1900 — 1982 |
Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Computer Simulation of Molecular Dynamics |
0.915 |
1981 — 2013 |
Zhuang, Yu (co-PI) [⬀] Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Computer Simulation of Chemical Dynamics
William Hase of Texas Tech University is supported by the Theory, Models and Computational Methods Program to enhance algorithms and software for studying chemical dynamics phenomena at short times.
Research goals comprise the development of accurate numerical implementations to compare results with experimental measurements, to determine fundamental information about intramolecular dynamics, energy transfer, and chemical dynamics. Four specific applications will be studied: i) soft-landing and reactive-landing of peptide ions on hydrocarbon surfaces for specific surface modifications; e.g. biological modifications to prepare protein microarrays, ii) surface-induced dissociation (SID) of protein multimers, iii) intrinsic non-RRKM unimolecular dynamics of low barrier isomerization reactions, and iv) post-transition state dynamics of organic reactions in condensed phases.
Chemical dynamics simulation studies will be compared with experimental results and are expected to provide new chemical knowledge. The computer programs and simulation models to be developed during the course of this project will be distributed to the scientific community, and will serve to enhance the theoretical/computational chemistry infrastructure.
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0.915 |
1984 — 1988 |
Lintvedt, Richard (co-PI) [⬀] Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Computer Simulation of Chemical Dynamics (Chemistry) |
0.915 |
1994 — 1995 |
Bach, Robert Schlegel, H. Bernhard Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Acquisition of a Computing Facility For Computational Chemistry
This award from the Chemistry Research Instrumentation and Facilities Program will assist the Department of Chemistry at the Wayne State University in the purchase of a Convex SPX writer, and a cluster of three HP 735 processors. This equipment will enhance research in a number of areas including the following: (1) perform numerically intensive calculations in the research areas of electronic structure theory and chemical kinetics and dynamics; (2) further develop general computer programs such as VENUS and Gaussian; and (3) educate students in the field of computational chemistry. A workstation network of fast, modern computer workstations is a new way to satisfy the computing needs of chemistry departments. Such a "computer network" also serves as a development environment for new theoretical codes and algorithms, and provides state-of-the-art graphics and visualization facilities.
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0.915 |
1997 — 2001 |
Conrad, Michael (co-PI) [⬀] Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Neuromolecular Computer Design Through Adaptive Surface Engineering
*** 9704190 Conrad Artificial neuromolecular (ANM) architectures are brain-like computer designs in which the input-output capabilities of the neuronal units are controlled by internal dynamics that serve to fuse signals in space and time. These internal (or intra-neuronal) dynamics are motivated by molecular process believed to be operative in real neurons. The pattern processing and control capabilities of the global architecture this draw on neuronal as well as network level dynamics. Evolutionary algorithms orchestrate this repertoire into groupings suitable for coherent perception-action tasks, including tasks involving complex sequences of actions. The system is being applied to Chinese character differentiation and recognition/effector control behavior in a maze-like environment. The objective of this project is to develop a methodology for designing networks to increase the effectiveness of evolutionary computing as an adaptation technique. The AM architecture is use as the testbed. Four submodels with different types of dynamics have bee developed for this purpose. The first is an abstract (dual dynamics), network model that consist of pattern recognizing components subject to weak collective interactions. The second, the cytomatrix neuron, is a softened cellular automaton. the third is a coupled oscillator model motivated by the neuron cytoskeleton. the fourth is a general simulation system that can be used to model motivated by the neuronal cytoskeleton. The fourth is a general simulation system that can be used to model a wide variety of intracellular dynamic processes involving the co-action of kinetic and structural processes. These different submodels con be studied in their own right and also can be embedded in the neural units of ANM system. The comparative experimental study of these models complement theoretical analysis and provided guidelines for adaptive surface engineering pertinent to a wide variety of neural architectures. ***
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0.915 |
1999 — 2002 |
Schlegel, H. Bernhard Goldfield, Evelyn (co-PI) [⬀] Edjlali, Guy Chaudhary, Vipin [⬀] Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Mri: Acquisition of a Cluster of Symmetric Multiprocessors
EIA-9977815 Chaudhary, Vipin Guy, Edjlali Wayne State University
MRI: Acquisition of a Cluster of Symmetric Multiprocessors
The purpose of this proposal is to set up a high performance computing cluster consisting of symmetric multiprocessors connected by a high speed switched network to support research and training in an advanced parallel programming environment. The specific goals include: 1) develop programming environments to effectively use a cluster of multiprocessors for scientific computing, 2) develop general computer programs for modeling and simulation, 3) educate students in the field of computational science and engineering and 4) perform numerically intensive calculations in the research areas of electronic structure theory; classical, semi-classical and quantum molecular dynamics simulations; Monte Carlo simulations of electronic devices; and the development of powerful procedures for automatic parallelization. These goals will be achieved through the proposed Automatic Parallelization Environment or Network of Workstations programming environment.
