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This study introduces a mechanical spectrum analyzer (MSA) inspired by the tonotopic organization of the basilar membrane (BM), designed to achieve two critical features. First, it replicates the traveling-wave behavior of the BM, characterized by energy dissipation without reflections at the boundaries. Second, it enables the physical encoding of the wave energy into distinct spectral components. Moving beyond the conventional focus on metamaterial design, this research investigates wave propagation behavior and energy dissipation within metastructures, with particular attention to how individual unit cells absorb energy. To achieve these objectives, a metastructural design methodology is employed. Experimental characterization of metastructure samples with varying numbers of unit cells is performed, with reflection and absorption coefficients used to quantify energy absorption and assess bandgap quality. Simulations of a basilar membrane-inspired structure incorporating multiple sets of dynamic vibration resonators (DVRs) demonstrate frequency selectivity akin to the natural BM. The design features four types of DVRs, resulting in stepped bandgaps and enabling the MSA to function as a frequency filter. The findings reveal that the proposed MSA effectively achieves frequency-selective wave propagation and broad bandgap performance. The quantitative analysis of energy dissipation, complemented by qualitative demonstrations of wave behavior, highlights the potential of this metastructural approach to enhance frequency selectivity and improve sound processing. These results lay the groundwork for future exploration of 2D metastructures and applications such as energy harvesting and advanced wave filtering. 

Abstract Using steady-state traveling waves as a propulsion mechanism emerges as a highly effective strategy for displacing particles, eliminating the need for an external fluid transfer pump. This experimental inquiry delves into the intricate application of traveling waves within a beam submerged in quiescent water, deploying two distinctive force input methods to govern particle movement acoustically. The complexity of this research lies in balancing the finesse of particle motion while concurrently imposing constraints on the number of control cycles implemented. To address this challenge comprehensively, we introduce a diverse range of control cycles tailored to manipulate particles of varying sizes. Navigating the nuanced dynamics of this system requires a sophisticated approach, prompting the adoption of the Reinforcement Learning Approach. This methodological choice empowers us to discern the characteristics of traveling waves necessary for facilitating the movement of particles with divergent sizes. The utilization of Reinforcement Learning not only refines our understanding of the intricate interplay between waves and particles but also enhances our ability to optimize control strategies in this particular context. The significance of this research extends beyond the confines of the laboratory, resonating in various applications, with particular prominence in advancing transportation mechanisms for cells and analogous entities. By elucidating the underlying principles governing the interaction between traveling waves and particles of different sizes, the findings offer invaluable insights that can be harnessed to optimize particle manipulation techniques. This holds potential implications in biotechnology, where the precision control of particle movement is pivotal for applications ranging from targeted drug delivery to the manipulation of biological cells. Furthermore, our exploration not only contributes to the theoretical understanding of particle manipulation through traveling waves but also yields tangible practical implications. The versatility of our approach, as exemplified through the successful manipulation of particles with varying sizes, underscores its potential applicability across a spectrum of scenarios, emphasizing its broader relevance within the burgeoning field of acoustic fluids. In conclusion, the utilization of steady-state traveling waves as a particle propulsion mechanism, as showcased in this experimental investigation, not only holds promise for the advancement of particle manipulation but also underscores its potential impact in diverse applications. Through the thorough exploration of control cycles and the strategic application of the Reinforcement Learning Approach, this research not only contributes to the theoretical knowledge underpinning acoustofluidics but also provides practical methodologies for precision particle manipulation. These advancements are poised to play a pivotal role in shaping the future landscape of biotechnology and related fields, where fine-tuned control over particle dynamics is a cornerstone for innovation and progress. 

Abstract The Basilar Membrane (BM) is the structural component of the mammalian cochlea that transmits auditory information as traveling structural waves, and inner hair cells transduce acoustic waves into electrical impulses in the inner ear. These waves go up towards the cochlea’s apex from its base. The primary structure at the apex of the cochlea that keeps waves from returning to the base is the helicotrema. People can hear continuous sound waves without acoustic reflection or overlap because of this property of the BM. Our research is motivated by this biological phenomenon and aims to comprehend and passively reproduce it in engineering structures. By studying the dynamics of a uniform beam linked to a spring-damper system as a passive absorber, we can use this characteristic of the inner ear to explain some of the observed phenomenological behaviors of the basilar membrane. The spring-damper system’s position separates the beam into two dynamic regions: one with standing waves and the other with non-reflecting traveling waves. This study presents the computational realization of traveling waves co-existing with standing waves in the two different zones of the structure. Moreover, this study aims to establish a correlation between two approaches to analyze the characteristics of the wave profiles: (i) the absorption coefficient approach and (ii) the cost function based on the wave envelope. The Basilar Membrane (BM) serves as the crucial structural conduit for transmitting auditory information through traveling structural waves, with inner hair cells in the inner ear transducing these waves into electrical impulses. These waves ascend from the cochlea’s base towards its apex, and the helicotrema, positioned at the cochlear apex, plays a pivotal role in preventing wave reflection and overlap, thereby facilitating the perception of continuous sound waves. The intrinsic characteristics of the Basilar Membrane (BM) inspire our research as we seek to comprehend and passively replicate this phenomenon in simplified forms. The investigation involves the exploration of the dynamics exhibited by a uniform beam connected to a spring-damper system acting as a passive absorber. This chosen system allows us to take advantage of the unique property of the inner ear, shedding light on some of the observed phenomenological behaviors of the basilar membrane. The positioning of the spring-damper system engenders two distinct dynamic regions within the beam: one characterized by standing waves and the other by non-reflecting traveling waves. The comprehensive analysis incorporates analytical and computational aspects, providing a holistic understanding of the coexistence of traveling and standing waves within these two dynamic zones. 

Abstract In this study, the frequency selectivity phenomenon in the mammalian cochlea is replicated in a simulated environment. Frequency selectivity is found to be of crucial importance in the accurate perception of environmental noise. Previous studies have found that mammalian cochlea consists of basilar membrane which varies in width and stiffness along its length. This results in a gradient in mechanical properties and in turn results in a place-coding mechanism, where different frequencies of sound cause maximum displacement of the basilar membrane at specific locations along its length. The basilar membrane consists of multiple hair cells located along its length. The displacement of the basilar membrane due to sound waves causes hair cells to bend. This bending of hair cells activates ion channels, leading to the generation of electrical signals. Leveraging the principles of cochlear processing, a Kalimba-key-based broadband vibroacoustic device is developed in this study having potential implications for sensory technology and human perception enhancement. Dynamic vibration resonators (DVRs) are employed in this research to emulate the frequency-selective behavior of the mammalian cochlea where the DVRs act as hair cells. A beam structure, acting as a platform for 136 strategically placed DVRs, each corresponding to a Kalimba instrument key is considered. Upon stimulation, these Kalimba keys replicate the vibrations of the cochlear basilar membrane, enabling the recreation of frequency selectivity across a broad spectrum. To simulate the system, a Timoshenko beam is considered to consist of spatially attached Kalimba keys modeled as a Single-Degree Of Freedom (SDOF) systems. A Finite Element (FE) model of this system is developed to calculate the response of the system. Frequency selectivity for different combinations of Kalimba keys is explored in this study. This study shows promising results having potential implications extending beyond healthcare, encompassing fields such as robotics where the integration of biological cochlear principles could enhance robots’ sensory perception and interaction capabilities in diverse environments.