Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

Since the discovery of mechanically exfoliated graphene in 2004, research on ultrathin two-dimensional (2D) nanomaterials has grown exponentially in the fields of condensed matter physics, material science, chemistry, and nanotechnology. Highlighting their compelling physical, chemical, electronic, and optical properties, as well as their various potential applications, in this Review, we summarize the state-of-art progress on the ultrathin 2D nanomaterials with a particular emphasis on their recent advances. First, we introduce the unique advances on ultrathin 2D nanomaterials, followed by the description of their composition and crystal structures. The assortments of their synthetic methods are then summarized, including insights on their advantages and limitations, alongside some recommendations on suitable characterization techniques. We also discuss in detail the utilization of these ultrathin 2D nanomaterials for wide ranges of potential applications among the electronics/optoelectronics, electrocat...

Recent Advances in Ultrathin Two-Dimensional Nanomaterials

BiFeO3 is perhaps the only material that is both magnetic and a strong ferroelectric at room temperature. As a result, it has had an impact on the field of multiferroics that is comparable to that of yttrium barium copper oxide (YBCO) on superconductors, with hundreds of publications devoted to it in the past few years. In this Review, we try to summarize both the basic physics and unresolved aspects of BiFeO3 (which are still being discovered with several new phase transitions reported in the past few months) and device applications, which center on spintronics and memory devices that can be addressed both electrically and magnetically.

Physics and Applications of Bismuth Ferrite

N and Mn ions were co-implanted into p-type GaN and subsequently annealed at 700–900 °C. The ferromagnetic property was obtained after annealing at 800 °C. As compared with conventional Mn-implanted samples, Mn–N binary phases significantly decreased, resulting in the reduction of the N vacancies. From synchrotron radiation photoemission spectroscopy, the Ga–Mn magnetic phases, which contributed to the ferromagnetic property, were still observed after annealing at 900 °C. From these results, we propose the co-implantation of N and Mn atoms to achieve high TC ferromagnetism in GaN.

Co-implantation of Mn+N into p-type GaN for high T-C ferromagnetism

Halide perovskites (HPs) can be the effective functional materials for the sneak‐path current issue in the memristive crossbar array. Herein, an efficient strategy is proposed to integrate the HPs‐based bidirectional threshold and bipolar resistive switches (TS and RS). The resistance change characteristics from volatile threshold to nonvolatile resistive switching are modulated by controlling Ag doping concentration in the MAPbI3. HPs provide the diffusive condition and the quantity of Ag regulates the radius of its network. A low amount of Ag contributes to weak network with a short lifetime. However, when the amount of Ag increases, the conductive filament becomes more robust, showing a long lifetime. A MAPbI3:Ag TS with a low Ag content is developed, showing a steep switching slope (1 mV per decade), fast switching speed (< 80 ns), and low off‐current (10 nA). And, a MAPbI3:Ag RS with a high Ag content is developed, showing multilevel storage capability and long retention time (1400 s). Finally, these TS and RS coupled into the 1S‐1R integrated component, resulting the development of the maximum crossbar array size to 1.4 × 1012. This study offers an efficient methodology for tailoring the resistance change characteristics and a promising strategy for practical HPs‐based memristive crossbar application.

Controlling Threshold and Resistive Switch Functionalities in Ag‐Incorporated Organometallic Halide Perovskites for Memristive Crossbar Array

Method for preparing a gas sensor made of thin layers of highly sensitive nano-structure oxides

Stabilization of FCC Phase Using Mn Incorporation in Nanograin Invar Alloy Foils Fabricated by Electroforming

Recently, artificial synapses involving an electrochemical reaction of Li-ion have been attributed to have remarkable synaptic properties. Three-terminal synaptic transistors utilizing Li-ion intercalation exhibits reliable synaptic characteristics by exploiting the advantage of non-distributed weight updates owing to stable ion migrations. However, the three-terminal configurations with large and complex structures impede the crossbar array implementation required for hardware neuromorphic systems. Meanwhile, achieving adequate synaptic performances through effective Li-ion intercalation in vertical two-terminal synaptic devices for array integration remains challenging. Here, two-terminal Au/LixCoO2/Pt artificial synapses are proposed with the potential for practical implementation of hardware neural networks. The Au/LixCoO2/Pt devices demonstrated extraordinary neuromorphic behaviors based on a progressive dearth of Li in LixCoO2 films. The intercalation and deintercalation of Li-ion inside the films are precisely controlled over the weight control spike, resulting in improved weight control functionality. Various types of synaptic plasticity were imitated and assessed in terms of key factors such as nonlinearity, symmetricity, and dynamic range. Notably, the LixCoO2-based neuromorphic system outperformed three-terminal synaptic transistors in simulations of convolutional neural networks and multilayer perceptrons due to the high linearity and low programming error. These impressive performances suggest the vertical two-terminal Au/LixCoO2/Pt artificial synapses as promising candidates for hardware neural networks. 

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Ho Won Jang

Papers

Co-implantation of Mn+N into p-type GaN for high T-C ferromagnetism

Controlling Threshold and Resistive Switch Functionalities in Ag‐Incorporated Organometallic Halide Perovskites for Memristive Crossbar Array

Method for preparing a gas sensor made of thin layers of highly sensitive nano-structure oxides

Stabilization of FCC Phase Using Mn Incorporation in Nanograin Invar Alloy Foils Fabricated by Electroforming

Two-Terminal Lithium-Mediated Artificial Synapses with Enhanced Weight Modulation for Feasible Hardware Neural Networks