Merge pull request #18 from espottesmith/main

Change logo text color and make small paper and README changes in response to reviewer comments

README.md

@@ -28,4 +28,10 @@ If you don't know where to start, you can check out the open [issues](https://gi
 
 Have a problem installing or running RNMC, or have an idea for how the code could be better? Need support in using RNMC? Please open a new issue, and label the issue (with *e.g.*, “bug”, “enhancement”, or “question”) so that we can triage appropriately. Issues are preferred over e-mails or other private communications because multiple users might encounter the same problem.
 
-A more complete guide to contributing can be found in our [online documentation](https://blaugroup.github.io/RNMC/Contributors.html).
+A more complete guide to contributing can be found in our [online documentation](https://blaugroup.github.io/RNMC/Contributors.html).
+
+## Limitations
+
+In its current form, `RNMC` only allows reactions with up to two reactants and up to two products. Ternary and other n-ary reactions cannot be included in `RNMC` simulations, though this would be possible with modest modifications to the code.
+
+Reaction selection in kinetic Monte Carlo simulations can in principle be performed in $O(1)$ time (see Slepoy et al., *J. Chem. Phys.* **128**(205101) (2008). [DOI: 10.1063/1.2919546](https://doi.org/10.1063/1.2919546)). However, we have not yet implemented this algorithm, and simulations with `RNMC` are limited to at least $O(log(R))$ scaling, where $R$ is the number of reactions in the network.

paper.md

@@ -61,8 +61,7 @@ In order to capture complex processes with high fidelity, simulation methods tha
 While techniques like molecular dynamics and *ab initio* simulations capture dynamics and reactivity at high resolution, they cannot be used beyond relatively small length (hundreds to thousands of atoms) and time scales (picoseconds to microseconds).
 Kinetic Monte Carlo (kMC) approaches overcome these limitations to bridge length and time scales across several orders of magnitude while retaining relevant microscopic resolution, making it a powerful and flexible tool.
 
-
-Here, we present `RNMC`, an easy-to-use, modular, high-performance kMC simulation framework that enables modeling of complex systems.
+Here, we present Reaction Network Monte Carlo (`RNMC`), an easy-to-use, modular, high-performance kMC simulation framework that enables modeling of complex systems.
 `RNMC` consists of a core module defining the common features of kMC algorithms, including an implementation of the Gillespie algorithm [@gillespie1977exact], input/output operations leveraging SQLite databases, random number sampling, threading logic for parallel execution, and dependency graphs for efficient event propensity updates.
 In addition, there are currently three modules defining kMC implementations for different types of applications.
 The `GMC` (Gillespie Monte Carlo) module enables simulations of reaction networks in a homogeneous (well-mixed) environment.