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Add release notes for v2.3.0
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documentation/source/users/rmg/releaseNotes.rst

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Release Notes
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RMG-Py Version 2.3.0
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====================
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Date: Dec 20, 2018
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- Arkane (formerly CanTherm):
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- CanTherm had been renamed to Arkane (Automated Reaction Kinetics And Network Exploration)
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- New network exploration functionality using RMG-database
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- Support for all elements has been added for reading quantum output files
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- New supporting information output file with rotational constants and frequencies
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- Known thermo and kinetics can be provided in addition to quantum information
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- Improve general user experience and error handling
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- New machine learning thermo estimator
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- Estimate species thermochemistry using a graph convolutional neural network
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- Estimator trained on quantum calculations at B3LYP and CCSD(T)-F12 levels
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- Currently supports C/H/O/N, with an emphasis on cyclic molecules
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- Resonance:
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- New pathways added for lone-pair multiple-bond resonance, replacing
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two pathways which were more specific
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- New pathways added for aryne resonance
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- Aromatic resonance pathways simplified and refactored to use filtration
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- Kekule structures are now considered unreactive structures
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- Miscellaneous changes:
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- Isotope support added for reading and writing InChI strings
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- New branching algorithm for picking up feedback loops implemented (beta)
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- Global forbidden structure checking is now only done for core species for
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efficiency, which may lead to forbidden species existing in the edge
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- Minor improvements to symmetry algorithm to fix a few incorrect cases
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- Bug fixes:
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- Fixed issue where react flags were being reset when filterReactions was
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used with multiple reactors, resulting in no reactions generated
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- File paths for collision violators log changed to output directory
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- Fixed bug in local uncertainty introduced by ranged reactor changes
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- Fixed bug with diffusion limitation calculations for multi-molecular reactions
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- Various other minor fixes
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RMG-database Version 2.3.0
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==========================
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Date: Dec 20, 2018
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- Kinetics rules to training reactions
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- All kinetics rules have been converted into training reactions by converting
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each group to the smallest molecule that matches it
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- Training reactions are preferred over rules because they correspond to a
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specific reaction and are therefore easier to update
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- This conversion is in anticipation of upcoming changes to trees in kinetics families
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- Additions:
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- R_Addition_MultipleBond training reactions
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- intra_NO2_ONO_conversion training reactions
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- SABIC_aromatics thermo library (CBS-QB3, RRHO)
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- McGowan volumes for noble gases
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- More entries added to Lai_Hexylbenzene libraries
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- Architecture and weights for neural network thermo estimator
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RMG-Py Version 2.2.1
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====================
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Date July 23, 2018

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