Assistant Professor, Chemistry & Biochemistry
research associate, University of Alberta, Canada
postdoc, University of Houston, USA
PhD, University of Alberta, Canada
BSc and MSc, Ivan Franko National University of Lviv, Ukraine
- CHEM 101: General Chemistry I
- CHEM 102: General Chemistry II
- CHEM 111: Nanoscience I
- CHEM 112: Introduction to Materials Chemistry
- CHEM 335: Inorganic Chemistry
- CHEM 336: Inorganic Chemistry Laboratory
- CHEM 437: Computers, Structure and Bonding
- CHEM 460: Chemical Research
Solid state chemistry is the study of composition-structure-property relationship of solid phase materials. Specifically, in our group, we predict with machine-learning and systematize crystal structures of intermetallic compounds containing rare-earth elements and uranium, with the intention to synthesize these phases. Intermetallics are compounds formed by metals or metal-like elements and adopt complex atomic arrangements in their structures due to metallic bonding interactions. Single crystal and powder X-ray diffraction helps us to determine the structures of intermetallic solids. Intermetallics could be used in energy conversion devices, electronics, magnets, or drill bits.
Some of the projects that you might be interested in are listed below.
Machine-learning structure prediction: Discovering new compound is a challenge. Machine-learning methods help analyzing scientific reports, crystallographic database, and high-throughput DFT results to find systematic trends that govern formation of a particular structure. Once the structure is predicted, experimental validation takes place to confirm the proposed structure.
Uranium-containing intermetallics: Radioactive elements are used in curing cancers, generating energy, or even as a warfare tool. No matter how radioactive elements are used, humanity did not yet find the most effective way to deal with physical objects that were in contact with radioactive elements. Solid state chemistry proposes a solution to this problem in an elegant way: isolating waste in a crystalline material. We experimentally search for a crystalline intermetallic material, which can contain uranium surrounded by effective neutron absorbers (e.g., Eu and Gd) in the coordination polyhedra.
Exploratory synthesis: New compounds could be found serendipitously, with a systematic phase-diagram study, or predicted with machine learning. We use arc-melting synthesis, sintering, or metal flux crystal growth to make the phase and study its structure with X-ray diffraction method. Working with precious or radioactive elements we need to confirm that a new compound is highly likely to form in a given system. DFT and machine-learning methods are useful to guide our synthetic efforts.
Mechanical property optimization: We improve hardness and mechanical wear resistance of the materials that will be used for cutting, drilling, and polishing in industry. Gradually changing the composition of a given compound, we can make the bonds in the structure stronger, and as a result, improve the hardness. Polished samples are tested with Vickers hardness tester to probe synthesized intermetallics.
Publications and Scholarly Activities
Publications as an assistant professor (Manhattan College affiliation)
57. Selvaratnam, B.; Oliynyk, A.O.; Mar, A. Explainable machine learning models in solid state chemistry: finding descriptors for Decision Trees using Decision Trees. Under review.
56. Gvozdetskyi, V.; Selvaratnam, B.; Oliynyk, A.O.; Mar, A. Revealing hidden patterns in binary rare-earth intermetallics RX through chemical intuition and interpretable machine learning. Under review.