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0.915 |
2000 — 2007 |
Schlegel, H. Bernhard Goldfield, Evelyn (co-PI) [⬀] Edjlali, Guy Chaudhary, Vipin (co-PI) [⬀] Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Igert Full Proposal: Interdisciplinary Traineeship in High Performance Computing Applications
9987598 William Hase - Wayne State University IGERT: Interdisciplinary Traineeship in High Performance Computing Applications
This Integrative Graduate Education and Research Training (IGERT) award supports the establishment of a multidisciplinary graduate training program of education and research in high performance computing. This project will integrate ongoing interdisciplinary research efforts in our new Institute for Scientific Computing into a cooperative traineeship program. The program will build upon existing high-performance computing related projects, many with industrial collaboration, to develop a concerted thrust in the area of scientific computing, a growing research strength at Wayne State University. Active programs in computer intensive, data intensive, and real-time computing will form the core research that will be the hallmark of a new interdisciplinary Masters/Ph.D. curriculum. The curriculum will consist of an integrated series of hands-on (lecture and laboratory) courses and seminars on scientific computing developed by university and industrial participants. Graduate thesis training will be based on teaming where students work individually on different components of a major interdisciplinary project. Programs using high performance computing in the following strategically important areas are envisioned: (i) Medicine, Genetics, and Biochemistry, (ii) Chemistry, Physics, and Materials Science, and (iii) Automotive and Aerospace Systems. This research-educational initiative has the active support of industry, particularly Ford, IBM, SGI, SUN, and CFD Research, who will provide substantial resources as a match to initiate this program and who will participate in lectures, research training, and oversight/assessment of the project. Wayne State University will commit more than $2,320,000 in resources to support this program. To ensure the success of this training program and to be competitive with the many opportunities in scientific computing, Wayne State University is supplementing the graduate stipends to give a total stipend of $23,266/year. With this stipend and the strength of the training program, we will be able to recruit outstanding students.
IGERT is an NSF-wide program intended to meet the challenges of educating Ph.D. scientists and engineers with the multidisciplinary backgrounds and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing new, innovative models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries. In the third year of the program, awards are being made to nineteen institutions for programs that collectively span all areas of science and engineering supported by NSF. The intellectual foci of this specific award reside in the Directorates for Computer and Information Science and Engineering, Mathematical and Physical Sciences, Engineering, Biological Sciences, and Education and Human Resources.
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0.915 |
2002 — 2007 |
Xu, Chengzhong Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Algorithms: Adaptive Stochastic Scheduling For Bulk Synchronous Computations and Its Application in Molecular Dynamics Simulations
This research investigates the parallel efficiency of an important class of bulk synchronous applications, as exemplified by computational molecular dynamics, in clusters of workstations. Bulk synchronous applications are often characteristic of non-deterministic computational requirements over time. In a multiprogramming environment, the nodal capacities allocated to an application may also change as other jobs join and leave. With respect to the dynamics of the computation and uncertainties of the cluster resources, this research aims at developing stochastic scheduling strategies in support of high performance computing in the clusters. It constructs a framework for modeling and analyses of adaptive scheduling algorithms by characterizing scheduling factors as random variables. It develops efficient application-level remapping policies by taking into account the dynamic systems of workload evolution and capacity change. The scheduling strategies are evaluated in the application of molecular dynamics computer simulations.
The research will blend formal modeling/analyses, experimentation, and evaluation of stochastic scheduling algorithms. Success of this research will help increase the industrial acceptance of high performance cluster computing and advance computational molecular dynamics to simulations of large, multi-atom systems in a timely manner.
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0.915 |
2007 — 2013 |
Tully, John Windus, Theresa Zhuang, Yu (co-PI) [⬀] Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Pire: Simulation of Electronic Non-Adiabatic Dynamics For Reactions With Organic Macromolecules, Liquids, and Surfaces
0730114 Hase
This award provides support for a proposal submitted to the 2007 OISE Partnerships for International Research and Education (PIRE) competition. It involves a collaboration on the US side between Texas Tech and Yale Universities and the University of Santiago da Compostela in Spain, the University of Pisa in Italy, and the University of Vienna in Austria.
Intellectual Merit. The collaborative partners propose to address electronic non-adiabatic transitions between multiple potential energy surfaces in chemical reactions with organic macromolecules. The research partners have combined expertise in multiple theoretical methods required to address this problem. The US and European partners have developed software for chemical dynamics simulations. They will unify and expand this software to develop the "leading" software package to simulate electronic non-adiabatic transitions for complex chemical reactions in condensed phases and in the gas phase. The second element of the project is to apply the software to the following problems: reaction of oxygen molecules with liquid hydrocarbon fields; reaction of energetic oxygen atoms with polymer surfaces, and collisions of projectile ions with organic surfaces in ion implantation and surface-induced dissociation processes. The Pisa and Vienna groups are part of a larger, related, pan-European project supported by the European Science Foundation, which provides the US side access to the larger ESF project.
Broader Impacts. The project will train a diverse group of undergraduate and graduate students in "cutting edge" research within a multidisciplinary, collaborative, and international environment. Attracting women and under-represented groups will be a priority. The PI has developed mechanisms for working with high school students as well. The project will develop new, cutting edge software, and develop a model for scientific computing involving international collaboration. The project's dissemination efforts will include a summer institute to educate a broader community in the use of the developed algorithms and software. The project's results may have an impact on other fields such as materials processing and molecular biology.
