Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Design Example: Managing Concrete Workability

Design Example: Managing Concrete Workability

This example deals with managing the workability of concrete for a raft foundation project under hot weather conditions. Workability is crucial for ensuring the concrete is easy to place, compact, and finish. In this scenario, a slump test — a common method to measure the workability of fresh concrete — initially indicated low workability. This was attributed to the rapid water loss from the concrete mix, exacerbated by the high temperatures causing the course aggregates to heat up.

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Composite Bodies

Composite Bodies

A composite body is a body made up of multiple parts, connected to form a larger, unified object. Each part has its own weight and center of gravity, which must be considered to determine the center of gravity of the composite body. In cases where the density or specific weight is constant, the center of gravity coincides with the centroid.
Composite bodies have widespread applications in mechanical engineering, from automobiles to aircraft to rockets. For example, an automobile wheel comprises...

Design of Prismatic Beams for Bending

Design of Prismatic Beams for Bending

The design of prismatic beams, structural elements with a uniform cross-section, focuses on ensuring safety and structural integrity under load. The design process begins by determining the allowable stress, either from material properties tables, or by dividing the material's ultimate strength by a safety factor. This safety factor is essential for accommodating uncertainties, and varies depending on the material—timber, steel, or concrete—with each having unique strength and...

Response Surface Methodology

Response Surface Methodology

Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:

Ampere-Maxwell's Law: Problem-Solving

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Nanoscale frictional imaging of ferroelectric domains.

Science advances·2026

Same author

Surface-based stress tomography of architected metamaterials <i>via</i> physics-constrained generative learning.

Materials horizons·2026

Same author

Inverse design of thermally active composite <i>via</i> policy-transferred reinforcement learning.

Materials horizons·2026

Same author

Comparative assessment of composition- and structure-based surrogate models across 2D materials databases.

Physical chemistry chemical physics : PCCP·2026

Same author

Physics-informed neural networks for programmable origami metamaterials with controlled deployment.

Materials horizons·2025

Same author

Meter-scale heterostructure printing for high-toughness fiber electrodes in intelligent digital apparel.

Nature communications·2025

Search research articles

Related Experiment Video

Updated: Jul 23, 2025

A Protocol for Bioinspired Design: A Ground Sampler Based on Sea Urchin Jaws

A Protocol for Bioinspired Design: A Ground Sampler Based on Sea Urchin Jaws

Published on: April 24, 2016

Multi-objective Bayesian optimization for the design of nacre-inspired composites: optimizing and understanding

Kundo Park¹, Chihyeon Song², Jinkyoo Park²

¹Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea. ryush@kaist.ac.kr.

Materials Horizons

|July 12, 2023

Summary

This study introduces a data-driven framework for designing bioinspired composites, optimizing strength, toughness, and specific volume. The method generates a Pareto surface of optimal designs, enabling tailored material selection for specific applications.

More Related Videos

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Related Experiment Videos

Last Updated: Jul 23, 2025

A Protocol for Bioinspired Design: A Ground Sampler Based on Sea Urchin Jaws

A Protocol for Bioinspired Design: A Ground Sampler Based on Sea Urchin Jaws

Published on: April 24, 2016

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Materials Science
Composite Materials
Bioinspired Engineering

Background:

Biological materials exhibit hierarchical structures offering superior, balanced properties.
Designing engineering materials inspired by nature (bioinspired composites) is challenging due to 'black-box' optimization problems and trade-offs between properties.
Existing methods struggle to find unique optimal designs for multi-objective composite optimization.

Purpose of the Study:

To develop a data-driven material design framework for generating bioinspired composites with an optimal balance of material properties.
To apply this framework to a nacre-inspired composite, optimizing for strength, toughness, and specific volume.
To overcome the limitations of traditional optimization methods for complex, multi-objective material design.

Main Methods:

Utilized Gaussian process regression to model complex input-output relationships.
Trained the model using data generated from crack phase-field simulations.
Employed multi-objective Bayesian optimization to identify Pareto-optimal composite designs.
Generated a 3D Pareto surface representing a spectrum of optimal design solutions.

Main Results:

Successfully generated a 3D Pareto surface of optimal composite designs for a nacre-inspired material.
Demonstrated that the data-driven framework can achieve an optimal balance of strength, toughness, and specific volume.
Validated Pareto-optimal designs through physical fabrication using a PolyJet 3D printer and subsequent tensile testing.

Conclusions:

The proposed data-driven framework offers a breakthrough in optimizing bioinspired composites with multiple, trade-off properties.
Users can select designs from the generated Pareto surface based on their specific requirements.
Experimental validation confirmed the effectiveness of the data-driven approach in achieving well-optimized material designs.