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Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by identifying...

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Multifunctional Piezoelectric Foams Enabling Noise Absorption and Deep-Learning-Driven Motion Recognition.

Shuyi Shen1, Yanjun Lu1,2, Zishi Jiang1

  • 1State Key Laboratory of Powder Metallurgy, Central South University, Changsha, China.

Small (Weinheim an Der Bergstrasse, Germany)
|June 16, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed novel bacterial cellulose-Ba0.85Ca0.15Zr0.1Ti0.9O3 (BCZT)-melamine composite foams (BZMFs). These lightweight, multifunctional materials offer excellent noise reduction and piezoelectric sensing for motion monitoring applications.

Keywords:
deep learningfreeze‐castinghierarchical structurepiezoelectric functionalitysound absorption

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Acoustics

Background:

  • Industrial and traffic noise pollution is a growing environmental concern.
  • Conventional porous materials often have high density and limited functionality.
  • Lightweight, multifunctional acoustic materials are needed for environmental and wearable applications.

Purpose of the Study:

  • To fabricate novel bacterial cellulose-Ba0.85Ca0.15Zr0.1Ti0.9O3 (BCZT)-melamine composite foams (BZMFs).
  • To investigate the acoustic properties, piezoelectric sensing capabilities, and motion recognition potential of BZMFs.

Main Methods:

  • Freeze-casting was employed to create BZMFs with hierarchical pore channels.
  • Acoustic performance was evaluated by measuring the noise reduction coefficient (NRC).
  • Piezoelectric sensing functionality was assessed through dynamic compression tests and coupled with a convolutional neural network for motion recognition.

Main Results:

  • BZMFs exhibited a noise reduction coefficient (NRC) of 0.24 at a low areal density of 11.36 mg·cm-2.
  • The material demonstrated piezoelectric sensing with a sensitivity of 0.256 V·kPa-1, showing stable output after 1890 cycles.
  • Human motion recognition achieved over 93.75% classification accuracy when BZMFs were coupled with a convolutional neural network.

Conclusions:

  • The fabricated BZMFs possess a hierarchical structure, enabling effective noise reduction and piezoelectric sensing.
  • These multifunctional materials show significant potential for applications in noise pollution control and intelligent motion monitoring systems.