Tianhe2-JK Time Allocation Application –

Computational study on high-speed disperse flows

The aims of this proposed project are dual and mutually dependent. One aim is to advance the

understanding of the basic physics that control the multiphase interactions in high speed,

non-dilute disperse flows. The other aim is to advance computational methods and computer

implementations of such methods so as to achieve practical direct numerical simulations necessary

for meeting the first aim. We have done already the ground work towards both aims, so our

research plans are well defined and the work involves a minimal amount of risk.

On the first aim, we should mention that high-speed disperse flows are not only one of the

cornerstones of advanced technologies, they are also at the essence of the science of fluid

mechanics since the averaging process of the field equations yields an ill-posed problem, which

despite enormous efforts over the past 50 years remains unresolved. On the second aim, as we

explain below, and as evidenced by the meager results available in the literature so far, the need

for practical simulations of high fidelity, involving no modelling assumptions continues to be great.

The computational demands are great because of the essential threedimensionality of the flow on

the one hand, and the tremendous resolution requirements that high-speed flows (thin boundary

layers) entail. This proposal sets us to operate at the intersection of these two major challenges.

To better appreciate the scope of the first aim, we need to mention recent experiments

(Theofanous et al. [1], our long-term collaborators in the USA) involving the interaction of shock

waves with a curtain of particles made to occupy the full cross-sectional area of the channel of a

shock tube. They found that the curtain expands rapidly in an explosive like manner and at

accelerations that reach up to 10,000 g. Efforts made by these authors to compute this behavior

using an effective field model (Lhuillier et al. [4]) failed by under predicting the accelerated

expansion by about 40%. Another work by Wagner et al. [2], involving particles and curtain

thickness that were an order of magnitude smaller, conformed to the scaling approach of

Theofanous et al. [1], but again the effective field approach failed by the same 40%. Ling et al. [3]

presented results by a point-particle method, and claimed excellent agreement, but it is trivial to

see a major error in their formulation that led to an over prediction of the added mass and transient

viscous force totaling 40%. It is also trivial to see that both of these forces are negligibly small for

the conditions of both tests. Clearly then there are new physics here that may impact even the

whole classical idea of averaging! To better appreciate the scope of the second aim, we note that

current experience with DNS of disperse flows has been limited to a handful of studies. Most of

them are for incompressible flow with Reynolds numbers only up to 180, and resolutions only up

to 13 cells per particle [5, 6]. DNS simulations of compressible disperse flows are limited in 2D

with at most 100 stationary spheres [8, 9]. To our knowledge, there is no 3D DNS for

compressible flow so far. Our present code for compressible 3D flows was demonstrated can

handle a few hundreds of particles, and to produce promising results relative to the experiments

mentioned above (as we explain below). The aims of the present work is to extend the capability

to 2000 particles, Re of up to 10,000, and resolutions of 40 cells per particle for a total of 400

million cells, and using the results to get an appreciation of the forces on individual particles and

how they are affected by the collective effect of nearby particles (the concentration of particles).

Application for computing time

Applicant: Yang Ding

The proposed research is to explore the principles of the mechanics and control of

biological locomotion, and apply these principles to more advanced bionic machineries and

bio-robots. To compute the dynamics of fish swimming, high performance computational

fluid dynamics simulation is an essential tool.

Different animals show diversity in undulatory motion, such as the amplitude of the

body undulation, speed, body shape, and maneuverability. Such diversity can also provide

inspirations for the design of robots. We will seek for the laws in the variation, and the

relation between the body shape, the internal structure, the muscle activity, and the

mechanical environment. The results will contribute to our understanding of each component

of locomotion and how these components coordinate. Specifically, we will try to explain the

diverse muscle activation pattern during fish swimming with realistic 3D simulation of

various fishes.

Computational studies of plasmons and excitons in nanomaterials and their energy

applications

Principle Investigator: Shiwu Gao

Participantes: Fei Gao, Chao Zheng, Yi Yang, Saranya G. Jinling Li

Materials and Energy Division, CSRC

This project focuses on the theoretical and computational study of electronic excitations, plasmons

and excitons in particular, at surfaces and interfaces of nanomaterials. Such excitations play

important roles in many material properties and photochemical phenomena at surfaces including

sensing, photovoltaics, solar cells, photocatalysis, and optoelectronic devices. Theoretical

understanding on the formation and decay of these excitations is essential to gain insights into the

nature and dynamics of such excited states and to the design and optimization of materials and

device applications. Combined with analytical models and semiclassical theories, we will conduct

large-scale numerical computations for nanostructured materials and on well-defined systems

using home-developed and open source codes (octopus of TDDFT, BerkeleyGW package), so that

quantitative results can be achieved and comparisons with spectroscopy and measurement can be

made. Calculations of electronic excitations in nanostructures involve large-scale and massively

parallel computations, which usually requires an order of magnitude more computational efforts

and resources than the ground state DFT calculations. This is in part due to the nature and

complexity of surface plasmons and interface excitons, which involve long-range interactions

between many electron-hole pairs, and in part due to the broking symmetry of molecule-surface

systems, so that a large number of atoms (hundreds to thousands of atoms) have to be treated.

Here in this project, first-principles density functional theory will be combined with a

semiclassical theory of plasmon-electron coupling to describe these processes in order to gain

insight into nanoscale light-matter interaction, plasmon and exciton induced electron and energy

transfer processes.

Tianhe2-JK Time Allocation Application

Ab initio study of thermodynamically consistent physical properties of warm dense

plasma

A computational resources of 2000 CPU core for 1000 hours (2,000,000 core hours) is

applied to study the physical properties of warm dense matter. Matter at extreme conditions (i.e.

ultra-high temperatures, up to several million Kelvins, and density, up to several times normal

solid density) is also referred to as “warm dense matter”.

Understanding the behavior of matter at extreme conditions is a major challenge and of critical

importance for a number of scientific fields ranging from astrophysics to the inertial confinement

fusion. The temperature, pressure, and density of the matter under such extreme conditions often

vary several orders of magnitude. Therefore, experimentally, realizing controllable systems at

extreme conditions and probing these systems are understandably extremely difficult. Accurate

theoretical calculations and predictions also face enormous challenge both in terms of constructing

reliable model and in terms of the required computational resources.

In 2014, Sandia National Laboratories of the US carried out a benchmark experiment on the

opacity of warm dense iron, with Te~2,00,000K and solid density. In the high density region, the

measured wavelength dependent opacity is 30–400 per cent higher than predicted. Since iron

accounts for a quarter of the total opacity of the Sun, such discrepancy will lead to reductions of

30–50 per cent in the inferred amounts of carbon, nitrogen and oxygen in the Sun based on

standard solar models. Therefore, some new theoretical methods which can treat these many-body

interactions more adequately need to be developed.

In this study, density functional theory (DFT) based first-principles electronic structure

methods, which have successfully applied for many-body system under conventional conditions,

are applied to the study of the EOS and opacities of warm dense matter. In this study, we will

concentrate on the iron opacity problem, where the calculations will be carried out using the DFT

based method in the similar conditions of the Sandia’s new experiment. Because such kind of

calculation can take into account the many-body interactions in the warm dense matter, the results

can serve as a benchmark to the average atom model as well as experimental measurements,

which should be crucial to astrophysics and ICF studies.

Investigation of Spin-dependent Energy Conversion Processes in Organic

Photovoltaic and Lighting-emitting Devices

Over the past decade, organic electronics have been attracting a great deal of attentions.

