readme updates

Author: shirubana

README.md

@@ -27,13 +27,24 @@
 </table>
 
 
-# PV ICE: PV in the Circular Economy, a Dynamic Energy and Materials TOOL
+# PV ICE: A Dynamic Framework for Photovoltaic Material, Energy, and Lifetime Analysis
 
-This open-source tool explores the effects of Circular Economy (CE) pathways for photovoltaic (PV) materials. It can be used to quantify and assign a value framework to CE efforts including re-design, reduction, replacement, reuse, recycling, and lifetime and reliability improvements across the PV value chain. PV ICE enables tradeoff analysis through scenario comparisons, and is highly customizable through user inputs such as deployment schedules, module properties and component materials, and CE pathways.
+PV ICE is an open-source modeling framework for quantifying photovoltaic (PV) material flows, energy flows, and lifetime behavior across deployment, operation, reuse, and end-of-life scenarios.
+
+The framework supports scenario-based analysis of evolving PV technologies by combining deployment schedules, module and material properties, and reliability and degradation parameters. PV ICE enables transparent accounting of capacity evolution, material demand, waste generation, and energy balance over time, supporting comparative analysis across technology designs and lifecycle pathways.
+
+PV ICE was originally developed to explore circular material pathways in PV systems and has since evolved into a general modeling framework for lifecycle and reliability-aware analysis.
 
 The provided PV ICE module and material baselines leverage published data from many sources on PV manufacturing and predicted technological changes. Input data are being compiled [here](https://docs.google.com/spreadsheets/d/1WV54lNAdA2uP6a0g5wMOOE9bu8nbwvnQDgLj3GuGojE/edit?usp=sharing) and the baselines are available here for use in other projects as well as for the PV ICE tool.
 
 
+## Scope and Intended Use
+
+PV ICE provides core calculations for photovoltaic material flows, energy flows, and lifetime behavior.  
+The framework is designed to support comparative scenario analysis and does not prescribe policy, investment, or operational decisions.
+
+Downstream applications—such as techno-economic assessments, repowering decision tools, or site-specific case studies—may use PV ICE outputs but are maintained in separate repositories to preserve modularity and reproducibility.
+
 How it Works
 =============
 
@@ -43,25 +54,25 @@ This section provides a brief description of how the PV ICE tool works. FULL DOC
 Mass
 -----
 
-PV ICE is a dynamic mass flow based tool. It takes in any deployment forecast of any evolving module design along with it's component materials and uses sophisticated lifetime and reliability parameters to calculate effective capacity, virgin material demand, and life cycle wastes. The calculator captures all the mass flows shown in the simplified diagram below for all years studied in a simulation (ex: 2020-2050). 
+PV ICE is a dynamic mass flow based tool. It takes in any deployment forecast of any evolving module design along with it's component materials and uses user-defined lifetime, degradation, and reliability parameters to calculate effective capacity, virgin material demand, and life cycle wastes. The calculator captures all the mass flows shown in the simplified diagram below for all years studied in a simulation (ex: 2020-2050). 
 
 <img src="docs/images_wiki/PV_ICE_diagram-simpleAltUpdate.png" width="550">
 
-Annually deployed cohorts of modules are tracked through the simulation, subjected to lifetime, degradation, and reliability parameters, and guided along user defined CE pathways (ex: resell, recycling). The PV ICE framework is designed for scenario comparisons (ex: different deployment schedules, module designs, or circular pathways) and is capable of both geospatial and temporal analysis (i.e. when and where materials will be demanded or are available).
+Annually deployed cohorts of modules are tracked through the simulation, subjected to lifetime, degradation, and reliability parameters, and guided along user-defined lifecycle pathways (e.g., continued operation, reuse, recycling). The PV ICE framework is designed for scenario comparisons (ex: different deployment schedules, module designs, or circular pathways) and is capable of both geospatial and temporal analysis (i.e. when and where materials will be demanded or are available).
 
