Creator
- Aihua Huang 1
- Inez Hua, 0000-0003-4977-5758 1
- John W. Sutherland, 0000-0002-2118-0907 1
- Kali D Frost, 0000-0003-2493-5065 1
- Sidi Deng, 0009-0003-9234-1952 1
- Xiaoyu Zhou 1
- Yuehwern Yih, 0000-0003-2087-7718 1
Type
- Dataset 2
Date
subject: Environmental and Ecological Engineering
Total is 2 Results
Evaluating Economic Opportunities for Product Recycling via the Sherwood Principle and Machine Learning - Supporting Information
10.4231/E80W-7941
Aihua Huang
,
John W. Sutherland
,
Sidi Deng
,
Xiaoyu Zhou
,
Yuehwern Yih
09/03/2020
This repository contains the supporting information for the manuscript regarding Sherwood principle and Machine learning. All critical underlying data files, along with a flow chart that describes the methodologies applied in the paper are enclosed.
Circular Economy Empirical Models Environmental and Ecological Engineering Machine Learning Sherwood Principle
Global Semiconductor Manufacturing Water Withdrawals
10.4231/NYGF-BH18
03/01/2019
This study estimates and displays Tier 1 (direct manufacturing) and Tier 2 (electricity-related) water withdrawals by the semiconductor manufacturing industry. Scarcity-weighted withdrawals are also summarized by facility and watershed.
Environmental and Ecological Engineering Industrial Water Use Semiconductor Water Water Footprint Water Scarcity Water Withdrawals Water-Energy Nexus
Display #
Results 1 - 2 of 2