In comparison with their inorganic counterparts, organic devices have added advantages

of low cost, easy fabrication, and mechanical flexibility. While great progress has been

made in OPV solar cells and OLEDs, their efficiencies are still far below their

thermodynamic limits. A deeper fundamental understanding is critically needed to

generate breakthroughs that will lead to practical application of OPV solar cells and

OLED solid-state lighting. One distinct difference between the energy conversion

processes, either from light to electrical energy or from electrical to light energy, in

organic versus inorganic semiconducting materials lies in “spin dependency”. In

inorganic materials, energy conversion is mediated through creation/annhilation of

unbound electrons and/or holes (charge carriers), which is spin independent; while in

organic materials, energy conversion, mediated through creation/annhilation of bound

electron-hole pairs (excitons), is spin dependent. Specially, photogeneration of charges in

OPV solar cells is a complex, only partially understood process that involves multiple

steps, which can all be spin dependent. It starts with the absorption of a photon to form a

mobile excited state, or exciton. The exciton then diffuses to an interface between donor

(D) and acceptor (A) domains where it dissociates into a charge transfer (CT) state,

which may be regarded as a tightly bound polaron pair (PP) across the D-A interface.

Next, the CT state undergoes a multistep process to dissociate into free charges (i.e., the

charge separated (CS) state) that ultimately are collected at the electrodes. This complex

reaction and its dynamics is strongly governed by the spin multiplicity of the excited state

(e.g., singlet vs. triplet, having different life time), film morphology at the junction of D

and A, and the energetics of both the bound CT and CS states. Because of the number of

steps involved, there are many routes that an exciton and subsequent products may take

following its generation that can lead to dissipative reactions that degrade the efficiency

of the OPV cell, or alternatively to reactions that may enhance the cell efficiency.

Similarly, the efficiency of OLED device, governed by the rate of exciton recombination,

depends also on the spin multiplicity of excitons.

The mission of this proposal is to provide a significantly deeper understanding of the

energy conversion processes, in particular their spin dependency, in polymeric and

molecular OPVs and WOLEDs through a concerted research effort using spectroscopy,

morphological and electrical characterization, and advanced theoretical and

computational methods. The proposed research will be at the scientific forefront to

address one of the “grand challenges” identified for basic energy science in “How do we

control material processes at the level of electrons?” and the basic energy research needs

in “Solar Energy Utilization and Solid-State Lighting”. Our three-year scientific research

goal is to understand the dynamics of “spin-dependent” electronic processes at the donor-

acceptor (D-A) interfaces in OPV and use it for enhancing solar power conversion

efficiency; as well as singlet-triplet energy flow in WOLEDs and use it for enhancing

electrical power conversion efficiency.

Tianhe2-JK Time Allocation Application

Advanced Functional Materials and Green Energy

Leader: Prof. Jiang Jing（姜晶，中心教授），Leo Lau

Members: Wen-Jin Yin, Ting-Cha Wei, Yu-Xuan Wu, and Jian Wu

Application：3.5 million core hours, or 400 cores for for 8640 hours

slim (the code can be run without cuda or mic)

It is great desire to reduce both the emission and accumulation of CO2

in the atmosphere as is the main greenhouse and ocean acidification gas.

The major source of CO2 emission is the traditional fossil fuel-fired

plants. Apart from the natural photosynthesis, various strategies have

been proposed to mitigate CO2 emission including carbon capture, energy

conservation, and energy storage through the chemical approaches.

Photo-catalytic reduction of CO2 is an efficient way to convert CO2 into

synthetic fuels or other useful chemicals by harnessing the renewable

solar energy. Titanium dioxide (TiO2) is a prototype photo-catalyst for

water splitting, and degradation of organic contaminants, because it is

highly stable, nontoxic and cheap. A series of experiments for

photo-catalytic reduction or fixation of CO2 into fuels have been

performed on the TiO2-based materials. The early experiment was

proposed by Inoue et al., who reported that photo-catalytic reduction of

CO2 in an aqueous suspension of Titania powder can form formaldehyde

(HCHO), formic acid (HCOOH), methanol (CH3OH), and methane (CH4)

as main products.5 Although CO2 can be successfully converted or fixated

through photo-catalytic reduction, both the efficiency and selectivity of

photo-catalytic system are extremely low and poor. In order to design

more efficient and selective photo-catalyst, many related works have been

carried out on the different phases of TiO2.

