Machine Learning Empowered Thin Film Acoustic Wave Sensing

Thin film based surface acoustic wave (SAW) technology has been extensively explored for physical, chemical and biological sensors. However, these sensors often show inferior performance for a specific sensing in complex environments, as they are affected by multiple influencing parameters and their coupling interferences. To solve these critical issues, we propose a methodology to extract critical information from the scattering parameter and combine machine learning method to achieve multi-parameter decoupling. We used AlScN film-based SAW device as an example, in which highly c-axis orientated and low stress AlScN film was deposited on silicon substrate. The AlScN/Si SAW device showed a Bode quality factor value of 228 and an electro-mechanical coupling coefficient of ~2.3. Two sensing parameters (i.e., ultraviolet or UV and temperature) were chosen for demonstration and the proposed machine-learning method was used to distinguish their influences. Highly precision UV sensing and temperature sensing were independently achieved without their mutual interferences. This work provides an effective solution for decoupling of multi-parameter influences and achieving anti-interference effects in thin film based SAW sensing

The Role Assignment in Robot Soccer

Non

Multisatellite Task Allocation and Orbit Planning for Asteroid Terminal Defence

Near-Earth asteroids are a great threat to the Earth, especially potential rendezvous and collision asteroids. To protect the Earth from an asteroid collision, it is necessary to investigate the asteroid defence problem. An asteroid terminal defence method based on multisatellite interception was designed in this study. For an asteroid intruding in the sphere of the gravitational influence of the Earth, multiple interceptor satellites are used to apply a kinetic energy impulse to deflect the orbit of the asteroid. First, the effects of planned interception time and planned interception position on the required impulse velocity increment applied to the asteroid are assessed for interception opportunity selection. Second, multiple interceptor satellites are selected to perform the defence task from the on-orbit available interceptor satellite formation. An improved contract net protocol algorithm considering the Lambert orbital manoeuvre is designed to fulfil the task allocation and satellite orbit planning. Finally, simulation experiments demonstrate the rationale and effectiveness of the proposed method, which provides support for asteroid terminal defence technology

Strategy to Minimize Bending Strain Interference for Flexible Acoustic Wave Sensing Platform

There are great concerns for sensing using flexible acoustic wave sensors and labon-a-chip, as mechanical strains will dramatically change the sensing signals (e.g., frequency) when they are bent during measurements. These strain-induced signal changes cannot be easily separated from those of real sensing signals (e.g., humidity, ultraviolet, or gas/biological molecules). Herein, we proposed a new strategy to minimize/eliminate effects of mechanical bending strains by optimizing off-axis angles between the direction of bending deformation and propagation of acoustic waves on curved surfaces of layered piezoelectric film/flexible glass structure. This strategy has theoretically been proved by optimization of bending designs of offaxis angles and acoustically elastic effect. Proof-of-concept for humidity and ultraviolet-light sensing using flexible SAW devices with negligible interferences are achieved within a wide range of bending strains. This work provides the best solution for achieving high performance flexible acoustic wave sensors under deformed/bending conditions

Robust Spontaneous Raman Flow Cytometry for Single‐Cell Metabolic Phenome Profiling via pDEP‐DLD‐RFC

Abstract A full‐spectrum spontaneous single‐cell Raman spectrum (fs‐SCRS) captures the metabolic phenome for a given cellular state of the cell in a label‐free, landscape‐like manner. Herein a positive dielectrophoresis induced deterministic lateral displacement‐based Raman flow cytometry (pDEP‐DLD‐RFC) is established. This robust flow cytometry platform utilizes a periodical positive dielectrophoresis induced deterministic lateral displacement (pDEP‐DLD) force that is exerted to focus and trap fast‐moving single cells in a wide channel, which enables efficient fs‐SCRS acquisition and extended stable running time. It automatically produces deeply sampled, heterogeneity‐resolved, and highly reproducible ramanomes for isogenic cell populations of yeast, microalgae, bacteria, and human cancers, which support biosynthetic process dissection, antimicrobial susceptibility profiling, and cell‐type classification. Moreover, when coupled with intra‐ramanome correlation analysis, it reveals state‐ and cell‐type‐specific metabolic heterogeneity and metabolite‐conversion networks. The throughput of ≈30–2700 events min−1 for profiling both nonresonance and resonance marker bands in a fs‐SCRS, plus the >5 h stable running time, represent the highest performance among reported spontaneous Raman flow cytometry (RFC) systems. Therefore, pDEP‐DLD‐RFC is a valuable new tool for label‐free, noninvasive, and high‐throughput profiling of single‐cell metabolic phenomes