readme restructure

Author: TimoDiepers

README.md

@@ -10,27 +10,31 @@
 [![Conda Version](https://img.shields.io/conda/v/diepers/timex_lca?label=conda)](https://anaconda.org/diepers/timex_lca)
 ![Conda - License](https://img.shields.io/conda/l/diepers/timex_lca)
 
-> ℹ️ *This package is still under development and some functionalities may change in the future.*
+> ℹ️ _This package is still under development and some functionalities may change in the future._
 
-This is a python package for __time-explicit Life Cycle Assessment (LCA)__, building on top of the [Brightway](https://docs.brightway.dev/en/latest) LCA framework. 
+This is a python package for time-explicit Life Cycle Assessment that helps you assess the environmental impacts of products and processes over time. `timex_lca` builds on top of the [Brightway LCA framework](https://docs.brightway.dev/en/latest).
 
-Time-explicit LCA aims to treat time more coherently in LCA, by __streamlining dynamic LCI and LCIA with prospective LCI databases__. As such, `timex_lca` enables the consideration of both the __timing of processes and emissions__ (e.g., end-of-life treatment occurs 20 years after construction), as well as the __changing state__ of the production system (e.g., increasing shares of renewable electricity in the future). 
+## Features
+This package enables you to account for: 
+- **Timing of processes** throughout the supply chain (e.g., end-of-life treatment occurs 20 years after construction)
+- **Variable** and/or **evolving** supply chains & technologies (e.g., increasing shares of renewable electricity in the future)
+- **Timing of emissions** (by applying dynamic characterization functions)
 
-Users can define the timing of process and emission exchanges as *temporal distributions*. `timex_lca` automatically propoagates the temporal information through the supply chain and sources the LCI data from the corresponding time explicit database. As the timing of each emission is recorded, `timex_lca` supports __dynamic LCIA methods__, which are provided for the climate change metrics radiative forcing and global warming potential. 
+You can define temporal distributions for process and emission exchanges, which are then *automatically* propagated through the supply chain and mapped to corresponding time-explicit databases. The resulting time-explicit LCI reflects the current technology status within the production system at the actual time of each process. Also, `timex_lca` keeps track of the timing of emissions which means that you can apply dynamic characterization functions.
 
-Time explicit LCA can provide more representative LCA results for use cases, such as:
-- products with variable or evolving production systems
-- long-lived products
-- products with biogenic carbon
+## Use cases:
+`timex_lca` is ideal for cases with:
+- **Variable** or strongly **evolving production systems**
+- **Long-lived** products
+- **Biogenic** carbon
 
-### Quick links:
-All [documentation](https://timex.readthedocs.io/en/latest/), including detailed description of `timex_lca`.
+## Documentation and Resources:
+- [Full Documentation](https://timex.readthedocs.io/en/latest/)
+- [Installation Guide](https://timex.readthedocs.io/en/latest/content/installation.html)
+- [Example Notebook](https://github.com/TimoDiepers/timex/blob/main/notebooks/example_setac.ipynb)
 
-[Installation instructions](https://timex.readthedocs.io/en/latest/content/installation.html)
-
-[Example notebook](https://github.com/TimoDiepers/timex/blob/main/notebooks/example_setac.ipynb)
-
-
-### Questions and remarks:
-For suggestions of improvements or reporting of bugs, please open an issue on the Github page, send a pull request or directly contact the maintainers.
+### Contributing:
 
+We welcome contributions! If you have suggestions or want to fix a bug, please:
+- [Open an Issue](https://github.com/TimoDiepers/timex/issues)
+- [Send a Pull Request](https://github.com/TimoDiepers/timex/pulls)