In Loving Memory of
Warren Joseph Hehre (1945 - 2026)
Devoted husband, father, mentor, friend.
The world is less clever in his absence.
SPARTAN IN RESEARCH
Spartan is a general purpose molecular modeling application providing an elegant graphical user interface and integrated molecular mechanics, quantum chemical, and machine learning computational models.
Research is supported from predictive graphical models, integrated spreadsheet and plotting tools, customizable workflows and 2D
and 3D visualization.
SIMPLE. SOFTWARE. SOLUTIONS.
Where do you want to take your chemistry?
SPARTAN AND ODYSSEY IN EDUCATION
Both Spartan'26 and Spartan Student 9 support the molecular components of organic, physical, inorganic, intro to med chem and analytical chemistry courses.
ODYSSEY Instructor 7 and Student 7 includes fully integrated molecular dynamics with a GUI offering a window onto molecular-level concepts in general and physical chemistry. Lab activities included.
WHAT'S NEW
Spartan’26 is now available for Windows, Macintosh and Linux. Including the new MLHF-NMR protocol for highly accurate C shifts of flexible organic molecules. The new protocol takes advantage of the approach and set of machine learning models documented in the articles below and typically requires less than 90 seconds for common natural product structures.
The new release is accompanied by an updated version of the quantum computational engines to the current release of Q-Chem (6.4), and includes several new functionals, improved frequency calculations, VCD spectra. The new graphical interface has been retooled, affording complete 2D and 3D user-views and includes a number of additional enhancements.
13
Machine Learning models
trained to good quality
(empirically corrected)
DFT GIAO NMR shifts
are now available for
1H and 13C centers.
2025, 90, 32, 11478-11485.
Three new “Est. Density Functional Energy” machine learning models are described, assessed, and benchmarked in our latest paper available now: Journal of Computational Chemistry, 2025, 46(12), e70129. Publication Date: May 14, 2025.
The machine learning model “Est. Density Functional Geometry” definition, assessment and benchmarking paper has been released: Journal of Chemical Information and Modeling, 2025, 65, 5, 2314-2321. Publication Date February 17, 2025.
13
13
We are pleased to announce the publication defining the machine learning model termed “Corrected MMFF”
in the current Spartan’24 release, available from the:
Journal of Computational Chemistry, 2025, 46(1), e70016. Publication Date: January 5, 2025.
Spartan’s empirical corrections improve accuracy of DFT C shifts to within ≈2 ppm for rigid molecules. The multi-step NMR Spectrum protocol, providing C shifts within ≈3.5 - 4 ppm for conformationally flexible molecules is defined and assessed. Journal of Natural Products, 2019, 82, 8, 2299-2306.
Featured Article:
Isolated cyclic peptides were identified with support from calculated structure and NMR data. Density functional results established the substitution pattern in an ambiguous aromatic ring moiety (with corroboration from related molecule from the same culture). Journal of Natural Products, 2026,89, 4, 1344-1354.
