Andras Kis

Bio: Andras Kis is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Monolayer & Semiconductor. The author has an hindex of 67, co-authored 165 publications receiving 53990 citations. Previous affiliations of Andras Kis include École Normale Supérieure & Lawrence Berkeley National Laboratory.

Super-resolved Optical Mapping of Reactive Sulfur-Vacancies in Two-Dimensional Transition Metal Dichalcogenides.

Abstract: Transition metal dichalcogenides (TMDs) represent a class of semiconducting two-dimensional (2D) materials with exciting properties. In particular, defects in 2D-TMDs and their molecular interactions with the environment can crucially affect their physical and chemical properties. However, mapping the spatial distribution and chemical reactivity of defects in liquid remains a challenge. Here, we demonstrate large area mapping of reactive sulfur-deficient defects in 2D-TMDs in aqueous solutions by coupling single-molecule localization microscopy with fluorescence labeling using thiol chemistry. Our method, reminiscent of PAINT strategies, relies on the specific binding of fluorescent probes hosting a thiol group to sulfur vacancies, allowing localization of the defects with an uncertainty down to 15 nm. Tuning the distance between the fluorophore and the docking thiol site allows us to control Foster resonance energy transfer (FRET) process and reveal grain boundaries and line defects due to the local irregular lattice structure. We further characterize the binding kinetics over a large range of pH conditions, evidencing the reversible adsorption of the thiol probes to the defects with a subsequent transitioning to irreversible binding in basic conditions. Our methodology provides a simple and fast alternative for large-scale mapping of nonradiative defects in 2D materials and can be used for in situ and spatially resolved monitoring of the interaction between chemical agents and defects in 2D materials that has general implications for defect engineering in aqueous condition.

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Abstract: Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electronics requires increased energy efficiency of processors for specialized data-driven applications. Here, we show how an in-memory processor fabricated using a two-dimensional materials platform can potentially outperform its silicon counterparts in both standard and nontraditional Von Neumann architectures for artificial neural networks. We have fabricated a flash memory array with a two-dimensional channel using wafer-scale MoS2. Simulations and experiments show that the device can be scaled down to sub-micrometer channel length without any significant impact on its memory performance and that in simulation a reasonable memory window still exists at sub-50 nm channel lengths. Each device conductance in our circuit can be tuned with a 4-bit precision by closed-loop programming. Using our physical circuit, we demonstrate seven-segment digit display classification with a 91.5% accuracy with training performed ex situ and transferred from a host. Further simulations project that at a system level, the large memory arrays can perform AlexNet classification with an upper limit of 50 000 TOpS/W, potentially outperforming neural network integrated circuits based on double-poly CMOS technology.

Optospintronics in graphene via proximity coupling

Abstract: The observation of micrometer size spin relaxation makes graphene a promising material for applications in spintronics requiring long-distance spin communication. However, spin dependent scatterings at the contact/graphene interfaces affect the spin injection efficiencies and hence prevent the material from achieving its full potential. While this major issue could be eliminated by nondestructive direct optical spin injection schemes, graphene’s intrinsically low spin–orbit coupling strength and optical absorption place an obstacle in their realization. We overcome this challenge by creating sharp artificial interfaces between graphene and WSe2 monolayers. Application of circularly polarized light activates the spin-polarized charge carriers in the WSe2 layer due to its spin-coupled valley-selective absorption. These carriers diffuse into the superjacent graphene layer, transport over a 3.5 μm distance, and are finally detected electrically using Co/h-BN contacts in a nonlocal geometry. Polarization-depen...

Electrical control of glass-like dynamics in vanadium dioxide for data storage and processing

Abstract: Metal–oxide–semiconductor junctions are the building blocks of modern electronics and can provide a variety of functionalities, from memory to computing. The technology, however, faces constraints in terms of further miniaturization and compatibility with post–von Neumann computing architectures. Manipulation of structural—rather than electronic—states could provide a path to ultrascaled low-power functional devices, but the electrical control of such states is challenging. Here we report electronically accessible long-lived structural states in vanadium dioxide that can provide a scheme for data storage and processing. The states can be arbitrarily manipulated on short timescales and tracked beyond 10,000 s after excitation, exhibiting features similar to glasses. In two-terminal devices with channel lengths down to 50 nm, sub-nanosecond electrical excitation can occur with an energy consumption as small as 100 fJ. These glass-like functional devices could outperform conventional metal–oxide–semiconductor electronics in terms of speed, energy consumption and miniaturization, as well as provide a route to neuromorphic computation and multilevel memories. Electronically accessible states in vanadium dioxide can be arbitrarily manipulated on short timescales and tracked beyond 10,000 s after excitation.

Fast parallel algorithms for short-range molecular dynamics

Abstract: 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.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Electronics and optoelectronics of two-dimensional transition metal dichalcogenides.

Abstract: Single-layer metal dichalcogenides are two-dimensional semiconductors that present strong potential for electronic and sensing applications complementary to that of graphene.