Max R. Phelps
Battelle Memorial Institute
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Featured researches published by Max R. Phelps.
MRS Proceedings | 2002
Jamie D. Holladay; Evan O. Jones; Daniel R. Palo; Max R. Phelps; Ya-Huei Chin; Robert A. Dagle; Jianli Hu; Yong Wang; Ed G. Baker
Miniature and micro-scale fuel processors are discussed. The enabling technologies for these devices are the novel catalysts and the micro-technology-based designs. The novel catalyst allows for methanol reforming at high gas hourly space velocities of 50,000 hr-1 or higher, while maintaining a carbon monoxide levels at 1% or less. The micro-technology-based designs enable the devices to be extremely compact and lightweight. The miniature fuel processors can nominally provide between 25-50 watts equivalent of hydrogen which is ample for soldier or personal portable power supplies. The integrated processors have a volume less than 50 cm3, a mass less than 150 grams, and thermal efficiencies of up to 83%. With reasonable assumptions on fuel cell efficiencies, anode gas and water management, parasitic power loss, etc., the energy density was estimated at 1700 Whr/kg. The miniature processors have been demonstrated with a carbon monoxide clean-up method and a fuel cell stack. The micro-scale fuel processors have been designed to provide up to 0.3 watt equivalent of power with efficiencies over 20%. They have a volume of less than 0.25 cm3 and a mass of less than 1 gram.
Archive | 2001
Evan O. Jones; Jamie D. Holladay; Steve Perry; Rick Orth; Bob Rozmiarek; John Hu; Max R. Phelps; Consuelo Guzman
A sub-watt power system is being developed as an alternative to conventional battery technology to better meet energy and power densities needed for operating wireless electronic devices, such as microsensors and microelectromechanical systems. This system integrates a microscale fuel processor, which produces a hydrogen-rich stream from liquid fuels, such as methanol and butane, and a microscale fuel cell, which uses the hydrogen as fuel to produce electric power. Battelle, Pacific Northwest Division and Case Western Reserve University are developing and demonstrating this technology for the Defense Advanced Research Projects Agency. This paper describes work being performed by Battelle on the fuel processor, in particular, catalyst and reactor design and testing.
Supercritical Fluid Cleaning#R##N#Fundamentals, Technology and Applications | 1998
Max R. Phelps; Laura J. Silva; Michael O. Hogan
Publisher Summary This chapter discusses general parameters, processes, and procedures for scaling up supercritical fluid parts cleaning (SFPC) vessels at the mechanistic level. The chapter includes a, section which includes work at Pacific Northwest Laboratory (PNL), and describes the subsequent scaleup approach used in designing a transportable SFPC cleaning unit. Scaleup considerations for a cleaning system can be viewed from three different levels—overall, process, and mechanistic. It is mentioned that when scaling the process, the model and prototype must have Reynolds numbers in the same regime (i.e., laminar or turbulent flow) in order to achieve similar results. The process of scaleup can be simplified by dividing the principle of similarity into four separate states or categories—geometrical, mechanical, thermal and chemical. Overall scaleup considerations cover the entire cleaning operation, from acquiring and processing raw resources to the geographical distribution of the final product. The process level considers pumps, separators, cleaning vessels, condensers, solvents, and solutes collectively. At the mechanistic level, considerations are specific to each part in the process. The scaleup process is not just a matter of plugging values into prescribed equations, nor can exact scaleup criteria be obtained from generalized correlations for certain types of equipment. In a good scaleup approach, all variables that describe the process are determined; desired process conditions and the magnitude of the scaleup taken into account; and a design selected. Scaleup designs are based almost exclusively on the “principle of similarity.” The success of the scaleup approach is determined by comparing data obtained from both the model and the prototype.
Industrial & Engineering Chemistry Research | 1994
Douglas C. Elliott; Max R. Phelps; L.J. Sealock; Eddie G. Baker
Archive | 2002
Jamelyn D. Holladay; Max R. Phelps; Yong Wang; Ya-Huei Chin
Industrial & Engineering Chemistry Research | 1999
Douglas C. Elliott; Gary G. Neuenschwander; Max R. Phelps; Todd R. Hart; and Alan H. Zacher; Laura J. Silva
Archive | 2009
Jamelyn D. Holladay; Yong Wang; Jianli Hu; Ya-Huei Chin; Robert A. Dagle; Guanguang Xia; Eddie G. Baker; Daniel R. Palo; Max R. Phelps; Heon Jung
Archive | 2007
Jamelyn D. Holladay; Yong Wang; Jianli Hu; Ya-Huei Chin; Robert A. Dagle; Guanguang Xia; Eddie G. Baker; Daniel R. Palo; Max R. Phelps; Heon Jung
Archive | 2000
John L. Fulton; George S. Deverman; Dean W. Matson; Gordon L. Graff; Max R. Phelps
Archive | 1999
Max R. Phelps; Clement R. Yonker; John L. Fulton; Lawrence E. Bowman