⚡ Bolt: [performance improvement] Optimize Pandas iteration

[alinelena]

💡 What:
Refactored pandas dataframe iteration in calc_elasticity.py, gscdb138.py, calc_solvMPCONF196.py, and calc_MPCONF196.py from iterrows() to to_dict('records') or itertuples(index=False, name=None). Also added a .jules/bolt.md learning note.

🎯 Why:
iterrows() is a known performance bottleneck in Pandas as it constructs a Series object for each row. Iterating via to_dict('records') or itertuples() is significantly faster and more memory-efficient.

📊 Impact:
Improves execution speed during iteration. Tests executed perfectly without regressions.

🔬 Measurement:
Run the benchmarks before and after to observe speed improvements, or inspect CPU profiles during data processing.

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PR created automatically by Jules for task 11350768937248521922 started by @alinelena

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