55. Pinto, A.H.; Cho, D.R.; Oliynyk, A.O.; Silverman, J.R. Green Chemistry applied to Transition Metal Chalcogenides through Synthesis, Design of Experiments, Life Cycle Assessment, and Machine Learning. Green Chemistry – New Perspectives, IntechOpen: Rijeka, 2022. [DOI]
54. Machado, C.; Oliynyk, A.O.; Silverman, J. Tie-Dyeing with Foraged Acorns and Rust: A Workshop Connecting Green Chemistry and Environmental Science. Journal of Chemical Education 99, 2022, 2431–2437. [DOI]
53. Parry, M.; Hendry, J.; Couper, S.; Oliynyk A.O.; Tehrani, A.M.; Brgoch, J.; Miyagi, L.; Sparks, T. Trends in bulk compressibility of Mo2-xWxBC solid solutions. Chemistry of Materials 34, 2569–2575. [DOI]
52. Tyvanchuk, Yu.B.; Fecica M.; Garcia, G.; Mar, A.; Oliynyk, A.O. Ternary rare-earth-metal indides RE23Ni7In4 (RE = Gd, Tb, Dy) with Yb23Cu7Mg4 -type structure Inorganic Chemistry 60, 2021, 17900–17910. [DOI]
51. Sparks, T.D.; Oliynyk A.O.; Romaka, V. Preface to the special issue on machine learning and data-driven design of materials issue in computational materials science. Computational Materials Science 195, 2021, 110452. [DOI]
50. Zhang, D.; Oliynyk, A.O.; Mar, A. Three Rh-rich ternary germanides in the Ce–Rh–Ge system. Journal of Solid State Chemistry 304, 2021, 122585. [DOI]
49. Gzyl, A.S.; Mar, A.; Oliynyk, A.O. Machine Learning in Solid State Chemistry: Heusler Compounds. Encyclopedia of Inorganic and Bioinorganic Chemistry 2021. [DOI]
48. Zhang, Z.; Mansouri Tehrani, A.; Oliynyk, A.O.; Day, B.; Brgoch, J. Finding the Next Superhard Material through Ensemble Learning. Advanced Materials 33, 2021, 2005112. [DOI]
47. Wang, A.Y.-T.; Murdock, R.J.; Kauwe, S.K.; Oliynyk, A.O.; Gurlo, A.; Brgoch, J.; Persson, K.A.; Sparks, T.D. Machine Learning for Materials Scientists: An introductory guide towards best practices. Chemistry of Materials 32, 2020, 4954–4965. [DOI]
46. Gzyl, A.S.; Oliynyk, A.O.; Mar, A. Half-Heusler Structures with Full-Heusler Counterparts: Machine-Learning Predictions and Experimental Validation. Crystal Growth & Design 20, 2020, 6469–6477. [DOI]
45. Mishra, V.; Iyer, A.K.; Mumbaraddi, D.; Oliynyk, A.O.; Zuber, G.; Boucheron, A.; Dmytriv, G.S.; Bernard, G.M.; Michaelis, V.K.; Mar, A. Coloured intermetallic compounds LiCu2Al and LiCu2Ga. Journal of Solid State Chemistry 292, 2020, 121703. [DOI]
44. Abou-Ghanem, M.; Oliynyk, A.O.; Chen, Z.; Matchett, L.; McGrath, D.; Katz, M.; Locock, A.; Styler, S. Photoenhanced ozone uptake by natural titanium-containing minerals: implications for atmospheric mineral dust photochemistry.
Environmental Science & Technology 54, 2020, 13509–13516. [DOI]
43. Thiessen, A.N.; Zhang, L.; Oliynyk, A.O.; Yu, H.; O’Connor, K.M.; Meldrum, A.; Veinot, J.G.C. A Tale of Seemingly “Identical” Silicon Quantum Dot Families: Structural Insight into Silicon Quantum Dot Photoluminescence. Chemistry of Materials 32, 2020, 6838–6846. [DOI]
