Inglewood, CA, July 18, 2018 --(PR.com
)-- Minus K Technology celebrating its 25th year in business, will grant at least $20,000* of its superior performing patented Negative-Stiffness low-frequency vibration isolators to colleges in the United States.
Minus K’s vibration isolators have been used in a wide variety of applications where the elimination low-frequency vibrations is critical, such as microscopy; neuroscience; laser-optical systems; micro-hardness testing; spacecraft testing and more.
Past giveaway winners include: Arizona State University, California Polytechnic State University San Luis Obispo, University of Michigan, City University of New York, Irvine Valley College, Northwestern University, Purdue University, Saint Louis University, Saint Olaf College, Spokane Community College, Stanford University, University of California, Berkeley, University of California Davis, University of California Merced, University of Rochester, University of Tennessee, University of Texas at Dallas, Washington University in Saint Louis, Willamette University.
Recipients of a Minus K isolator will be chosen based on the proposed use and applicability of the isolators. Deadline to apply is February 28, 2019. Winners will be notified via email and will also be posted on Minus K’s website (www.minusk.com). The grantees will be interviewed six months after receiving their equipment to learn how their Minus K vibration isolators helped them reach their goals. The interviews will be used for articles in industry publications.
Entry form and more information are available on Minus K’s website www.minusk.com.
For more information, please contact:
Steve Varma, Operations Manager
Minus K Technology, Inc.; 460 Hindry Ave., Unit C, Inglewood, CA 90301
Email: email@example.com; www.minusk.com
* $20,000 of retail products will consist of at least one each of the following models of Negative-Stiffness vibration isolators: WS-4, BM-1, BM-4, BM-8, BM-10 and CM-1. Based on the number of qualified application forms received and Minus K may substitute different models to best accommodate the application and payload needs.