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Flexoelectricity, inherent in all materials, offers a promising alternative to piezoelectricity for nanoscale actuation and sensing. However, its widespread application faces significant challenges: differentiating flexoelectric effects from those of piezoelectricity and other phenomena, verifying its universality across all material structures and thicknesses, and establishing a comprehensive database of flexoelectric coefficients across different materials. This work introduces a groundbreaking methodology that accurately isolates flexoelectricity from piezoelectric, electrostrictive, and electrostatic effects, with a detection threshold extending below 1 fC/m. The robustness of this method is demonstrated through its application to amorphous hafnium oxide, successfully measuring a flexoelectric coefficient of 105 ± 10 pC/m. This measurement signifies the first measurement of flexoelectricity in hafnia, as well as in any amorphous material. In addition, the study compiles a list of published flexoelectric coefficients, revealing an important insight. The relationship between the flexoelectric coefficient and the material’s relative permittivity is better approximated by a quadratic proportionality. This challenges the traditional linear assumption proposed in Kogan’s work and opens new avenues for future research in flexoelectric materials.

Abstract Microelectromechanical system (MEMS) devices, such as accelerometers, are widely used across industries, including the automotive, consumer electronics, and medical industries. MEMS are efficiently produced at very high volumes using large-scale semiconductor manufacturing techniques. However, these techniques are not viable for the cost-efficient manufacturing of specialized MEMS devices at low- and medium-scale volumes. Thus, applications that require custom-designed MEMS devices for markets with low- and medium-scale volumes of below 5000–10,000 components per year are extremely difficult to address efficiently. The 3D printing of MEMS devices could enable the efficient realization and production of MEMS devices at these low- and medium-scale volumes. However, current micro-3D printing technologies have limited capabilities for printing functional MEMS. Herein, we demonstrate a functional 3D-printed MEMS accelerometer using 3D printing by two-photon polymerization in combination with the deposition of a strain gauge transducer by metal evaporation. We characterized the responsivity, resonance frequency, and stability over time of the MEMS accelerometer. Our results demonstrate that the 3D printing of functional MEMS is a viable approach that could enable the efficient realization of a variety of custom-designed MEMS devices, addressing new application areas that are difficult or impossible to address using conventional MEMS manufacturing.

Nonlinear optical frequency conversion is of fundamental importance in photonics and underpins countless of its applications: Sum- and difference-frequency generation in media with quadratic nonlinearity permits reaching otherwise inaccessible wavelength regimes, and the dramatic effect of supercontinuum generation through cubic nonlinearities has resulted in the synthesis of broadband multi-octave spanning spectra, much beyond what can be directly achieved with laser gain media. Chip-integrated waveguides permit to leverage both quadratic and cubic effects at the same time, creating unprecedented opportunities for multi-octave spanning spectra across the entire transparency window of a nonlinear material. Designing such waveguides often relies on numeric modeling of the underlying nonlinear processes, which, however, becomes exceedingly challenging when multiple and cascading nonlinear processes are involved. Here, to address this challenge, we report on a novel numeric simulation tool for mixed and cascaded nonlinearities that uses anti-aliasing strategies to avoid spurious light resulting from a finite simulation bandwidth. A dedicated fifth-order interaction picture Runge–Kutta solver with adaptive step-size permits efficient numeric simulation, as required for design parameter studies. The simulation results are shown to quantitatively agree with experimental data, and the simulation tool is available as an open-source Python package (pychi).