High mechanical Q-factor measurement of Si using a 3D cantilever support.

Rev Sci Instrum

Department of Physics, ARC Centre of Excellence for Gravitational Wave Discovery, University of Western Australia, Crawley WA 6009, Australia.

Published: October 2022

Thermal noise in test mass substrates and coatings is a significant noise contribution in the detection band of current and proposed future gravitational wave detectors. Substrate thermal noise can be reduced by using high mechanical Q-factor materials and cooling the test mass mirrors. Silicon is a promising potential candidate for the next generation detector test masses. The low thermal expansion and high thermal conductivity of silicon allow efficient cryogenic operation, and a significant increase in the amount of optical power that can be used in the detectors by decreasing thermal deformation and aberration. Mechanical stress, damage, poor surface quality or contamination can result in increased loss and thermal noise. Therefore, the characterization of mechanical loss in silicon test masses is necessary. In this project, we developed a technique to measure high Q-factor mechanical modes. We used finite element modeling to optimize the design of the test mass support structure to minimize the loss coupling from the support structure over a wide frequency range. Mechanical Q-factors of the order of 10 were achieved for several modes of a 10 cm diam. × 3 cm cylindrical silicon test mass with such a support at room temperature.

Download full-text PDF

Source
http://dx.doi.org/10.1063/5.0106565DOI Listing

Publication Analysis

Top Keywords

test mass
16
thermal noise
12
high mechanical
8
mechanical q-factor
8
test masses
8
silicon test
8
mass support
8
support structure
8
thermal
6
test
6

Similar Publications

Background: Many studies have examined the prevalence of acetabular version (AV) and femoral version (FV) abnormalities and their effect on patient-reported outcomes (PROs) after hip arthroscopy for femoroacetabular impingement syndrome (FAIS), but few have explored the prevalence and influence of combined version (CV) abnormalities.

Purpose: To (1) describe the distribution of AV, FV, and CV in the largest cohort to date and (2) determine the relationship between AV, FV, and CV and PROs after hip arthroscopy for FAIS.

Study Design: Cohort study; Level of evidence, 3.

View Article and Find Full Text PDF

Nobiletin: a potential erythropoietin receptor activator protects renal cells against hypoxia.

Apoptosis

January 2025

Department of Pharmacology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, 710061, China.

Tangerine peel is a traditional Chinese herb and has been widely applied in foods and medicine for its multiple pharmacological effects. Erythropoietin receptor (EPOR), a member of the cytokine receptor family, is widely expressed in multiple tissues in especial kidney and plays protective effects in adverse physiological and pathological conditions. We hypothesized that it might be EPOR agonists existing in Tangerine peel bring such renal benefits.

View Article and Find Full Text PDF

Afforestation projects on saline land, using Eucalyptus trees and ectomycorrhizal fungi, are crucial for restoring affected areas and promoting ecological and economic benefits, particularly in saline-affected areas. This study was conducted to isolate Pisolithus sp. and estimate its potential to improve the growth performance of Eucalyptus globulus seedlings under salt-stress conditions.

View Article and Find Full Text PDF

Functional fitness and psychological well-being in older adults.

BMC Geriatr

January 2025

Institute of Health Promotion and Sport Sciences, Faculty of Education and Psychology, ELTE Eötvös Loránd University, Bogdánfy St. 12, Budapest, H-1117, Hungary.

Background: Physical fitness and functioning are related to better mental health in older age. However, which fitness components (body composition, strength, flexibility, coordination, and endurance) are more closely related to psychological well-being (PWB) is unclear.

Methods: This research examined how body mass index (BMI) and six indices of functional fitness (i.

View Article and Find Full Text PDF

Effective prediction of organosilicon molecular structures and risks in aquatic environment with machine learning.

Sci Total Environ

January 2025

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 330106, China.

Until now, mass spectrometry databases lack molecular information of most organosilicon oligomers, and risk models needing accurate molecular descriptors are unavailable for these emerging contaminants with thousands of monomers. To address this issue, based on molecular/fragment ions and relative abundance from GC-Orbitrap-MS, this study developed appropriate classification (accuracies = 0.750-0.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!