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People Data and Metrics
https://www.avient.com/company/sustainability/sustainability-report/reporting/sasb
Planet Data and Metrics
Planet Data and Metrics
Planet Data and Metrics
https://www.avient.com/knowledge-base/article/developing-your-esg-framework
A guide for describing, evaluating, and reporting environmental, social, and governance (ESG) data
Social-related data reported to stakeholders rose 37% in 2021 compared to 2020 (McKinsey & Company).
Interested in learning more about your ESG data and how to achieve your sustainability goals?
https://www.avient.com/knowledge-base/article/developing-your-esg-framework?sust[]=1133
A guide for describing, evaluating, and reporting environmental, social, and governance (ESG) data
Social-related data reported to stakeholders rose 37% in 2021 compared to 2020 (McKinsey & Company).
Interested in learning more about your ESG data and how to achieve your sustainability goals?
https://www.avient.com/company/sustainability/sustainability-report/reporting/tcfd
People Data and Metrics
Planet Data and Metrics
People Data and Metrics
https://www.avient.com/knowledge-base/article/optimizing-automotive-structural-component-designs-advanced-modeling?rtype[]=1164
Predictive simulation technology uses conventional (isotropic) and advanced (anisotropic) modeling data from material characterizations, mold filling analysis, and finite element analysis (FEA) to more accurately forecast performance and potential failure points.
By factoring in static and dynamic data, the CAE simulations can identify where an injection molded plastic part may crack or break when exposed to real-world conditions such as physical loading force, sudden impact (crash simulation), or environmental factors like temperature and humidity.
For more technical details on the structural performance of reinforced polymers using CAE, automotive design engineers may access material data and models for Avient’s fiber-reinforced solutions using Hexagon’s Digimat-MX Tool.
https://www.avient.com/knowledge-base/article/optimizing-automotive-structural-component-designs-advanced-modeling
Predictive simulation technology uses conventional (isotropic) and advanced (anisotropic) modeling data from material characterizations, mold filling analysis, and finite element analysis (FEA) to more accurately forecast performance and potential failure points.
By factoring in static and dynamic data, the CAE simulations can identify where an injection molded plastic part may crack or break when exposed to real-world conditions such as physical loading force, sudden impact (crash simulation), or environmental factors like temperature and humidity.
For more technical details on the structural performance of reinforced polymers using CAE, automotive design engineers may access material data and models for Avient’s fiber-reinforced solutions using Hexagon’s Digimat-MX Tool.
https://www.avient.com/news/archives?page=57
See LEDs in a Brand New Light: PolyOne UltraTuf™ LED Light-Diffusing Sheet Cuts Hot Spots, Improves Design Freedom
CLEVELAND – PolyOne today announced the launch of UltraTuf™ LED, a premium light diffusing sheet that combines excellent light transmission and di
https://www.avient.com/knowledge-base/case-study/navigating-challenges-semiconductor-packaging-specialty-polymer-solutions
Increased Demand for Specialty Polymer Solutions and Materials for Semiconductor Packaging
The demand for data center infrastructure has significantly increased with the accelerated adoption of AI-based solutions, cloud computing, and big data analytics.
These technologies rely on semiconductors to process data and provide cloud computing power.
Citations: ¹Fortune Business Insights "Data Center Market Regional Forecast, 2024-2032" https://www.fortunebusinessinsights.com/data-center-market-109851
https://www.avient.com/news/polyone-announces-strong-fourth-quarter-and-full-year-2013-results
In millions, except per share data)
In millions, except per share data)
In millions, except per share data)