Parallel machines are an important part of the scientific application developer's tool box and the processing demands placed on these machines are rapidly increasing. Many scientific applications tend to perform high volume data storage, data retrieval and data processing, which demands high performance from the I/O subsystem. In this paper, we conduct an experimental study of the I/O performed by the Hartree-Fock (HF) method, as implemented using a fully distributed data approach in the NWChem parallel computational chemistry package. We use PASSION, a parallel and scalable I/O library to improve the I/O performance of the application and present extensive experimental results. The effects of both application-related factors and system-related factors on the application's I/O performance are studied in detail. We rank the optimizations based on the significance and impact on the performance of HF's I/O phase as: I. efficient interface to the file system, II. prefetching, and III. buffering. The results show that within the limits of our experimental framework, application-related factors are more effective on the overall I/O behavior of this application. We obtained up to 95% improvement in I/O time and 43% improvement in the overall application performance with the optimizations.