-Module and material properties are known to be variable with time, and PV ICE can capture this dynamic evolution of PV technology. Dynamic baseline inputs for crystalline silicon PV modules and component materials are provided in the PV_ICE \ baselines folder. These baselines are dervied from [literature and report data](https://docs.google.com/spreadsheets/d/1Ec5JRBSN2NFXjEABgUp1ch-EG6uQao8j5Rk1MLuZZYI/edit?usp=sharing). Module baselines capture the annual average crystalline silicon module (i.e. a market share weighted average of the silicon PV technologies deployed). Each material similarly is a market share weighted average of silicon PV technologies, compiled from multiple sources, most notably consistent with ITRPV data. Please see the Jupyter Journals (tutorials \ baseline development documentation) for the derivations and sources (baselines \ SupportingMaterials) of the provided c-Si baselines. Alternate module and material files can be created by the user, and an expanded set of PV technology baselines is planned for the future, including CdTe and perovskites.
+Module and material properties are known to be variable with time, and PV ICE can capture this dynamic evolution of PV technology. Dynamic baseline inputs for crystalline silicon and cadmium-telluride PV modules and their component materials are provided in the PV_ICE \ baselines folder. These baselines are derived from [literature and report data](https://docs.google.com/spreadsheets/d/1Ec5JRBSN2NFXjEABgUp1ch-EG6uQao8j5Rk1MLuZZYI/edit?usp=sharing). Module baselines capture the annual average module (i.e. a market share weighted average of PV technologies deployed). Each material similarly is a market share weighted average compiled from multiple sources, most notably consistent with ITRPV data. Please see the Jupyter Journals (tutorials \ baseline development documentation) for the derivations and sources (baselines \ SupportingMaterials) of the provided c-Si and CdTe baselines. Simplified baselines for perovskites are also included, as well as of business as usual and ideal modules evolutions as described in [Mirletz et al., 2024]: https://doi.org/10.1051/epjpv/2024015. Alternate module and material files can be created by the user.
 
 
 Energy
 -------
 
-The energy balance of renewable energy technologies is as important and the mass balance when evaluating sustainability. Additionally, few studies of Circular Economy (CE) pathways consider the energy return on investment of a particular pathway. PV ICE energy flows fill this analysis gap, and provide useful insights into the potential tradeoffs between mass and energy of CE pathways.
+Energy accounting is a critical complement to material flow analysis when evaluating the lifecycle performance of energy technologies. Additionally, few studies of Circular Economy (CE) pathways consider the energy return on investment of a particular pathway. PV ICE energy flows fill this analysis gap, and provide useful insights into the potential tradeoffs between mass and energy of CE pathways.
 
 The energy flows of PV ICE are based on the mass flows. These energy flows, like the mass flows, are dynamic with time and are seperated into module and material energies. For each supply chain process step captured in the mass flows, an energy per module area or energy per material mass is captured as an input (ex: module manufacturing energy, energy to manufacture rolled glass from silica sand, energy to crush a module for recycling ). The energy demanded for each step is the sum of all electrical energy demands and all fuel/heating energy demands. 
 
-We provide an energy baseline for crystalline silicon modules and component materials. Data for these baselines is being compiled from [literature and report data](https://docs.google.com/spreadsheets/d/1Ec5JRBSN2NFXjEABgUp1ch-EG6uQao8j5Rk1MLuZZYI/edit?usp=sharing). For the complete derivation of the energy demands for crystalline silicon modules and materials, please see the Jupyter Journals (tutorials \ baseline development documentation) and (baselines \ SupportingMaterials). Alternate module and material files can be created by the user, and an expanded set of PV technology baselines is planned for the future, including CdTe and perovskites.
+We provide an energy baseline for crystalline silicon modules and cadmium telluride modules including their component materials. Data for these baselines is being compiled from [literature and report data](https://docs.google.com/spreadsheets/d/1Ec5JRBSN2NFXjEABgUp1ch-EG6uQao8j5Rk1MLuZZYI/edit?usp=sharing). For the complete derivation of the energy demands, please see the Jupyter Journals (tutorials \ baseline development documentation) and (baselines \ SupportingMaterials). Simplified baselines for perovskites are also included, as well as of business as usual and ideal modules evolutions as described in [Mirletz et al., 2024]: https://doi.org/10.1051/epjpv/2024015. Alternate module and material files can be created by the user.
 
-After running a mass flow simulation, an energy flow calculation can be run which will multiply the energy demands by the mass flows and calculate annual generation from the deployed modules. Results of this calculation provide annual, cumulative, and lifetime energy demands and energy generated. These values can be used to calculate energy balance metrics such as energy return on investment (EROI), net energy, and energy payback time (EPBT). These features are actively under development, so check back for updates soon!
+After running a mass flow simulation, an energy flow calculation can be run which will multiply the energy demands by the mass flows and calculate annual generation from the deployed modules. Results of this calculation provide annual, cumulative, and lifetime energy demands and energy generated. These values can be used to calculate energy balance metrics such as energy return on investment (EROI), net energy, and energy payback time (EPBT). 
 
 
 Installation for PV ICE
@@ -112,6 +123,15 @@ PV ICE has been used in a variety of published analyses, including:
     Technology Evolution and Reliability Impacts,” 
     ISCIENCE, Jan. 2022, doi: https://doi.org/10.1016/j.isci.2021.103488.
 
+**EPJ**
+
+    Mirletz, H., Ovaitt, S., Sridhar, S., & Barnes, T. M. (2024). 
+    "Prioritizing circular economy strategies for sustainable PV deployment at the terawatt scale."
+    EPJ Photovoltaics*, 15, 18.  
+    https://doi.org/10.1051/epjpv/2024015
+
+Other
+
 **PVSC**
 
     H. M. Mirletz, S. Ovaitt, A. Gaulding, S. Sridhar, and T. Barnes,