On-chip nano-optomechanical systems (NOMS) have demonstrated a zeptogram-level mass sensitivity and are promising candidates for low-cost implementations in areas such as metabolite quantitation and chemical analysis. High responsivity and sensitivity call for substantial optomechanical coupling and cavity finesse, resulting in detuning-dependent stiffness and mechanical damping via optomechanical back-action. Since mass loading (or temperature or force change) can alter both mechanical and cavity properties, mechanical frequency shifts induced by loading can encompass both effects. Precision sensing requires understanding and quantifying the source of the frequency tuning. Here, we show the deconvolution of direct loading and optomechanical stiffness change on the mechanical eigenfrequency as a function of detuning for a nano-optomechanical sensor in gaseous sensing experiments. Responses were generally dominated by shifts in optical stiffness and resulted in a mass loading signal amplification by as much as a factor of 2.5. This establishes an alternative possible route toward better mass sensitivity in NOMS while confirming the importance of incorporating optical stiffness effects for precision mass sensing.
BackgroundThe application and appropriate use of imaging-based scoring instruments is usually based on passive learning from published manuscripts while real-time interaction with instrument developers is often non-feasible. Moreover, most instruments lack knowledge transfer tools that would facilitate attainment of pre-specified performance targets for reader reliability.Objectives1. To develop a web-based calibration module for the SPARCC MRI SIJ Inflammation Score based on consensus scores from these instrument developers, experiential game psychology, and real-time iterative feedback. 2. To test the feasibility and attainment of pre-specified performance targets for reader reliability.MethodsThe scoring of inflammatory lesions of the SIJ on MRI using the SPARCC method is based on SIJ quadrants and the calibration module is comprised of 50 DICOM cases, each with scans from baseline and 12 weeks after the start of TNF inhibitor therapy. Scans are scored blinded-to-time-point. Continuous visual real-time feedback regarding concordance/discordance of scoring per SIJ quadrant with expert readers is provided by a color-coding scheme. Reliability is additionally assessed by real-time intra-class correlation coefficient with the first ICC data being provided after 20 cases. Accreditation for SPARCC BME score is achieved with status and change score ICC of >0.8 and>0.7 and is based on the final 20 cases. 26 readers scored the SPARCC BME module (7 rheumatology fellows, 2 chiropracters, 1 undergraduate, 8 rheumatologists, 8 radiologists) with 21 having no prior experience. Feasibility was assessed by 8-item survey.ResultsThe majority of readers achieved accreditation for SPARCC BME score on the basis of sufficient reliability with instrument developers for both status and change scores, irrespective of prior experience (table 1). All readers who completed the module a second time, 6 months after the first exposure, achieved accreditation for SPARCC BME score. All readers rated the modules as easy and intuitive with average time for reading each case for SPARCC BME being 8 min.Abstract FRI0597 – Table 1*Proficiency targets for reader reliability**7 rheumatology fellows, 2 chiropractors, 1 undergraduateConclusionsExperiential web-based learning is an effective and feasible calibration tool to achieve proficiency targets in the scoring of MRI scans for SIJ inflammatory lesions.Disclosure of InterestW. Maksymowych Shareholder of: CaRE Arthritis, S. Krabbe: None declared, D. Biko: None declared, P. Weiss: None declared, M. Maksymowych: None declared, J. Cheah: None declared, G. Kröber: None declared, U. Weber: None declared, K. Danebod: None declared, P. Bird: None declared, P. Chiowchanwisawakit: None declared, J. Moeller: None declared, M. Francavilla: None declared, J. Stimec: None declared, T. Kogay: None declared, V. Zubler: None declared, M. Battish: None declared, N. Winn: None declared, D. Rumsey: None declared, R. Guglielmi: None declared, S. Pedersen: None declared, H. Boutrup: None declared, S. Shafer: None declare...
Nano-optomechanical systems (NOMS) achieve high-precision measurement of displacement which enables very high sensitivity through mechanical resonance-shift sensing. A recent breakthrough [1] has shown that NOMS devices can operate in high-damping environment without sacrificing their frequency stability and sensing resolution. This is because stability losses from lower quality factor (Q) are offset by stability gains from a larger intrinsic signal-to-noise ratio. We take advantage of this excellent stability to do atmospheric pressure resonant mechanical gas sensing with high sensitivity using NOMS [2]. In particular, we have set up a traditional gas chromatograph to output to a NOMS detector and shown parts-per-billion level detection [2]. By modifying the NOMS devices to make the silicon cantilevers porous, we have improved sensitivity by a further factor of 10 [3]. The next challenge, and opportunity, in using NOMS for mass sensing, is to separate the gas loading signals that affect both the mechanical and optical resonances in high optomechanical-coupling devices [4]. This is because, at high coupling, changes in optical resonance produce changes in mechanical resonance and vice versa. This effect can be used to amplify the sensing signal obtained when measuring mechanical frequency changes. In fact, it scales particularly well with high-finesse optical cavities and could lead to a situation where evanescent field gas loading on the optical cavity is transduced as a mechanical frequency shift with orders of magnitude better mass sensitivity than could be realized from the NEMS alone or the optical cavity alone. As an example, our present mass loading sensitivity is around 50 kDa [5]; improving the cavity linewidth merely by a factor of 10 should shrink that mass sensitivity by a factor of 1000, bringing it down to 50 Da. This level of sensitivity would allow studying chemical adsorption and desorption of individual gas chromatography molecules on the sensor surface and could provide a simple path for obtaining orthogonal information in gas chromatography detectors. [1] S. K. Roy, V. T. K. Sauer, J. N. Westwood-Bachman, A. Venkatasubramanian, and W. K. Hiebert, Improving mechanical sensor performance through larger damping. Science 360, eaar5220 (2018); doi: 10.1126/science.aar5220. [2] A. Venkatasubramanian, et al., Nano-optomechanical systems for gas chromatography. Nano Lett. 16, 6975-6981 (2016); doi: 10.1021/acs.nanolett.6b03066. [3] A. Venkatasubramanian, et al., Porous nanophotonic optomechanical beams for enhanced mass adsorption. ACS sensors 4, 1197-1202 (2018); doi: 10.1021/acssensors.8b01366. [4] M. P. Maksymowych, J. N. Westwood-Bachman, A. Venkatasubramanian, and W. K. Hiebert, Optomechanical spring enhanced mass sensing. Appl. Phys. Lett. 115, 101103 (2019); doi: 10.1063/1.5117159 [5] Da = Dalton = 1 amu = 1 atomic mass unit ~ 1.66 x 10-27 kg.
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