Tianhe2-JK Time Allocation Application

Leader: Leo Lau（刘焕明）

Postdocs and students: Da Wang, Zhen-Kun Tang, Xi-Bo Li, Jian Wu and

Wei-Wei Liu

The total resource application：600 cores for 8400 hours (1 year)

Advanced Functional Materials and Green Energy

With the rapid development of electronic market, energy storage for renewable

energy sources and hybrid electric vehicles is a pressing technological challenge.

Lithium ion batteries (LIBs) have been the subject of intense investigations due to

their good cycling performance, high storage capacity and high energy density. In

order to meet the requirements for the high power tools and electric vehicles,

electrode materials with high Li reversible storage capacity and fast Li and electron

transport are needed for lithium ion batteries. After graphene became experimentally

accessible in 2004, the layered materials like graphite have attracted great attention

mainly due to their unique physical properties and capability to fulfill the demands of

future nanoelectronic industry on adaptability, flexibility, and multi-functionality.

Although their intensive investigations, excellent anodes with good electrical

conductivity and high reversible lithium storage are still under development. In our

studies, we intend to systematically investigate the electrochemical properties of

a number of layered materials, such as germanium, silicon, black phosphorus,

transition oxides and transition metal dichalcogenides (TMD), etc., by means of

density functional theory (DFT) calculations. Our works propose to provide valuable

insights into exploring new types of high-capacity layered materials for potential

battery applications.

Proposal for TianHe-­‐JK computing time Haiguang Liu et al. Algorithm/Complex System

division

Mapping experimental data to conformational space and recovering free energy landscape

using cryoEM-­‐MDSimulation hybrid approach

Protein molecules are dynamic in cellular environment, such that the biological functions are

carried out via a series of conformational changes. Existing structure determination methods

mostly focus on determining static snapshots of the conformation space. Such static structures are

do facto some forms of ensemble averaged structures. Single molecule structure determination

methods, such as cryo electron-microscopy (cryoEM) or X-ray scattering from single particles,

can detect structure information of individual molecules at distinct conformation state. However,

mapping the experimental data to each structure is challenging due to the information deficiency

from each measurement (2D measurements of the projections in unknown orientation of 3D

structures). Molecular Dynamics simulations, on the other hand, take static structures as starting

model and evolve to continuous trajectories, or in silico molecular movies. The generated

structures can compensate the unknown information from each measurement, such that each 2D

projection can be reliably mapped to specific structures that lie in the conformational space.

Furthermore, the free energy landscape can be recovered by exploiting the relation between

probability distribution and free energy as in Boltzmann distribution. Briefly, this proposal is aim

to develop a computational protocol that extract information from single molecule structure

determination method using computationally generated structures as seeds. The basic flow is as

the following: Experimental data can be converted to ensemble averaged structure (static), which

serves as the initial seed for the conformation generating; then the computational modeling, such

as physics based MD simulation methods, is applied to generate hypothetical structures

(dynamics); as the last step, the experimental data are mapped to the most likely conformation

states in the structure pool. The distribution function can be obtained at the end of the process,

which provides free energy information, and possible conformational transition pathways (energy

landscape). Most of the computations are perfectly parallelizable, taking full advantages of the

Tianhe-2 computer clusters. We request a computing time allocation of 0.6 million CPU hours

with some GPU resources, which is justified in the detailed research plan.

