Roberto Car

Bio: Roberto Car is an academic researcher from Princeton University. The author has contributed to research in topics: Density functional theory & Ab initio. The author has an hindex of 99, co-authored 389 publications receiving 76681 citations. Previous affiliations of Roberto Car include International School for Advanced Studies & University of Geneva.

Heat transport in liquid water from first-principles and deep-neural-network simulations

Abstract: We compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way, that a DNN model, trained on meta-GGA (SCAN) data, reduce the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.

Root-Growth of Boron Nitride Nanotubes: Experiments and \textit{Ab Initio} Simulations

Abstract: We have synthesized boron nitride nanotubes (BNNTs) in an arc in presence of boron and nitrogen species only, without transition metals. We find that BNNTs are often attached to pure boron nanoparticles, suggesting that root-growth is a likely mechanism for their formation. To gain further insight into this process we have studied key mechanisms for root growth of BNNTs on the surface of a liquid boron droplet by ab initio molecular dynamics simulations. We find that nitrogen atoms reside predominantly on the droplet surface where they organize to form boron nitride islands below 2400 K. To minimize contact with the liquid particle underneath, the islands assume non-planar configurations that are likely precursors for the thermal nucleation of cap structures. Once formed, the caps are stable and can easily incorporate nitrogen and boron atoms at their base, resulting in further growth. Our simulations support the root-growth mechanism of BNNTs and provide comprehensive evidence of the active role played by liquid boron.

Theoretical Design by First Principles Molecular Dynamics of a Bioinspired Electrode−Catalyst System for Electrocatalytic Hydrogen Production from Acidified Water

Abstract: Bacterial di-iron hydrogenases produce hydrogen efficiently from water. Accordingly, we have studied by first-principles molecular-dynamics simulations (FPMD) electrocatalytic hydrogen production from acidified water by their common active site, the [FeFe]H cluster, extracted from the enzyme and linked directly to the (100) surface of a pyrite electrode. We found that the cluster could not be attached stably to the surface via a thiol link analogous to that which attaches it to the rest of the enzyme, despite the similarity of the (100) pyrite surface to the Fe4S4 cubane to which it is linked in the enzyme. We report here a systematic sequence of modifications of the structure and composition of the cluster devised to maintain the structural stability of the pyrite/cluster complex in water throughout its hydrogen production cycle, an example of the molecular design of a complex system by FPMD.

Cu++ and Li+ interaction with polyethylene oxide by ab initio molecular dynamics

Abstract: Equilibrium positions on the Li+–PEO and on the Cu++–PEO ground state potential energy surfaces have been determined by ab initio molecular dynamics. Our results confirm the previously proposed jump mechanism for ion diffusion in polymer electrolytes. The energy barriers for Li+ and Cu++ ionic diffusion along the PEO chain have been estimated.

Recent numerical results on the two dimensional Hubbard model

Abstract: A new method for simulating strongly correlated fermionic systems has been applied to the study of the ground state properties of the 2D Hubbard model at various fillings. Comparison has been made with exact diagonalization in the 2×2, 3×3 and 4×4 lattices where very good agreement has been verified. Numerical results concerning a)magnetization, b)momentum distribution, c)charge, spin and pairing correlations have been obtained with this method for sizes up to 16×16 sites and several fillings. The 2D antiferromangetic order is destroyed by the presence of few holes and is very sensitive to the boundary conditions. The momentum distribution of the doped system does not have a clear Fermi surface. This is also supported by the exponential decay of the density matrix at large enough distances. Particular attention will be paid to the single hole properties and hole-hole correlations.

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.

QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials

Abstract: QUANTUM ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). The acronym ESPRESSO stands for opEn Source Package for Research in Electronic Structure, Simulation, and Optimization. It is freely available to researchers around the world under the terms of the GNU General Public License. QUANTUM ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively parallel architectures, and a great effort being devoted to user friendliness. QUANTUM ESPRESSO is evolving towards a distribution of independent and interoperable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.

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。

Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium.

Abstract: We present ab initio quantum-mechanical molecular-dynamics simulations of the liquid-metal--amorphous-semiconductor transition in Ge. Our simulations are based on (a) finite-temperature density-functional theory of the one-electron states, (b) exact energy minimization and hence calculation of the exact Hellmann-Feynman forces after each molecular-dynamics step using preconditioned conjugate-gradient techniques, (c) accurate nonlocal pseudopotentials, and (d) Nos\'e dynamics for generating a canonical ensemble. This method gives perfect control of the adiabaticity of the electron-ion ensemble and allows us to perform simulations over more than 30 ps. The computer-generated ensemble describes the structural, dynamic, and electronic properties of liquid and amorphous Ge in very good agreement with experiment. The simulation allows us to study in detail the changes in the structure-property relationship through the metal-semiconductor transition. We report a detailed analysis of the local structural properties and their changes induced by an annealing process. The geometrical, bonding, and spectral properties of defects in the disordered tetrahedral network are investigated and compared with experiment.