Short answer

Integrate computational materials databases into the early stages of design to explore a wider range of functional materials, accelerating innovation and performance optimization.

Field: Final Production
Source: Scientific Data (2015)
Method: Computational simulation and database development
Sample: Approximately 1000 compounds
Evidence: Strong effect

Leveraging first-principles calculations and a comprehensive database significantly expands the known pool of piezoelectric materials, enabling more informed selection for advanced applications. This final production research insight is drawn from a 2015 study published in Scientific Data. Using Computational simulation and database development with Approximately 1000 compounds, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Integrate computational materials databases into the early stages of design to explore a wider range of functional materials, accelerating innovation and performance optimization.

Study

Final ProductionHigh ImpactStrong effect

Computational screening of piezoelectric materials accelerates discovery by over 1000%

Leveraging first-principles calculations and a comprehensive database significantly expands the known pool of piezoelectric materials, enabling more informed selection for advanced applications.

Scientific Data · 2015

Key Findings

01Computational methods can accurately predict piezoelectric properties for a vast number of materials.
02The developed database increases the available data for piezoelectricity by over an order of magnitude.
03The database is designed for accessibility and application in materials development efforts.

Application

Design takeaway

Integrate computational materials databases into the early stages of design to explore a wider range of functional materials, accelerating innovation and performance optimization.

How to apply

When designing a product requiring piezoelectric properties, consult comprehensive computational materials databases to identify novel or optimized material candidates before focusing on experimental characterization.

Project actions

01When choosing materials for a design project, consider using online databases that offer computational predictions of material properties.
02Explore how computational tools can help you discover new materials that might not be commonly known or easily accessible.

Method & Evidence

AimTo computationally screen a large number of inorganic compounds for piezoelectric properties and create a publicly accessible database to facilitate materials discovery and design.

MethodComputational simulation and database development

ProcedureFirst-principles calculations using density functional perturbation theory were performed to compute piezoelectric tensors for nearly a thousand inorganic compounds. The results were validated against experimental data and compiled into a structured database for public access and use in materials development.

SampleApproximately 1000 compounds

ContextMaterials science and computational chemistry, with applications in electronics, sensors, and actuators.

Variables

IVComputational screening methodology and database structure

DVNumber of characterized piezoelectric materials, accessibility of data

CVFirst-principles calculation parameters, crystallographic symmetry requirements

Strengths & Limitations

Strengths

+Massive increase in the number of characterized piezoelectric materials.
+Creation of a publicly accessible and usable database.
+Validation of computational methods against experimental data.

Limitations

The accuracy of computational predictions can vary, and real-world manufacturing processes might introduce complexities not accounted for in simulations.

Reliability & validity

The study validates its computational findings against experimental data, suggesting good reliability. The validity is high within the domain of first-principles calculations for predicting piezoelectric properties.

Think critically

To what extent can we rely on computationally predicted material properties for critical design decisions without extensive experimental validation?

Design Principles

"Leverage computational screening and large-scale data aggregation to broaden the material selection palette for functional components."

This research provides a vast, computationally-derived dataset for piezoelectric materials, far exceeding experimentally characterized ones. This allows designers and engineers to explore a much wider range of material options for applications requiring electromechanical coupling, potentially leading to novel product functionalities and improved performance.

What This Means for Your Design

Scientists used computers to predict if lots of different materials can turn movement into electricity (or vice versa). They made a big list (database) of these materials, making it much easier for designers to find the right one for their projects.

How to use in your project

1.Reference this study when discussing the selection of functional materials, particularly if you are exploring less common or computationally predicted options.
2.Use the concept of computational screening to justify your material choices or to suggest alternative materials for your design.

Add to My Project

Quick Cite

Paragraph starter

This research highlights the significant impact of computational materials science on design practice. By employing first-principles calculations, researchers have generated a comprehensive database of piezoelectric materials, expanding the available options for designers by over an order of magnitude. This approach enables a more informed and accelerated discovery process, allowing for the identification of novel materials with tailored properties for specific applications, thereby driving innovation in product development.

Source

Scientific Data

A database to enable discovery and design of piezoelectric materials

journal · 2015

View source

Questions About This Research

What does the research say about computational screening of piezoelectric materials accelerates discovery by over 1000%?: Integrate computational materials databases into the early stages of design to explore a wider range of functional materials, accelerating innovation and performance optimization. Evidence: Scientific Data (2015).
Why does "Computational screening of piezoelectric materials accelerates discovery by over 1000%" matter for design?: This research provides a vast, computationally-derived dataset for piezoelectric materials, far exceeding experimentally characterized ones. This allows designers and engineers to explore a much wider range of material options for applications requiring electromechanical coupling, potentially leading to novel product functionalities and improved performance.
How can designers apply this research?: Integrate computational materials databases into the early stages of design to explore a wider range of functional materials, accelerating innovation and performance optimization.
What were the main findings?: Computational methods can accurately predict piezoelectric properties for a vast number of materials.. The developed database increases the available data for piezoelectricity by over an order of magnitude.. The database is designed for accessibility and application in materials development efforts.
What research method was used?: Computational simulation and database development with Approximately 1000 compounds.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2015 journal from Scientific Data.
What should I do differently in my next project?: When designing a product requiring piezoelectric properties, consult comprehensive computational materials databases to identify novel or optimized material candidates before focusing on experimental characterization.
What are the limitations?: Computational predictions may not perfectly capture all real-world material behaviors; experimental validation is still crucial for critical applications.