Kasthurirangan Gopalakrishnan

Learn More
Mixed-Ionic-Electronic-Conduction (MIEC) at 100% yield G. W. Burr, K. Virwani, R. S. Shenoy, A. Padilla, M. BrightSky†, E. A. Joseph†, M. Lofaro†, A. J. Kellock, R. S. King, K. Nguyen, A. N. Bowers, M. Jurich, C. T. Rettner, B. Jackson, D. S. Bethune, R. M. Shelby, T. Topuria, N. Arellano, P. M. Rice, B. N. Kurdi, and K. Gopalakrishnan IBM Almaden Research(More)
The mission of the Institute for Transportation (InTrans) at Iowa State University is to develop and implement innovative methods, materials, and technologies for improving transportation efficiency, safety, reliability, and sustainability while improving the learning environment of students, faculty, and staff in transportation-related fields. The contents(More)
This paper describes the current state of RUgle, a system for classifying and indexing papers made available on the World Wide Web, in a domain-independent and universal manner. By building RUgle with the most relaxed restrictions possible on the formatting of the documents it can process, we hope to create a system that can combine the best features of(More)
versity is to develop and implement innovative methods, materials, and technologies for improv­ ing transportation efficiency, safety, and reliability while improving the learning environment of students, faculty, and staff in transportation-related fi elds. The contents of this report reflect the views of the authors, who are responsible for the facts and(More)
3D crosspoint memory based on Mixed-Ionic-Electronic-Conduction (MIEC) Materials K. Virwani, G. W. Burr, R. S. Shenoy, C. T. Rettner, A. Padilla, T. Topuria, P. M. Rice, G. Ho†, R. S. King, K. Nguyen, A. N. Bowers, M. Jurich, M. BrightSky†, E. A. Joseph†, A. J. Kellock, N. Arellano, B. N. Kurdi and K. Gopalakrishnan† IBM Almaden Research Center, 650 Harry(More)
Various models have been developed over the past several decades to predict the dynamic modulus |E*| of Hot-Mix Asphalt (HMA) based on regression analysis of laboratory measurements. The models most widely used in the asphalt community today are the Witczak (1999 and 2006) predictive models. Although the overall predictive accuracies for these existing(More)
We demonstrate compact integrated arrays of BEOL-friendly novel access devices (AD) based on Cu-containing MIEC materi-als[1-3]. In addition to the high current densities and large ON/OFF ratios needed for Phase Change Memory (PCM), scaled-down ADs also exhibit larger voltage margin Vm, ultra-low leakage (<10pA), and much higher endurance (>10 8) at high(More)
Phase change memory (PCM) could potentially achieve high density with large, 3D-stacked crosspoint arrays, but not without a BEOL-friendly access device (AD) that can provide high current densities and large ON/OFF ratios. We demonstrate a novel AD based on Cu-ion motion in novel Cu-containing Mixed Ionic Electronic Conduction (MIEC) materials[1, 2].(More)
This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data. The HWD test is one of the most widely used tests for routinely assessing the(More)