibrational and electronic transitions-possibly all within the same molecule. Here we demonstrate entanglement between the rotational states of a (CaH+)-Ca-40 molecular ion and the internal states of a Ca-40(+) atomic ion(2). We extend methods used in quantum logic spectroscopy(1,3) for pure-state initialization, laser manipulation and state readout of the molecular ion. The quantum coherence of the Coulomb coupled motion between the atomic and molecular ions enables subsequent entangling manipulations. The qubit addressed in the molecule has a frequency of either 13.4 kilohertz(1) or 855 gigahertz(3), highlighting the versatility of molecular qubits. Our work demonstrates how molecules can transduce quantum information between qubits with different frequencies to enable hybrid quantum systems. We anticipate that our method of quantum control and measurement of molecules will find applications in quantum information science, quantum sensors, fundamental and applied physics, and controlled quantum chemistry.


Quantum entanglement is realized between rotational levels of a molecular ion with energy differences spanning several orders of magnitude and long-lived internal states of a single atomic ion.


  
Coherent electrical control of a single high-spin nucleus in silicon 期刊论文
NATURE, 2020, 579 (7798) : 205-+
作者:  Dedoussi, Irene C.;  Eastham, Sebastian D.;  Monier, Erwan;  Barrett, Steven R. H.
收藏  |  浏览/下载:23/0  |  提交时间:2020/07/03

Nuclear spins are highly coherent quantum objects. In large ensembles, their control and detection via magnetic resonance is widely exploited, for example, in chemistry, medicine, materials science and mining. Nuclear spins also featured in early proposals for solid-state quantum computers(1) and demonstrations of quantum search(2) and factoring(3) algorithms. Scaling up such concepts requires controlling individual nuclei, which can be detected when coupled to an electron(4-6). However, the need to address the nuclei via oscillating magnetic fields complicates their integration in multi-spin nanoscale devices, because the field cannot be localized or screened. Control via electric fields would resolve this problem, but previous methods(7-9) relied on transducing electric signals into magnetic fields via the electron-nuclear hyperfine interaction, which severely affects nuclear coherence. Here we demonstrate the coherent quantum control of a single Sb-123 (spin-7/2) nucleus using localized electric fields produced within a silicon nanoelectronic device. The method exploits an idea proposed in 1961(10) but not previously realized experimentally with a single nucleus. Our results are quantitatively supported by a microscopic theoretical model that reveals how the purely electrical modulation of the nuclear electric quadrupole interaction results in coherent nuclear spin transitions that are uniquely addressable owing to lattice strain. The spin dephasing time, 0.1 seconds, is orders of magnitude longer than those obtained by methods that require a coupled electron spin to achieve electrical driving. These results show that high-spin quadrupolar nuclei could be deployed as chaotic models, strain sensors and hybrid spin-mechanical quantum systems using all-electrical controls. Integrating electrically controllable nuclei with quantum dots(11,12) could pave the way to scalable, nuclear- and electron-spin-based quantum computers in silicon that operate without the need for oscillating magnetic fields.


  
Fully hardware-implemented memristor convolutional neural network 期刊论文
NATURE, 2020, 577 (7792) : 641-+
作者:  Yoshioka-Kobayashi, Kumiko;  Matsumiya, Marina;  Niino, Yusuke;  Isomura, Akihiro;  Kori, Hiroshi;  Miyawaki, Atsushi;  Kageyama, Ryoichiro
收藏  |  浏览/下载:56/0  |  提交时间:2020/07/03

Memristor-enabled neuromorphic computing systems provide a fast and energy-efficient approach to training neural networks(1-4). However, convolutional neural networks (CNNs)-one of the most important models for image recognition(5)-have not yet been fully hardware-implemented using memristor crossbars, which are cross-point arrays with a memristor device at each intersection. Moreover, achieving software-comparable results is highly challenging owing to the poor yield, large variation and other non-ideal characteristics of devices(6-9). Here we report the fabrication of high-yield, high-performance and uniform memristor crossbar arrays for the implementation of CNNs, which integrate eight 2,048-cell memristor arrays to improve parallel-computing efficiency. In addition, we propose an effective hybrid-training method to adapt to device imperfections and improve the overall system performance. We built a five-layer memristor-based CNN to perform MNIST10 image recognition, and achieved a high accuracy of more than 96 per cent. In addition to parallel convolutions using different kernels with shared inputs, replication of multiple identical kernels in memristor arrays was demonstrated for processing different inputs in parallel. The memristor-based CNN neuromorphic system has an energy efficiency more than two orders of magnitude greater than that of state-of-the-art graphics-processing units, and is shown to be scalable to larger networks, such as residual neural networks. Our results are expected to enable a viable memristor-based non-von Neumann hardware solution for deep neural networks and edge computing.


  
Development of a hybrid model to interpolate monthly precipitation maps incorporating the orographic influence 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019, 39 (10) : 3962-3975
作者:  Alvarez-Rodriguez, Javier;  Llasat, Maria-Carmen;  Estrela, Teodoro
收藏  |  浏览/下载:26/0  |  提交时间:2019/11/27
hybrid method  interpolation  monthly precipitation  orography  Spain  
East Asian winter monsoon forecasting schemes based on the NCEP's climate forecast system 期刊论文
CLIMATE DYNAMICS, 2018, 51: 2793-2805
作者:  Tian, Baoqiang;  Fan, Ke;  Yang, Hongqing
收藏  |  浏览/下载:16/0  |  提交时间:2019/04/09
East Asian winter monsoon  Year-to-year increment method  Hybrid prediction  CFSv2