Project Number: 3620-41000-120-00
Project Type: Appropriated

Start Date: Sep 02, 2004
End Date: Sep 01, 2009

Objective:
1. Investigate the tribological properties of ag-based products of interest in metalworking lubricant formulation. 2. Develop and apply tribological predictive models for ag-based raw materials of interest in metalworking lubricant formulation.

Approach:
(1) Bio-based materials of interest in metalworking lubrication will be obtained from various commercial and non-commercial sources. These will include starches, proteins, vegetable oils, modified vegetable oils, and composites (e.g. starch-oil composite FanteskTM). Chemically and/or enzymatically modified materials will be obtained from sources within and outside of ARS. Collaboration will be pursued with industry and academia actively engaged in the development of new bio-based raw materials. Tribological properties will be investigated using a variety of equipment currently available at NCAUR (4-ball EP, 4-ball AW, Timken EP, ball-on-flat, pin-on-disk, ball-on-disk, block-on-ring, EHD). Ex-situ and post-mortem -tribochemical studies will be conducted using instruments currently available at NCAUR. In-situ tribochemical studies will be conducted using instrument(s) to be developed later in the program. Tribosimulation tests will be conducted using Tapping Torque tribosimulator currently at NCAUR. Prototype tests will be conducted at partners' facilities. Formulations that successfully performed in prototype tests will be produced in pilot scale quantity at NCAUR. Commercial blenders will be certified for producing larger quantities for use in production mill trials. (2) Modeling efforts will be focused around metalworking processes of interest to partners. Models that allow for the prediction of interface film thickness and tribochemistry will be developed. These parameters are selected because of their profound effect on critical metalworking outcomes such as: friction, wear, product surface quality, lubricant quality, exposure, safety, pollution, etc. Development of these models requires detailed data on biobased materials, tools, workpiece, and process parameters. Some of this data will be generated in this program while others will be obtained from partners and/or from the literature. Predictive capability of models will be evaluated and fine-tuned through additional experiments in collaboration with CRADA partners. Models will then be implemented and used to help accelerate development of metalworking lubricant formulations for various metalworking applications.