DNTMC is a tool for estimating the kinetics of molecular agglomeration in aerosols. The ultimate goal is to use DNTMC to gain insight into atmospheric nucleation processes that influence climate. Useful application of the DNTMC method involves sampling millions of configurations (geometries) for multiple clusters of weakly interacting molecules. This sampling is parallelized by having multiple Markov chains (walkers) explore configuration space. The current implementation is a data-parallel design in which compute processes are evenly arranged into groups, each generating one chain. Every some number of samples, results from all groups are merged and analyzed to determine if independent sampling should continue. This design works very well provided all groups reach the synchronization point in close proximity. When energies are evaluated with iterative methods, solution time can be dependent on geometry and chains may not advance at the same rate. Because process groups do not reach the synchronization barrier at the same time, sampling rate variability can cause significant idling of resources. A potential solution to this load imbalance is to create an actively managed task distribution system through which Markov chains can be dynamically assigned to process groups. If there are more chains than process groups, a task manager can minimize variation in sampling rates by giving slower chains more computing time. This task-parallel design also has the advantage of replacing the periodic active synchronization of the current implementation with passive alternatives. While idle resources should be minimized, some overhead is introduced from use of manager processes (fewer to compute energies) and from the communication needed to distribute tasks and collect results. Though it won't match the ideal performance of the current implementation, the new design should provide greater overall efficiency for those cases needing dynamic load balancing.
Understand the processes and interactions that attempt to explain the recalcitrance of cellulose to decomposition. One project deals with B3LYP and two-body fragment molecular orbital (FMO-2) calculations of energies resulting from the rotation of dihedral angles formed by free hydroxyl groups in glucose residues of a cellulose fragment, and the rotation of torsion angles involving glycosidic linkages between glucose residues in cellulose (psi and phi angles). The use of FMO-2 allows us to pinpoint specific interactions among the glucose residues in cellulose that give rise to critical points in the potential energy curves obtained from the changing cellulose geometries.
A second project is a simulation of the reaction mechanism of the acid-catalyzed hydrolysis of cellobiose, the repeating unit of cellulose. In this project, EFP1 (effective fragment potential) water molecules are used to form a first solvation shell around the cellobiose molecule. The polarizable continuum model (PCM) is used to form a second solvation shell.
Accurate Potential Energy Curve for C2
Diatomic carbon, C2, is found in hydrocarbon flames, comets, and the interstellar medium. C2 has an interesting electronic structure, including several low-lying excited states, and a ground state which exhibits strong multiconfigurational character even at equilibrium. The potential energy curve (PEC) of C2 dissociation is being calculated using the correlation energy extrapolation by intrinsic scaling (CEEIS) method. CEEIS was developed by Ruedenberg and Bytautas to estimate the full configuration interaction energy. The method employs a linear extrapolation between a series of configuration interaction calculations with truncated virtual orbital spaces. CEEIS has already been used to obtain high accuracy correlation energies in several diatomic systems (F2, O2, B2). Additional corrections to the PEC (core-electron correlation, scalar relativistic effects, spin-orbit coupling) were applied to these systems to obtain near spectroscopic accuracy. Our current work focuses on obtaining highly accurate PECs for the ground state, well as several excited singlet states.
I-A: Implementation of Dynamical Nucleation Theory using the ab initio based Effective Fragment Potentials (DNTEFP).
Identified new transition state structures of water hexamer clusters relevant to molecular nucleation. Predicted that the rate of evaporation of water from isoprene water cluster increases with respect to the rate of evaporation of water from pure water hexamer cluster. This is the first result of multi-component nucleation using the abinito based molecular nucleation Theory. (Results presented at ACS National Meeting Fall 2010, Boston, MA. (Submitted to. J. Phys. Chem A )
I-B: Implementation of Multi chain Monte Carlo and Multilevel Parallel Molecular Nucleation Model using the Ab initio based EFP potential (MMC-EFP-NM).
I-C: Implementation of molecular nucleation model using the all atom ab initio Fragment Molecular orbital Potentials. (FMO-NM).
Evaporation rates of multi-component clusters containing open shell radicals were predicted for the first time. (Results Presented at ACS Spring National Meeting, Anaheim, March 2011).
I-D: Implementation Multilevel Parallel Fragment Molecular Obital Theory Monte Carlo for modeling Molecular Nucleation (FMO-NM) (Work in Progress)
PROJECT II: Bio Energy Sciences Project
Computational Search to enable a faster and economically viable conversion of biomass to ethanol
Fig 1A. I-alpha -12chains -144 units) FMO-study
Fig 1B. alpha-233- Cellotetraose FMO study
Fig 1C. celluloseIII +h2o ( 2 ns-- MD-charmm Potential)
Fig 1D. 8CelA + nanocellaose (4ns MD Charmm27 potential)
A. Molecular Origins of Cellulose Recalcitrance: Goal is to understand hydrogen bonded network in polymorphs of Cellulose using complex electronic structure theory methods. (Results presented in SCIDAC Meeting 2011). First FMO studies of cellulose. (Fig. 1A)
B. Using Model of cellulose-assembly: Goal is to obtain FMO based statistical weights for strengths of hydrogen bonded interaction (case study cellotetraose)--(Fig. 1B)
C. All atom, FMO and CGMD simulations of crystalline cellulosic materials with explicit water: Chain dynamics (Results Presented in SCIDAC Meeting 2011)(Fig. 1C)
D. Biohydrolysis of cellulose: cellulose-protein binding dynamics using the all atom MD and FMO study (Fig. 1D)
Malonic acid is a common organic aerosol found in the atmosphere. It exists in two tautomers, a ketone and enol form. Malonic acid can react with other atmospheric substances and its reactivity may be linked to the more common tautomer in a highly concentrated deliquesced particles. Using DFT, B3LYP allows for the elucidation and confirmation of IR frequencies indicating a more abundant enol structure in the malonic acid particles. DFT is useful in this application due to the need for calculations on large systems of hundreds of atoms or more. To efficiently sample many structures on the potential energy surface (PES) and to find several low energy conformations, effective fragment potential (EFP) methods with simulated annealing in GAMESS are employed.
Stereospecific catalytic reactions are important for drug design. This work focuses on computational mechanism elucidation of Zirconium catalyzed hydroamination using MP2 single point energies of DFT optimized structures.
Adding and enhancing GPU functions in NWChem and GAMESS, as well as developing algorithms for heterogeneous computing environments.
Considering a long interest in transition metals and their behavior, theoretical studies have been employed to understand them on a more fundamental level. Current work involves gas-phase reactions of transition metal ions with small molecules such as CO and CO2. These reactions involve clustering and/or activation of the C-O bond to form M-O and C-O. Experimental results are augmented by computational studies exploring possible products and mechanisms which can involve avoided crossings. Other work involves developing quasi-atomic minimal basis set approach to transition metal species.
Having knowledge of the iridium cluster size and structure will lead to further knowledge of its catalytic properties and the properties of other metals with hydrazine. In the future, this information could help to create more efficient rocket fuel cells. Previous theoretical studies employ DFT thus it will be important to understand how to effectively use DFT.
Update coming soon!