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

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。

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

6.2.2. Definition of Effective Properties 3064 6.3. Response Properties to Magnetic Fields 3066 6.3.1. Nuclear Shielding 3066 6.3.2. Indirect Spin−Spin Coupling 3067 6.3.3. EPR Parameters 3068 6.4. Properties of Chiral Systems 3069 6.4.1. Electronic Circular Dichroism (ECD) 3069 6.4.2. Optical Rotation (OR) 3069 6.4.3. VCD and VROA 3070 7. Continuum and Discrete Models 3071 7.1. Continuum Methods within MD and MC Simulations 3072

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Quantum mechanical continuum solvation models.

Metal–organic frameworks (MOFs) display a wide range of luminescent behaviors resulting from the multifaceted nature of their structure. In this critical review we discuss the origins of MOF luminosity, which include the linker, the coordinated metal ions, antenna effects, excimer and exciplex formation, and guest molecules. The literature describing these effects is comprehensively surveyed, including a categorization of each report according to the type of luminescence observed. Finally, we discuss potential applications of luminescent MOFs. This review will be of interest to researchers and synthetic chemists attempting to design luminescent MOFs, and those engaged in the extension of MOFs to applications such as chemical, biological, and radiation detection, medical imaging, and electro-optical devices (141 references).

Luminescent Metal–Organic Frameworks

Nanocrystals (NCs) discussed in this Review are tiny crystals of metals, semiconductors, and magnetic material consisting of hundreds to a few thousand atoms each. Their size ranges from 2-3 to about 20 nm. What is special about this size regime that placed NCs among the hottest research topics of the last decades? The quantum mechanical coupling * To whom correspondence should be addressed. E-mail: dvtalapin@uchicago.edu. † The University of Chicago. ‡ Argonne National Lab. Chem. Rev. 2010, 110, 389–458 389

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Prospects of Colloidal Nanocrystals for Electronic and Optoelectronic Applications

Summary form only given. Donor/acceptor substituted conjugated molecules possess even-order nonlinear polarizabilities. Existing experimental and theoretical studies have not yet established the precise scaling law of the second-order polarizability /spl beta/ and its the crossover to the bulk. In this paper we use a Collective Electronic Oscillator (CEO) technique to explore the variation of linear, second, and third order polarizabilities in donor/acceptor substituted polymers all the way to the bulk.

Origin, scaling, and saturation of nonlinear polarizabilities in donor/acceptor polymers

Highly energetic electron–hole pairs (hot carriers) formed from plasmon decay in metallic nanostructures promise sustainable pathways for energy-harvesting devices. However, efficient collection before thermalization remains an obstacle for realization of their full energy generating potential. Addressing this challenge requires detailed understanding of physical processes from plasmon excitation in the metal to their collection in a molecule or a semiconductor, where atomistic theoretical investigation may be particularly beneficial. Unfortunately, first-principles theoretical modeling of these processes is extremely costly, preventing a detailed analysis over a large number of potential nanostructures and limiting the analysis to systems with a few 100s of atoms. Recent advances in machine learned interatomic potentials suggest that dynamics can be accelerated with surrogate models which replace the full solution of the Schrödinger Equation. Here, we modify an existing neural network, Hierarchically Interacting Particle Neural Network (HIP-NN), to predict plasmon dynamics in Ag nanoparticles. The model takes as a minimum as three time steps of the reference real-time time-dependent density functional theory (rt-TDDFT) calculated charges as history and predicts trajectories for 5 fs in great agreement with the reference simulation. Further, we show that a multistep training approach in which the loss function includes errors from future time-step predictions can stabilize the model predictions for the entire simulated trajectory (∼25 fs). This extends the model’s capability to accurately predict plasmon dynamics in large nanoparticles of up to 561 atoms, not present in the training data set. More importantly, with machine learning models on GPUs, we gain a speed-up factor of ∼103 as compared with the rt-TDDFT calculations when predicting important physical quantities such as dynamic dipole moments in Ag55 and a factor of ∼104 for extended nanoparticles that are 10 times larger. This underscores the promise of future machine learning accelerated electron/nuclear dynamics simulations for understanding fundamental properties of plasmon-driven hot carrier devices.

Machine Learning Models Capture Plasmon Dynamics in Ag Nanoparticles

3d Nanographene Precursor Assemblies Suppress Interfacial Recombination in Pedot: Pss Based Perovskite Solar Cells

While stoichiometric quantum dots (QDs) have been well studied, a significant knowledge gap remains in the atomistic understanding of the non-stoichiometric ones, which are predominantly present during the experimental synthesis. Here, we investigate the effect of thermal fluctuations on structural and vibrational properties of non-stoichiometric cadmium selenide (CdSe) nanoclusters: anion-rich (Se-rich) and cation-rich (Cd-rich) using ab initio molecular dynamics (AIMD) simulations. While the excess atoms on the surface fluctuate more for a given QD type, the optical phonon modes are mostly composed of Se atoms dynamics, irrespective of the composition. Moreover, Se-rich QDs have higher bandgap fluctuations compared to Cd-rich QDs, suggesting poor optical properties of Se-rich QDs. Additionally, non-adiabatic molecular dynamics (NAMD) suggests faster non-radiative recombination for Cd-rich QDs. Altogether, this work provides insights into the dynamic electronic properties of non-stoichiometric QDs and proposes a rationale for the observed optical stability and superiority of cation-rich candidates for light emission applications.

How structural and vibrational features affect optoelectronic properties of non-stoichiometric quantum dots: computational insights.

Understanding conical intersection (CI) dynamics and subsequent conformational changes is key for exploring and controlling photo-reactions in aromatic molecules. Monitoring of their time-resolved dynamics remains a formidable experimental challenge. In this study, we simulate the photoinduced S3 to S1 non-adiabatic dynamics of cyclooctatetraene (COT), involving multiple CIs with relaxation times in good agreement with experiment. We further investigate the possibility to directly probe the CI passages in COT by off-resonant X-ray Raman spectroscopy (TRUECARS) and time-resolved X-ray diffraction (TRXD). We find that these signals sensitively monitor key chemical features during the ultrafast dynamics. First, we distinguish two CIs by using TRUECARS signals with their appearances at different Raman shifts. Second, we demonstrate that TRXD, where X-ray photons scatter off electron densities, can resolve ultrafast changes in the aromaticity of COT. It can further distinguish between planar and non-planar geometries explored during the dynamics, as e.g. two different tetraradical-type CIs. The knowledge gained from these measurements can give unique insight into fundamental chemical properties that dynamically change during non-adiabatic passages.

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Sergei Tretiak

Papers

Origin, scaling, and saturation of nonlinear polarizabilities in donor/acceptor polymers

Machine Learning Models Capture Plasmon Dynamics in Ag Nanoparticles

3d Nanographene Precursor Assemblies Suppress Interfacial Recombination in Pedot: Pss Based Perovskite Solar Cells

How structural and vibrational features affect optoelectronic properties of non-stoichiometric quantum dots: computational insights.

Monitoring vibronic coherences and molecular aromaticity in photoexcited cyclooctatetraene with an X-ray probe: a simulation study