Natural gas has become an essential energy resource in the U.S. due to the increasing demand of energy, the high oil prices, and the need of foreign oil independency. The improvement in the drilling technology has allowed the rapid expansion in gas production, especially for unconventional gas such as shale gas. Shale gas is natural gas trapped within fine-grained sedimentary rocks called shale formations. Hydraulic fracturing is used to extract natural gas from these formations. Although natural gas is cleaner-energy source than coal or oil, there is a lot of controversy due to the environmental impact related to the water consumption and treatment. Hydraulic fracturing generates significant volumes of wastewater that contain dissolved chemicals, high content of salts, and significant levels of natural occurring radioactive material (NORM). Hence, one of the biggest challenges of this industry is to develop techniques for the prevention, remediation, and appropriate disposal of NORM. The overall objective of this work is to develop and implement a novel computational tool for high-throughput screening and selection of new adsorbents for NORM removal. In the first part of this paper series, we study the adsorption theory for NORM removal and applied group contribution methods (GCMs) to predict specific properties of adsorbents based on their thermodynamics. Then, in the second part of this paper we develop a computer-aided molecular design (CAMD) framework that generates potential adsorbent candidates according to the properties developed by the GCMs. (C) 2015 Elsevier Ltd. All rights reserved.