A comparsion of force sensors for atomic force microscopy based on quartz tuning forks and length extensional resonators

TL;DR

This paper compares quartz-based force sensors for atomic force microscopy, analyzing their noise characteristics and performance factors to optimize sensor design and improve measurement accuracy.

Contribution

It provides a detailed calculation and measurement of noise sources in quartz sensors, offering insights into optimizing sensor stiffness, bandwidth, and amplitude for better AFM performance.

Findings

Deflection detector noise is independent of sensor stiffness.

Thermal, oscillator, and thermal drift noises increase with sensor stiffness.

Optimal signal-to-noise ratio depends on amplitude, bandwidth, and noise contributions.

Abstract

The force sensor is key to the performance of atomic force microscopy (AFM). Nowadays, most AFMs use micro-machined force sensors made from silicon, but piezoelectric quartz sensors are applied at an increasing rate, mainly in vacuum. These self sensing force sensors allow a relatively easy upgrade of a scanning tunneling microscope to a combined scanning tunneling/atomic force microscope. Two fundamentally different types of quartz sensors have achieved atomic resolution: the 'needle sensor' that is based on a length extensional resonator and the 'qPlus sensor' that is based on a tuning fork. Here, we calculate and measure the noise characteristics of these sensors. We find four noise sources: deflection detector noise, thermal noise, oscillator noise and thermal drift noise. We calculate the effect of these noise sources as a factor of sensor stiffness, bandwidth and oscillation amplitude. We find that for self sensing quartz sensors, the deflection detector noise is independent of sensor stiffness, while the remaining three noise sources increase strongly with sensor stiffness. Deflection detector noise increases with bandwidth to the power of 1.5, while thermal noise and oscillator noise are proportional to the square root of the bandwidth. Thermal drift noise, however, is inversely proportional to bandwidth. The first three noise sources are inversely proportional to amplitude while thermal drift noise is independent of the amplitude. Thus, we show that the earlier finding that quoted optimal signal-to-noise ratio for oscillation amplitudes similar to the range of the forces is still correct when considering all four frequency noise contributions. Finally, we suggest how the signal-to-noise ratio of the sensors can be further improved and briefly discuss the challenges of mounting tips.