Tianhe2-JK Time Allocation Application

Leader: Li-Min Liu

6.72 million cores hours, or 800 cores for 8400 hours

(slim queue, the code can run against with CUDA or MIC)

As the world’s population increases and substantial industrial growth

continues, the energy demands of society increase rapidly. The energy

produced by the sun and carried down to earth by its radiation provides

an alternative and clean source of energy to meet and exceed the world’s

energy consumption demands. Organic-inorganic halide perovskites such

as CH3NH3PbI3 (MAPbI3) exhibit great promise for low cost and high

efficiency thin film solar cells due to the relative ease through solution

casting to achieve high degrees of crystallinity, excellent carrier transport

properties, tunable optical bandgaps, and strong light absorption.

Perovskites based solar cells have been under very fast development over

the past three years with the power conversion efficiency (PCE) rapidly

improved from 3.8% to 19.3%. Hence, perovskites based solar cells were

seen as the third-generation solar cells.

To solve the problem still in the photocatalytic applications of

CH3NH3PbI3 perovskite and make sure the mechanism of charge

transfer, we plan to perform large scale calculations with multiple

methods based on our initial results and achievements have been made

(two SCI publications and one submit).

Tianhe2-JK Time Allocation Application

Project Title: Quantum mechanical simulations of optoelectronic devices

Optoelectronics involves the study and application of electronic devices that source, detect

and control light, usually considered as a sub-field of photonics. In this project, we propose to

study quantum mechanically the electrical-to-optical or optical-toelectrical conversion in different

devices, including solar cells, light-emitting diode and plasmonic devices. In particular, we will

develop methods within our software package to study metal-halide perovskite solar cells,

dye-sensitized solar cells and GaN lightemitting diode. We propose here to employ our newly

developed quantum mechanical method to investigate in details the properties and mechanism of

these different optoelectronic devices. Unlike the existing classical or semi-classical theoretical

methods that focus on electronic structure calculation from which parameters such as effective

mass, bap gap and mobility can be inferred and subsequently substituted into classical or

semi-classical models, the quantum mechanical method that we recently developed can be used to

simulate directly the photo-excitation, electron-hole separation/recombination, charge carrier

migration, and heat dissipation, and evaluate the absorption coefficient, recombination rate,

radiative & non-radiative decay and power conversion efficiency without resorting to any classical

or semi-classical approximations. By simulating the electron-photon interaction process once, all

the relevant optoelectronic properties can be obtained. It was used to simulate quantum

mechanically the photo-induced current through a photovoltaic device made of a semiconductor

PN junction, and evaluate directly its power conversion efficiency, internal quantum efficiency,

open circuit voltage and short circuit current. In the proposed project, we plan to further develop

our method for applications of different optoelectronic devices, this includes light-emitting diode,

metal halide perovskite solar cells, dye-sensitized solar cells and plasmonic devices. The

electron-photon interaction will be included within the framework of non-equilibrium Green’s

function. The electromagnetic field is quantized to account for quantum mechanically the coupling

between the electrons and photons, and the heat dissipation due to the electron-phonon interaction

can be treated similarly. Specifically, absorption of photons, recombination of electron-hole pairs

or excitons, separation of electrons and holes and mobility of charge carriers of these devices will

be examined in depth to understand power conversion efficiency and to explore the possibility to

design more efficient devices.

The computational cost of the proposed project is high, mainly due to numerical integration

of Green’s function in large energy range. In addition, the frequency range of solar spectrum has

to be covered to obtain the power conversion efficiency of the solar cell. Fortunately, most of the

simulations are independent and can be readily parallelized.

Tianhe2-JK Time Allocation Application

QM and MD Simulations-Based Materials Design for Hydrogen Production and

Storage

Sateesh Bandaru, Limin Liu, Wei Cai

1.3 million core hours (150 cores for 8400 hours )

(slim queue, the code can run against with CUDA or MIC)

Hydrogen has emerged as one of the most promising alternative power fuel sources,

both as a transportation fuel and for proton-exchange membrane fuel cells, and as a

replacement for batteries for portable electric source. However, a number of difficulties

have risen in regards to small and large scale storage. Significant efforts are underway

to design materials for efficient chemical hydrogen storage, from both synthetic

and computational perspectives. Overall, tremendous progress has been made in recent

years in the discovery of new materials. However, the fundamental advantage of

hydrogen production from efficiency of photochemical water splitting is that the

hydrogen may be used as a mechanism for energy storage; this is considered to be an

efficient storage medium by many within the scientific community.

This study intends to make use of the quantum chemical theories to assist the catalyst

design and understanding the reaction profile of splitting of water using a metal catalyst.

The prime aim of this research is concerned with investigating mechanisms for

artificial water splitting by transition metal complexes, together with the concept of

insilico design of transition metal complexes which are commercially cheaper and

experimentally (synthetically) viable catalysts for suitable water oxidation catalysis

(WOC). Although the catalytic process of transition metal complexes for water

oxidation has been explored by several experimental and theoretical studies, the subtle

mechanisms of some key reaction processes still remain elusive. So, our focus is mainly

to explore the mechanistic pathway at both lower- and higher-concentration

mechanisms and explore intermediate reaction steps. In particular, assessing their

nature, e.g., whether proton-coupled electron transfer or stepwise processes, and,

finally, ease of O2 release from the pre- catalyst, are sine qua non. One of the main

objectives of this project is to develop theoretical methods that can serve as efficient

screening tools for the reactivity of putative catalyst candidates. Before exploring these

mechanisms with transition metal complexes, we need to validate the various DFT

simulation methods. These kinds of system will need more comprehensive simulation

techniques, such as fully explicit solvent models or the inclusion of counter-ions to

determining more accurately the redox potentials of these highly oxidized species.

Therefore, another objective of this project is to develop the theoretical methods that

can serve as efficient screening tools for the reactivity of putative catalyst candidates.

Until now, we do not have any detailed theoretical insights into WOC reactions. There

is an essential need to know which methodology is most appropriate. Initially, we want

to validate first-principles DFT studies to transition-metal-catalyzed water oxidation

reactions by using well-known catalyst such as single-site polypyridyl ruthenium

complexes [Ru(tpy)(bpm)(OH2)]+2

. Then the reliable methods will be applied to

unknown designed catalysts, and the calculated redox potentials and activation energy

barriers compared with known catalysts. The central aim of this proposal is to design a

novel and commercially cheap and experimentally viable structures for artificial

water-splitting by transition metal complexes.

The other important project in which the molecular dynamics simulation (MD) and ab

initio molecular dynamics (AIMD) will be performed of interfaces between metal

oxides and liquid water, to capture the rich tapestry of chemical and physical adsorption

interactions in all of their physic-chemical complexity, employing state-of-the-art

treatments of dispersion. Partial and full coverage of chemically and physically

adsorbed water molecules will be investigated, as well as full condensed phases of

liquid water in contact with metal oxide surfaces. A particular focus will be on the

dynamical properties of hydrogen bonds between protons in water molecules and the

bridging oxygen atoms at the surface, as well as the variation in bond-stretch and

bond-angle bending modes in the water molecules. The dipolar orientation of the water

molecules vis-à-vis the surface-normal will also be studied, as well as

water-dissociation kinetics and thermodynamics on these surfaces. The importance of

kinks and surface irregularities will also be studied very closely. It is to be expected that

this will contribute to our somewhat lacking understanding of water interactions with

metal oxide surfaces, to enhance efforts in the optimal design of nano-material surfaces

for photo-catalytic water-splitting.

Abstract of proposed research

Yi-bing ShanComplex Systems Divison

Proteins are building blocks of life and they are associated in almost all aspects of cellularactivities. Since a protein’s function is rooted in its distinct three-dimensional structures, the deter-mination of the atomic structures and to establish the structure-function relationships are crucialfor understanding life phenomenon at the molecular level.

The objective of our research is to understand the activation mechanism of plexin, an importantcell surface receptor protein that transduces signals for regulating neuronal axon guidance andimmune responses. Malfunction of plexin signaling has been related to neurological disorders andvarious cancers. It has been proposed as promising drug targets for a number of important diseases.Xuewu Zhang and colleagues form the University of Texas Southwestern Medical Center showedthat the upstream signal leads to dimerization and activation of plexins, and upon the activationplexins bind and activate the GTPase activity of a Rap proteins as a GTPase activation protein(GAP); the Rap proteins in turn interact with effectors and produce a downstream signal. However,in structural terms how plexins are restrained in its inactive state, and how they are activated bythe induced dimerization remain unclear.

The regulation mechanisms remained largely elusive until Xuewu Zhang et al. from the Universityof Texas Southwestern Medical Center published their pioneer experimental works on the structuralbasis for activation of plexin. They found plexin activation requires binding of Rap (a kind ofGTP-binding protein), but the mechanism of this process is still unclear and difficult to study byexperiments. Xuewu Zhang hence hope to cooperate with us on solving this important problemby investigating the functional related conformational dynamics of plexin using all-atom moleculardynamics simulations.

All-atom molecular dynamics simulations (MD) is an increasingly applied method for studies ofprotein conformational dynamics, which reveals atomic details of motions of macromolecules thatare often functionally highly important. However, despite the rapid development of hardware andsoftware, demanding computation cost still poses a major limitation to MD. Tianhe2-JK, a top rankgeneral-purpose supercomputer in China, is ideal for carrying out the demanding computation ofour research in a reasonable time scope.

Furthermore, with the MD simulations of plexin and other proteins as benchmark, we also intentto develop a novel sampling method aiming to accelerate molecular dynamics simulations. Gentlestascending dynamics (GAD) was proposed by Weinan E as a new sampling method that efficientlyidentifies the transition conformations of a protein in conformational changes. This method cangreatly reduce the computing time once it is adopted for protein simulations. Efficient implementa-tion of GAD on the platform of GPGPU technology (CUDA or OpenCL) will produces a softwarepackage that can be incorporated into the mainstream MD packages such as AMBER or GROMACS.

We shall study the functional-related conformational dynamics of plexin by all-atom moleculardynamics. GAD scheme will also be implemented and tested using plexin as the primary testingsystem. Such work requires simulations of plexin systems to reach microsecond timescale. Our testruns of these systems suggest that 30 slim nodes (600 cores) and one GPU node on Tianhe2-JK areneeded to complete such runs in approximately one year.

1

Tianhe2-JK Allocation application:

Simulating life’s crucial protein machinery for genetic and

metabolic control

Gene transcription is the first step in gene expression. The essential enzymes that

direct the processes are RNA polymerases (RNAPs; see Fig 1 left), which copy

information from template DNA to a newly synthesized RNA strand based on

Watson-Crick base pairing [1]. In recent years, high-resolution structures of RNAPs

become abundant, however, functional mechanisms in structural dynamics detail

remain illusive. In this application, we want to implement atomistic molecular

dynamics (MD) simulations to investigate physical mechanism of RNAP function.

The simulations take advantage of high performance computation (HPC), and apply to

all-atom biomolecular systems up to milliseconds with femtosecond time step [2]. Fig

1. Schematic structural views of an RNA polymerase (left) and F1-ATPase (right) In the

incoming year, we would focus on MD simulations of RNAP from bacteriophage T7,

a nice model system to study fundamentals of transcription. We have examined how a

critical amino acid selects right nucleotides over wrong ones in T7 RNAP [3], and

also simulated the product release and constructed the corresponding Markov state

model (MSM) [4]. Further, we will conduct systematical free energy calculations to

quantify the nucleotide selectivity essential for fidelity control. We will also construct

the MSM for the T7 RNAP translocation and design mutant polymerases for desired

functions, such as backtracking and/or proofreading.

