Andre K. Geim

Bio: Andre K. Geim is an academic researcher from University of Manchester. The author has contributed to research in topics: Graphene & Magnetic field. The author has an hindex of 125, co-authored 445 publications receiving 206833 citations. Previous affiliations of Andre K. Geim include University of Nottingham & Russian Academy of Sciences.

Atomically thin micas as proton-conducting membranes.

Abstract: Monolayers of graphene and hexagonal boron nitride (hBN) are highly permeable to thermal protons1,2. For thicker two-dimensional (2D) materials, proton conductivity diminishes exponentially, so that, for example, monolayer MoS2 that is just three atoms thick is completely impermeable to protons1. This seemed to suggest that only one-atom-thick crystals could be used as proton-conducting membranes. Here, we show that few-layer micas that are rather thick on the atomic scale become excellent proton conductors if native cations are ion-exchanged for protons. Their areal conductivity exceeds that of graphene and hBN by one to two orders of magnitude. Importantly, ion-exchanged 2D micas exhibit this high conductivity inside the infamous gap for proton-conducting materials3, which extends from ∼100 °C to 500 °C. Areal conductivity of proton-exchanged monolayer micas can reach above 100 S cm−2 at 500 °C, well above the current requirements for the industry roadmap4. We attribute the fast proton permeation to ~5-A-wide tubular channels that perforate micas’ crystal structure, which, after ion exchange, contain only hydroxyl groups inside. Our work indicates that there could be other 2D crystals5 with similar nanometre-scale channels, which could help close the materials gap in proton-conducting applications. Few-layer micas show proton permeation across the sheet, exceeding that of graphene and hBN by one to two orders of magnitude.

Scaling approach to tight-binding transport in realistic graphene devices: The case of transverse magnetic focusing

Abstract: Ultraclean graphene sheets encapsulated between hexagonal boron nitride crystals host two-dimensional electron systems in which low-temperature transport is solely limited by the sample size. We revisit the theoretical problem of carrying out microscopic calculations of nonlocal ballistic transport in such micron-scale devices. By employing the Landauer-B\"uttiker scattering theory, we propose a scaling approach to tight-binding nonlocal transport in realistic graphene devices. We test our numerical method against experimental data on transverse magnetic focusing (TMF), a textbook example of nonlocal ballistic transport in the presence of a transverse magnetic field. This comparison enables a clear physical interpretation of all the observed features of the TMF signal, including its oscillating sign.

Long-term memory and synapse-like dynamics in two-dimensional nanofluidic channels

Abstract: Fine-tuned ion transport across nanoscale pores is key to many biological processes, including neurotransmission. Recent advances have enabled the confinement of water and ions to two dimensions, unveiling transport properties inaccessible at larger scales and triggering hopes of reproducing the ionic machinery of biological systems. Here we report experiments demonstrating the emergence of memory in the transport of aqueous electrolytes across (sub)nanoscale channels. We unveil two types of nanofluidic memristors depending on channel material and confinement, with memory ranging from minutes to hours. We explain how large time scales could emerge from interfacial processes such as ionic self-assembly or surface adsorption. Such behavior allowed us to implement Hebbian learning with nanofluidic systems. This result lays the foundation for biomimetic computations on aqueous electrolytic chips. Description Toward fluidic neuromorphic computing There is considerable interest in strategies that mimic the structure of human brain and could lead to the development of next-generation neuromorphic devices. Many recent studies have focused on solid-state devices, although information in biological systems is conveyed by ions solvated in water, an approach now explored in two papers in this issue (see the Perspective by Noy and Darling). Robin et al. created nanofluidic devices consisting of nanometer-thick two-dimensional slits filled with a salt solution, whereas Xiong et al. present a nanofluidic ionic memristor based on confined polyelectrolyte-ion interactions. The two studies are focused on different aspects of neuromorphic engineering, but both show precise control of ion transport in water across nanoscale channels. These studies show promising directions for creating neuromorphic functions using energy-efficient fluidic memristors that could mimic biological systems down to their fundamental principles. —YS Two nanofluidic devices can reproduce Hebbian learning using ions in water as charge carriers, similar to how neurons work.

The rise of graphene

Abstract: Graphene is a rapidly rising star on the horizon of materials science and condensed-matter physics. This strictly two-dimensional material exhibits exceptionally high crystal and electronic quality, and, despite its short history, has already revealed a cornucopia of new physics and potential applications, which are briefly discussed here. Whereas one can be certain of the realness of applications only when commercial products appear, graphene no longer requires any further proof of its importance in terms of fundamental physics. Owing to its unusual electronic spectrum, graphene has led to the emergence of a new paradigm of 'relativistic' condensed-matter physics, where quantum relativistic phenomena, some of which are unobservable in high-energy physics, can now be mimicked and tested in table-top experiments. More generally, graphene represents a conceptually new class of materials that are only one atom thick, and, on this basis, offers new inroads into low-dimensional physics that has never ceased to surprise and continues to provide a fertile ground for applications.

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.

The electronic properties of graphene

Abstract: This article reviews the basic theoretical aspects of graphene, a one-atom-thick allotrope of carbon, with unusual two-dimensional Dirac-like electronic excitations. The Dirac electrons can be controlled by application of external electric and magnetic fields, or by altering sample geometry and/or topology. The Dirac electrons behave in unusual ways in tunneling, confinement, and the integer quantum Hall effect. The electronic properties of graphene stacks are discussed and vary with stacking order and number of layers. Edge (surface) states in graphene depend on the edge termination (zigzag or armchair) and affect the physical properties of nanoribbons. Different types of disorder modify the Dirac equation leading to unusual spectroscopic and transport properties. The effects of electron-electron and electron-phonon interactions in single layer and multilayer graphene are also presented.

Two-dimensional gas of massless Dirac fermions in graphene

Abstract: Quantum electrodynamics (resulting from the merger of quantum mechanics and relativity theory) has provided a clear understanding of phenomena ranging from particle physics to cosmology and from astrophysics to quantum chemistry. The ideas underlying quantum electrodynamics also influence the theory of condensed matter, but quantum relativistic effects are usually minute in the known experimental systems that can be described accurately by the non-relativistic Schrodinger equation. Here we report an experimental study of a condensed-matter system (graphene, a single atomic layer of carbon) in which electron transport is essentially governed by Dirac's (relativistic) equation. The charge carriers in graphene mimic relativistic particles with zero rest mass and have an effective 'speed of light' c* approximately 10(6) m s(-1). Our study reveals a variety of unusual phenomena that are characteristic of two-dimensional Dirac fermions. In particular we have observed the following: first, graphene's conductivity never falls below a minimum value corresponding to the quantum unit of conductance, even when concentrations of charge carriers tend to zero; second, the integer quantum Hall effect in graphene is anomalous in that it occurs at half-integer filling factors; and third, the cyclotron mass m(c) of massless carriers in graphene is described by E = m(c)c*2. This two-dimensional system is not only interesting in itself but also allows access to the subtle and rich physics of quantum electrodynamics in a bench-top experiment.

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。