42. Karmakar, A.; Alkiviathes, M.; Oliynyk, A.O.; Michaelis, V. Tailorable Indirect to Direct Bandgap Double Perovskites with Bright White-Light Emission: Decoding Chemical Structure using Solid-State NMR. Journal of the American Chemical Society 142, 2020, 10780–10793. [DOI]
41. Saal, J.E.; Oliynyk, A.O.; Meredig, B. Machine learning in materials discovery: Confirmed predictions and their underlying approaches. Annual Review of Materials Research 50, 2020. [DOI]
40. Hossain, M.A.; Javadi, M.; Yu, H.; Thiessen, A.N.; Ikpo, N.; Oliynyk, A.O.; Veinot, J.G.C. Dehydrocoupling – An Alternative Approach to Functionalizing Germanium Nanoparticle Surfaces. Nanoscale 12, 2020. [DOI]
39. Oliynyk, A.O.; Buriak, J.M. Virtual Issue on Machine-Learning Discoveries in Materials Science. Chemistry of Materials 31, 2019, 8243–8247. [DOI]
Publications as a research associate (University of Alberta affiliation)
38. Matlinska, M.A.; Ha, M.; Hughton, B.; Oliynyk, A.O.; Iyer, A.K.; Bernard, G.M.; Lambkin G.; Lawrence, M.C.; Katz, M.J.; Mar, A.; Michaelis, V.K. Alkaline Earth Metal–Organic Frameworks with Tailorable Ion Release: A Path for Supporting Biomineralization. ACS Applied Materials & Interfaces 11, 2019, 32739–32745. [DOI]
37. Zhou, Y.; Iyer, A.K.; Oliynyk, A.O.; Heyberger, M.; Lin, Y.; Qui, Y.; Mar, A. Quaternary rare-earth sulfides RE3M0.5M'S7 (M = Zn, Cd; M' = Si, Ge). Journal of Solid State Chemistry 278, 2019, 120914. [DOI]
36. Gzyl, A.S.; Oliynyk, A.O.; Adutwum, L.A.; Mar, A. Solving the Coloring Problem in Half-Heusler Structures: Machine-Learning Predictions and Experimental Validation. Inorganic Chemistry 58, 2019, 9280–9289. [DOI]
35. Schmidt, M.; Jansen van Beek, S.M.; Abou-Ghanem, M.; Oliynyk, A.O.; Locock, A.J.; Styler, S.A. Production of Atmospheric Organosulfates via Mineral-Mediated Photochemistry. ACS Earth and Space Chemistry 3, 2019, 424–431. [DOI]
34. Mumbaraddi, D.; Iyer, A.K.; Üzer, E.; Mishra, V.; Oliynyk, A.O.; Nilges, T.; Mar, A. Synthesis, structure, and properties of rare-earth germanium sulfide iodides RE3Ge2S8I (RE = La,Ce, Pr). Journal of Solid State Chemistry 274, 2019, 162–167. [DOI]
33. Thiessen, A.N.; Ha, M.; Hooper, R.W.; Yu, H.; Oliynyk, A.O.; Veinot, J.G.C.; Michaelis, V.K. Silicon Nanoparticles: Are they Crystalline from the Core to the Surface? Chemistry of Materials 31, 2019, 678–688. [DOI]
32. Han, K.-B.; Chong, S.K.; Oliynyk, A.O., Nagaoka, A.; Petryk, S.; Scarpulla, M.A.; Deshpande, V.V., Sparks, T.D. Enhancement in surface mobility and quantum transport of Bi2-xSbxTe3-ySey topological insulator by controlling the crystal growth conditions. Scientific Reports 8, 2018, 17290-1–17290-10. [DOI]
31. Zhang, D.; Oliynyk, A.O.; Duarte, G.M.; Iyer, A.K.; Ghadbeigi, L.; Kauwe, S.K.; Sparks, T.D.; Mar, A. Not just par for the course: 73 quaternary germanides RE4M2XGe4 (RE = La-Nd, Sm, Gd-Tm, Lu; M = Mn-Ni; X = Ag, Cd) and the search for intermetallics with low thermal conductivity. Inorganic Chemistry 57, 2018, 14249-14259. [DOI]
30. Zhou, Y.; Askar, A.M.; Pöhls, J.-H.; Iyer, A.K.; Oliynyk, A.O.; Shankar, K.; Mar, A. Hexagonal double perovskite Cs2AgCrCl6. Zeitschrift für Anorganische und Allgemeine Chemie 2019, accepted October 15, 2018. [DOI]