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0.915 |
2009 — 2013 |
Morales, Jorge (co-PI) [⬀] Poirier, Lionel Hase, William Gellene, Gregory (co-PI) [⬀] Korzeniewski, Carol [⬀] Casadonte, Dominick (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
A Cluster For Cyber-Enabled Research and Education in Computational Chemistry
With support from the Chemistry Research Instrumentation and Facilities: Multiuser program (CRIF:MU), the Department of Chemistry at Texas Tech University will acquire a 10.8 TeraFlop, parallel computing cluster. The computing cluster will be used by researchers to study a number of problems in the chemical sciences, including (a) the hydrolysis of cellulose as an efficient route to biofuels; (b) simulations of electrochemical surface reactions; (c) accurate quantum dynamical calculations for chemical reactions; (d) the role of non-adiabaticity in the chemistry of the early universe; (e) dynamics of protonated peptide ion surface-induced decomposition; and (f) studies of electronically non-adiabatic dynamics using a coherent-states model. The computing cluster will be used in a number of ongoing activities carried out by the department targeted to groups which have been traditionally underrepresented in the sciences. Software will be developed and freely-disseminated. Cyberinfrastructure will enable researchers at other schools (i.e. Eastern New Mexico University, and University of Texas, Permian Basin) to use this equipment.
Modern computer infrastructure allows chemists to do some experiments , virtually, without the need to use chemical reagents. In addition, checked against experiment, new, more accurate theoretical methods may be developed. In tandem with experiment, computations allow chemists to examine, in detail beyond that of current experimental methods, the molecular ballet that takes place in complicated chemical processes. The infrastructure made available with this grant will be used in teaching and training a broad range of young scientists in computational chemistry -- from high school, all the way through the post-graduate level.
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0.915 |
2015 — 2018 |
Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
International Collaboration in Chemistry: Development and Application of Direct Dynamics Simulations For Studying the Fragmentation and Reaction of Biological Molecules
In this award, funded by the Chemical Structure, Dynamics and Mechanisms (CSDM-A) Program, the Chemical Theory, Models and Computational Methods (CTMC) Program and the Chemical Measurement and Imaging (CMI) Program of the Division of Chemistry, Professor William Hase of Texas Tech University, his French collaborators (funded by the ANR) and Texas Tech University post-doctoral, graduate and undergraduate student researchers are conducting computational studies of the ways that biomolecular ions react in the gas phase. These studies will help to inform scientists who are using mass spectrometry methods to analyze the composition of complicated mixtures of biomolecules ? a ubiquitous problem in the biosciences. Post-doctoral, graduate and undergraduate students working on this project will receive world-class training in computational chemistry, while working with young scientists from France.
Prof. William Hase will collaborate with Prof. Riccardo Spezia from CNRS, Laboratoire Analyse et Modelisation pour Biologie et l?Environment. The US and French research groups are conducting a multi-pronged research effort investigating the reactions and dynamics of biomolecules in the gas phase. The two groups will: (1) model tandem mass spectrometry experiments of the fragmentation of peptides, carbohydrates and steroids; (2) model the gas-phase production of biomolecules from precursor species. The young researchers working on this project will receive excellent technical training, and will work alongside some of the best French researchers in this field. The software that is developed in this project will be incorporated into existing software packages that are used by a wide range of researchers.
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0.915 |
2018 — 2021 |
Dai, Dong Chen, Yong Ancell, Brian Hase, William |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Elements:Software:Nsci: Empowering Data-Driven Discovery With a Provenance Collection, Management, and Analysis Software Infrastructure
Scientific breakthroughs are increasingly powered by advanced computing and data analysis capabilities delivered by high performance computing (HPC) systems. In the meantime, many scientific problems have moved to a level of complexity that the ability of understanding the results, auditing how a result is generated, and reproducing the important experiments or simulation results, is critical to scientists. Enabling such a capability in HPC systems requires a holistic collection, management, and analysis software infrastructure for "provenance" data, the metadata that describes the history of a piece of data. Such a software infrastructure does not exist yet, which motivates the proposed software development of a lightweight provenance service. With such a software element, many advanced data management functionalities such as identifying the data sources, parameters, or assumptions behind a given result, auditing data history and usage, or understanding the detailed process that how different input data are transformed into outputs can be possible. Responding to the National Strategic Computing Initiative, this project will provide an attractive software infrastructure to future national HPC systems to improve the productivity of science in complex HPC simulation and analysis cycles. The project team will also recruit underrepresented students, mentor graduate and undergraduate students, integrate results into curriculum, and publish and disseminate results.
The lightweight provenance service software on HPC systems will provide: 1) an always-on, background service that automatically and transparently collects and manages provenance for scientific applications, 2) captures comprehensive provenance with accurate causality to support a wide range of use cases, and 3) provides easy-to-use analysis tools for scientists to quickly explore and utilize the provenance. This project will integrate the development, education, and outreach efforts tightly together.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.915 |