We review fiber-based multimode interference (MMI) devices with a particular focus on optical fiber-based sensing applications. The present review complements a recently published, extensive review where the sensing of conventional physical variables such as refractive index, temperature, displacement, and strain was covered. This review focuses on MMI fiber sensors for nonconventional physical variables, including mechanical, electromagnetic, chemical, and optical, covering around fifteen years of work in the field. Finally, by the end of this paper, we also review some new trends of MMI-based schemes based on polymer fibers, for wavelength-locking applications, for retrieving the thermo-optic coefficient of liquid samples, and for measuring the dynamics of complex fluids.

A highly sensitive salinity sensor based on a two-core optical fiber is demonstrated for both high- and low-concentration regimes. Salinity of several aqueous solutions is measured in the ranges from 0 to 5 mol/L and from 0 to 1 mol/L with sensitivities of 14.0086 and 12.0484 nm/(mol/L), respectively. The achieved sensitivity is ~19 times higher than that recently reported for polymide-coated photonic crystal fibers.

A curvature fiber optic sensor using a two-core fiber (TCF) is proposed and demonstrated. The TCF is designed to operate as a directional coupler with one core located exactly at the center of the fiber and the other off-axis, but close to the center of the fiber. This design allows straightforward splicing of the TCF to single mode fibers (SMF), and alignment of the off-axis core is not strictly required for optimum operation. The sensor is fabricated by simply splicing a 5 cm long section of TCF between two SMF sections, which provides a sinusoidal spectral response. When the fiber is bent, the coupling parameters are modified due to stress-optic and effective length effects, effectively blue-shifting the sinusoidal spectral response of the sensor and allowing for the measurement of curvature. The sensor exhibits linear response and a sensitivity of −137.87 nm/m⁻¹ for curvature ranging from 0 to 0.27 m⁻¹, making it suitable to measure small curvatures with high sensitivity.

In this paper we demonstrate highly sensitive refractive index (RI) sensing based on multicore coupled structures. Specifically, we use a seven-core fiber (SCF) as the sensing element. The interaction of the SCF and its surroundings is induced by controllably etching material from the cladding in order to expose its external cores. Thus, the sensor sensitivity can be tuned by simply controlling the etching depth. In our case, the cladding of a 10mm-long piece of SCF, spliced between two single-mode fibers (SMFs), was slowly removed until the remaining cladding around the external cores is only 2.5 μm. Sensitivity on the order of 1x104 nm/RIU is experimentally demonstrated. These sensing architectures are compact, all-fiber, simple to fabricate, and highly sensitive. Based on our results RI changes of 10-4-10-5 can be resolved with standard laboratory-graded equipment, which opens the possibility of using this type of sensing architectures in biological applications.

A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors.