A Resonant Graphene NEMS Vibrometer.

Measuring vibrations is essential to ensuring building structural safety and machine stability. Predictive maintenance is a central internet of things (IoT) application within the new industrial revolution, where sustainability and performance increase over time are going to be paramount. To reduce the footprint and cost of vibration sensors while improving their performance, new sensor concepts are needed. Here, double-layer graphene membranes are utilized with a suspended silicon proof demonstrating their operation as resonant vibration sensors that show outstanding performance for a given footprint and proof mass. The unveiled sensing effect is based on resonant transduction and has important implications for experimental studies involving thin nano and micro mechanical resonators that are excited by an external shaker.

Resonant Transducers Consisting of Graphene Ribbons with Attached Proof Masses for NEMS Sensors.

The unique mechanical and electrical properties of graphene make it an exciting material for nanoelectromechanical systems (NEMS). NEMS resonators with graphene springs facilitate studies of graphene's fundamental material characteristics and thus enable innovative device concepts for applications such as sensors. Here, we demonstrate resonant transducers with ribbon-springs made of double-layer graphene and proof masses made of silicon and study their nonlinear mechanics at resonance both in air and in vacuum by laser Doppler vibrometry. Surprisingly, we observe spring-stiffening and spring-softening at resonance, depending on the graphene spring designs. The measured quality factors of the resonators in a vacuum are between 150 and 350. These results pave the way for a class of ultraminiaturized nanomechanical sensors such as accelerometers by contributing to the understanding of the dynamics of transducers based on graphene ribbons with an attached proof mass.

Low ovarian responders produce more progesterone per follicle than normal and high responders.

OBJECTIVE: Late follicular premature progesterone rise is a complex phenomenon encountered during assisted reproductive technology (ART) treatments; different etiologies can occur in the same patient. Low ovarian responders may be the best example, since higher FSH doses and ovarian aging-related changes may interact and generate a premature progesterone rise. This study aims to explore the correlation between progesterone levels on hCG day and the progesterone-to-follicle index and compare the progesterone-to-follicle index according to ovarian response. METHODS: We performed a retrospective, observational, analytic, cross-sectional, and cohort study at the Reproductive Endocrinology Department at Centro Médico Nacional 20 de November between January 2015 to January 2020. After verifying for normalcy, a Spearman Rho, Principal Component Analysis, and a simple linear regression model were performed. Treatment cycles were classified according to their ovarian response. Low-ovarian responders were classified according to the Bologna Criteria. Then an ANOVA test was performed to compare each group. RESULTS: Our results show that the progesterone-to-follicle index correlates best with progesterone levels on hCG day. Comparing all the ovarian responses, low ovarian responders have the highest progesterone-to-follicle index of the four groups. CONCLUSIONS: Low ovarian responders produce more progesterone per follicle than regular and high responders.