29. Bing, C.; Adutwum, L.A.; Oliynyk, A.O.; Luber, E.J.; Olsen, B.C.; Mar, A.; Buriak, J.M. How to Optimize Materials and Devices via Design of Experiments and Machine Learning: Demonstration Using Organic Photovoltaics. ACS Nano 12, 2018, 7434–7444. [DOI]
28. Mishra, V.; Oliynyk, A.O.; Subbarao, U.; Sarma, S. Ch.; Mumbaraddi, D.; Peter, S.C. Complex Crystal Chemistry of Yb6(CuGa)50 and Yb6(CuGa)51 Synthesized at Non-Equilibrium Conditions. Crystal Growth & Design 18, 2018, 6091–6099. [DOI]
27. Oliynyk, A.O.; Mar, A. Discovery of Intermetallic Compounds from Traditional to Machine-Learning Approaches. Accounts for Chemical Research 51, 2018, 59–68. [DOI]
Publications as a postdoctoral researcher (University of Houston affiliation)
26. Parry, M.; Couper, S.; Tehrani, A. M.; Oliynyk, A.O.; Brgoch, J.; Miyagi, L.; Sparks, T.D. Lattice strain and texture analysis of superhard Mo0.9W1.1BC and ReWC0.8 via diamond anvil cell deformation. Journal of Materials Chemistry A 7, 2020, 24012–24018 . [DOI]
25. Tehrani, A.M.; Oliynyk, A.O.; Rizvi, Z.; Lotfi, S.; Parry, M.; Sparks, T.D.; Brgoch, J. Atomic substitution to balance hardness ductility and sustainability in molybdenum tungsten borocabide. Chemistry of Materials 31, 2019, 7696–7703. [DOI]
24. Viswanathan, G.; Oliynyk, A.O.; Antono, E.; Ling, J.; Meredig, B.; Brgoch, J. Single Crystal Automated Refinement (SCAR): A Data-Driven Method for Solving Inorganic Structures. Inorganic Chemistry 58, 2019, 9004–9015. [DOI]
23. Zhuo, Y.; Tehrani, A.M.; Oliynyk, A.O.; Duke, A.C.; Brgoch, J. Identifying an Efficient, Zero-Thermal Quenching Inorganic Phosphor Host via Machine Learning. Nature Communicatoins 9, 2018, 4377-1–4355-10. [DOI]
22. Lotfi, S.; Oliynyk, A.O.; Brgoch, J. Polyanionic gold-tin bonding and crystal structure preference in REAu1.5Sn0.5 (RE = La, Ce, Pr, Nd). Inorganic Chemistry 57, 2018, 10736–10743. [DOI]
21. Tehrani, A.M.; Oliynyk, A.O.; Parry, M.; Rizvi, Z.; Couper, S.; Lin, F.; Miyagi, L.; Sparks, T.D.; Brgoch, J. Machine learning directed search for ultraincompressible, superhard materials. Journal of the American Chemical Society 140, 2018, 9844–9853. [DOI]
20. Oliynyk, A.O.; Gaultois, M.W.; Hermus, M.; Morris, A.J.; Mar, A.; Brgoch, J. Searching for Missing Binary Equiatomic Phases: Complex Crystal Chemistry in the Hf–In System. Inorganic Chemistry 57, 2018, 7966–7974. [DOI]
19. Oliynyk, A.O.; Adutwum, L.A.; Rudyk, B.W.; Pisavadia, H.; Lotfi, S.; Hlukhyy, V.; Harynuk, J.J.; Mar, A.; Brgoch, J. Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABC. Journal of the American Chemical Society 139, 2017, 17870–17881. [DOI]
Publications as a graduate student (University of Alberta affiliation)
18. Oliynyk, A.O.; Antono, E.; Sparks, T.D.; Ghadbeigi, L.; Gaultois, M.W.; Meredig, B.; Mar A. High-throughput machine-learning-driven synthesis of full-Heusler compounds. Chemistry of Materials 28, 2016, 7324–7331. [DOI]
17. Oliynyk, A.O.; Adutwum, L.A.; