Andres Jaramillo-Botero

General Multiobjective Force Field Optimization Framework, with Application to Reactive Force Fields for Silicon Carbide

First-principles-based force fields prepared from large quantum mechanical data sets are now the norm in predictive molecular dynamics simulations for complex chemical processes, as opposed to force fields fitted solely from phenomenological data. In principle, the former allow improved accuracy and transferability over a wider range of molecular compositions, interactions, and environmental conditions unexplored by experiments. That is, assuming they have been optimally prepared from a diverse training set. The trade-off has been force field engines that are functionally complex, with a large number of nonbonded and bonded analytical forms that give rise to rather large parameter search spaces. To address this problem, we have developed GARFfield (genetic algorithm-based reactive force field optimizer method), a hybrid multiobjective Pareto-optimal parameter development scheme based on genetic algorithms, hill-climbing routines and conjugate-gradient minimization. To demonstrate the capabilities of GARFfield we use it to develop two very different force fields: (1) the ReaxFF reactive force field for modeling the adiabatic reactive dynamics of silicon carbide growth from an methyltrichlorosilane precursor and (2) the SiC electron force field with effective core pseudopotentials for modeling nonadiabatic dynamic phenomena with highly excited electronic states. The flexible and open architecture of GARFfield enables efficient and fast parallel optimization of parameters from quantum mechanical data sets for demanding applications like ReaxFF, electronic fast forward (or electron force field), and others including atomistic reactive charge-optimized many-body interatomic potentials, Morse, and coarse-grain force fields.

Development of a ReaxFF reactive force field for ettringite and study of its mechanical failure modes from reactive dynamics simulations.

Ettringite is a hexacalcium aluminate trisulfate hydrate mineral that forms during Portland cement hydration. Its presence plays an important role in controlling the setting rate of the highly reactive aluminate phases in cement paste and has also been associated with severe cracking in cured hardened cement. To understand how it forms and how its properties influence those of hardened cement and concrete, we have developed a first-principles-based ReaxFF reactive force field for Ca/Al/H/O/S. Here, we report on the development of this ReaxFF force field and on its validation and application using reactive molecular dynamics (RMD) simulations to characterize and understand the elastic, plastic, and failure response of ettringite at the atomic scale. The ReaxFF force field was validated by comparing the lattice parameters, pairwise distribution functions, and elastic constants of an ettringite crystal model obtained from RMD simulations with those from experiments. The predicted results are in close agreement with published experimental data. To characterize the atomistic failure modes of ettringite, we performed stress-strain simulations to find that Ca-O bonds are responsible for failure of the calcium sulfate and tricalcium aluminate (C3A) column in ettringite during uniaxial compression and tension and that hydrogen bond re-formation during compression induces an increase in plastic strain beyond the materials stress-strain proportionality limit. These results provide essential insight into understanding the mechanistic role of this mineral in cement and concrete degradation, and the ReaxFF potential developed in this work serves as a fundamental tool to further study the kinetics of hydration in cement and concrete.

Adaptive Accelerated ReaxFF Reactive Dynamics with Validation from Simulating Hydrogen Combustion

We develop here the methodology for dramatically accelerating the ReaxFF reactive force field based reactive molecular dynamics (RMD) simulations through use of the bond boost concept (BB), which we validate here for describing hydrogen combustion. The bond order, undercoordination, and overcoordination concepts of ReaxFF ensure that the BB correctly adapts to the instantaneous configurations in the reactive system to automatically identify the reactions appropriate to receive the bond boost. We refer to this as adaptive Accelerated ReaxFF Reactive Dynamics or aARRDyn. To validate the aARRDyn methodology, we determined the detailed sequence of reactions for hydrogen combustion with and without the BB. We validate that the kinetics and reaction mechanisms (that is the detailed sequences of reactive intermediates and their subsequent transformation to others) for H2 oxidation obtained from aARRDyn agrees well with the brute force reactive molecular dynamics (BF-RMD) at 2498 K. Using aARRDyn, we then extend our simulations to the whole range of combustion temperatures from ignition (798 K) to flame temperature (2998K), and demonstrate that, over this full temperature range, the reaction rates predicted by aARRDyn agree well with the BF-RMD values, extrapolated to lower temperatures. For the aARRDyn simulation at 798 K we find that the time period for half the H2 to form H2O product is ∼538 s, whereas the computational cost was just 1289 ps, a speed increase of ∼0.42 trillion (10(12)) over BF-RMD. In carrying out these RMD simulations we found that the ReaxFF-COH2008 version of the ReaxFF force field was not accurate for such intermediates as H3O. Consequently we reoptimized the fit to a quantum mechanics (QM) level, leading to the ReaxFF-OH2014 force field that was used in the simulations.

Molecular mechanics and molecular dynamics analysis of Drexler-Merkle gears and neon pump

Over the past two years at the Materials and Process Simulation Center, we have been developing simulation approaches for studying the molecular nanomachine designs pioneered by Drexler and Merkle. These nanomachine designs, such as planetary gears and neon pump, are described with atomistic details and involve up to 10 000 atoms. With the Dreiding and universal force fields, we have optimized the structures of the two planetary gear designs and the neon pump. At the Fourth Foresight conference, we reported rotational impulse dynamics studies of the first and second generation designs of planetary gears undergoing very high-frequency rotational motions. We will explore stability of these designs in the lower frequency regimes which require long time simulations. We will report the molecular mechanics and molecular dynamics simulations performed on these model systems. We explore the following modes in these studies: (1) impulse mode; (2) constant angular velocity - perpetual rotation; (3) constant torque - acceleration from rest.

A high speed parallel architecture for fuzzy inference and fuzzy control of multiple processes

A hardware processing architecture and an associated graphical compiler for fuzzy inference and control of multiple antecedents and output variables is presented. The hardware architecture, running as a fuzzy co-processor for IBM PC (or compatible) platforms, uses as core elements the FP9000 rules chips and FP9001 defuzzifier chips. The claimed response for these processors is in the order of 0.714 /spl mu/s per fuzzy inference without defuzzification, and 1.6 /spl mu/s per fuzzy inference including center of gravity defuzzification. The architecture proposed permits fuzzy inference simulation under PC master control, as well as direct fuzzy control of output processes. The system relies on the partial flexibility of the fuzzy chips (fuzzy rule parameters are programmable through a digital interface), their embedded parallel processing, and the analog processing speeds, in order to achieve high speed simulation and real-time control response. An object oriented graphical compiler designed to permit intuitive definitions and tuning of linguistic labels within membership functions, as well as plant control systems modeling, is currently under development. The compiler interacts directly with the PCs i80X86 and the fuzzy parallel engine (in a master-slave configuration), and generates, at users request, intermediate flat ANSI C type code for portability.<<ETX>>

Predicted Optimum Composition for the Glass-Forming Ability of Bulk Amorphous Alloys: Application to Cu-Zr-Al.

Metallic glasses have been established to have unique properties such as ductility, toughness, and soft magnetism with promising engineering applications. However, the glass-forming ability (GFA) has not been sufficient to synthesize the bulk metallic glasses (BMGs) required for many engineering applications. Attempts to develop the understanding of the GFA required to predict the optimum alloys have not yet been proven successful. We develop here a computational model based on molecular dynamics simulations that explains the dramatic change of GFA with alloying small amounts of Al into Cu-Zr. We find that the high GFA to form BMGs depends on a combination of three factors, (a) a low thermodynamic driving force for crystallization, (b) a high melt viscosity, and (c) large ratios of icosahedral structures in the liquid phase. These computational methods to predict these factors that suppress formation of crystal nuclei and slow the dynamic motions in the liquids are practical for in silico prediction of new alloys with optimal GFA.

Ultraviolet surface plasmon-mediated low temperature hydrazine decomposition

Conventional methods require elevated temperatures in order to dissociate high-energy nitrogen bonds in precursor molecules such as ammonia or hydrazine used for nitride film growth. We report enhanced photodissociation of surface-absorbed hydrazine (N2H4) molecules at low temperature by using ultraviolet surface plasmons to concentrate the exciting radiation. Plasmonic nanostructured aluminum substrates were designed to provide resonant near field concentration at λ = 248 nm (5 eV), corresponding to the maximum optical cross section for hydrogen abstraction from N2H4. We employed nanoimprint lithography to fabricate 1 mm × 1 mm arrays of the resonant plasmonic structures, and ultraviolet reflectance spectroscopy confirmed resonant extinction at 248 nm. Hydrazine was cryogenically adsorbed to the plasmonic substrate in a low-pressure ambient, and 5 eV surface plasmons were resonantly excited using a pulsed KrF laser. Mass spectrometry was used to characterize the photodissociation products and indicated a...

Novel algorithms for massively parallel, long-term, simulation of molecular dynamics systems

Abstract In this paper, a novel algorithm for solution of the constrained equations of motion with application to simulation of the molecular dynamics systems is presented. The algorithm enables the solution of equations of motion with an internal coordinates model wherein the high-frequency oscillations are frozen by explicit inclusion of hard constraints in the system as well as by clustering of atoms and, thus, allowing a much larger time step in the integration. For a molecular system with N clusters, the algorithm achieves the optimal sequential complexity of O ( N ). However, the main advantage of this new algorithm is its efficiency for massively parallel computation. In fact, this is the first known algorithm that achieves a both time- and processor-optimal parallel solution for the constrained equations of motion, i.e. an optimal computation time of O (log N ) by using an optimal number of O ( N ) processors. In addition to its theoretical significance, this algorithm is also very efficient for practical implementation on the coarse grain MIMD parallel architectures owing to its highly decoupled computational structure.

First-Principles-Based Multiscale, Multiparadigm Molecular Mechanics and Dynamics Methods for Describing Complex Chemical Processes

We expect that systematic and seamless computational upscaling and downscaling for modeling, predicting, or optimizing material and system properties and behavior with atomistic resolution will eventually be sufficiently accurate and practical that it will transform the mode of development in the materials, chemical, catalysis, and Pharma industries. However, despite truly dramatic progress in methods, software, and hardware, this goal remains elusive, particularly for systems that exhibit inherently complex chemistry under normal or extreme conditions of temperature, pressure, radiation, and others. We describe here some of the significant progress towards solving these problems via a general multiscale, multiparadigm strategy based on first-principles quantum mechanics (QM), and the development of breakthrough methods for treating reaction processes, excited electronic states, and weak bonding effects on the conformational dynamics of large-scale molecular systems. These methods have resulted directly from filling in the physical and chemical gaps in existing theoretical and computational models, within the multiscale, multiparadigm strategy. To illustrate the procedure we demonstrate the application and transferability of such methods on an ample set of challenging problems that span multiple fields, system length- and timescales, and that lay beyond the realm of existing computational or, in some case, experimental approaches, including understanding the solvation effects on the reactivity of organic and organometallic structures, predicting transmembrane protein structures, understanding carbon nanotube nucleation and growth, understanding the effects of electronic excitations in materials subjected to extreme conditions of temperature and pressure, following the dynamics and energetics of long-term conformational evolution of DNA macromolecules, and predicting the long-term mechanisms involved in enhancing the mechanical response of polymer-based hydrogels.

A Unified Formulation for Massively Parallel Rigid Multibody Dynamics of O(log2n) Computational Complexity

Abstract A novel algorithm for the solution of the inverse dynamics problem is presented and augmented to the solution of the equations of motion (EOM) for rigid multibody chains using explicit constraint components of force. The unified model corresponds to an optimal, strictly parallel, time, space, and processor lower bound solution to the dynamics of accelerated rigid multibodies, i.e., computation time of O (log 2 n ) using O ( n ) processors for an n body system. Complex topological structures are supported in the form of multiple degree-of-freedom (DOF) joints/hinges, free-floating, hyper-branched, and/or closed-chain systems, with applications ranging from multibody molecular dynamics simulations and computational molecular nanotechnology, to real-time control and simulation of spatial robotic manipulators. In addition to the theoretical significance, the algorithms presented are shown to be very efficient for practical implementation on MIMD parallel architectures for large-scale systems.