In addition, we want to study metabolically essential protein machinery

F1-ATPase (Fig 1 right) using also the MD simulation. F1-ATPase is part of the

synthase and ATPase, which can synthesize or hydrolyze ATP, the energy currency of

the cell. Our focus is on how the sequential hydrolysis pattern arises on the ATPase

ring, and the mechanisms can be universal for many ring-shaped motor proteins (such

as the viral DNA packaging motor [5] we studied). We want to combine atomistic

simulations with stochastic modeling and coarse-grained simulations, so that to

decipher the inter-subunit coupling leading to the sequential pattern at multiple time

scales.

In charge of the research work: Dong-Bo Zhang

Title in CSRC: Faculty

Application for the Tianhe2-JK Time.

Compared to electronic and photonic transports, lattice heat conduction is less well

understood for many materials. Our planed research projects are focusing the exploration of the

lattice thermal conductivities of bulk materials through ab initio molecular dynamics and classical

molecular dynamics. Two systems are considered: Fe-bearing MgSiO3 perovskite and MgO

periclase with defects. Recently, the PI developed a hybrid approach that combines ab initio

molecular dynamics and lattice dynamics to enable the first principle study of lattice anharmoncity

of complex crystal. In this approach, the anharmonic effect induced by intrinsic phonon-phonon

interaction are fully accounted for in terms of phonon quasi-particle. This approach allows not

only the calculation of anharmonic phonon dispersion, but also the calculation of phonon linewith.

The phonon lifetime, group velocity, and heat capacity can thus be obtained straightforward. The

knowledge on phonon properties enable the study of lattice thermal conductivity through phonon

gas model, where Boltzmann transport equation is employed.

MgSiO3 perovskite and MgO periclase are the most abundant minerals in the earth lower

mantle. Their properties determines to a great extent the properties of the lower mantle. Therefore,

the understanding on their thermal conductivity will help gain insight into the heat transfer inside

the deep earth. The present project will focus on the behavior Fe-bearing MgSiO3 perovskite and

MgO periclase, under extreme conditions, i.e., high pressure and high temperature mimicking the

lower mantle condictions. The study on Fe-bearing MgSiO3 perovskite aims to elucidate the role

of Fe ingredient in the thermal conductivity of MgSiO3 perovskite. On the other hand, the study

on MgO periclase will address the impact of defects on the thermal conductivity of MgO periclase.

Both are of crucial importance in geoscience.

First-Principles Studies in the Understanding and Design of Lithium-ion

Battery Materials

Yanning Zhang

Lithium-ion batteries (LIBs) are now ubiquitous in portable electronics because of

their high specific energy, high energy density, low weight and low volume.

Intercalation of LIBs to other advanced battery systems have also been developed for

a wide range of promising applications in, such as electrotraction in hybrid cars,

storage devices of solar power systems, and micro battery systems for integration in

electronic and medical devices. However, as LIBs are widely introduced into

commercial applications, several additional factors such as safety, minimum time to

charge and discharge, and cycle life are becoming increasingly important. Therefore,

researchers continually seek new electrode materials that are significant in structural

stability, safety, specific energy, and low cost, based on a good understanding and

control of the involved processes during charging-discharging (delithiation-lithiation)

cycle of the battery.i,ii

Encouraged by the significant development of pseudopotential plane wave approaches

and tremendous increase in computational capacity, in the last 20 years, the

first-principles electronic structure methods have shown highly reliability in the

prediction of phase stability and a large variety of physical and electronic

properties.iii,iv,v,vi

In the LIB research field, computational methods have successfully

elucidated several key properties of electrodes, such as cell voltage, ionic and

electronic conductivities, phase stability, and thermal stability, and more importantly,

predicted many high energy density electrode materials before experimental

realization, such as the Li(Al,Co)O2 system.vii,viii,ix

Obviously, a complementary

theoretical and experimental approach, combining aspects of materials science,

physics and chemistry, will be a cost-effective way to explore new materials for

battery applications.

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