How can I coin a topic that will include a moderating/mediating variable with capital structure and financial sustainability as the independent and dependent variables respectively?
You can add a moderate variable that improves the relationship between the dependent and independent variable, provided that the moderate variable is present in previous studies with the independent variable in a published research and again with the dependent variable.
Have a look at Dirk Schoenmaker's Lab Institution: Rotterdam School of Management Department: Department of Finance. Perhaps you wil find in their publications an answer of your very interesting research question.
I do not know if a moderating variable is a solution to your research question.
First, you have to clarify many issues before your research question can be answered. We know what capital structure means in Finance. What do you mean by moderating/mediating variable with capital structure? Please clearly define what moderating or mediating variable with capital structure is. Next, you must define what you mean by "Financial Sustainability". Once these concepts are clearly defined, you will be able to assign key financial variables to each one of them, be able to see which one is the dependent variable and which ones are the independent variables. Finally, you can regress the dependent variable over the independent variables and be able to interpret the results.
The relationship here is between risk, capital, and operational/financial performance (which leads to financial sustainability). The capital structure plays a moderating effect on the relationship between risk and performance. Capital funding moderates the impact of risk-taking or risk exposure on financial performance.
A mediating variable (or mediator) explains the process through which two variables are related, while a moderating variable (or moderator) affects the strength and direction of that relationship.
Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. These variables are important to consider when studying complex correlational or causal relationships between variables.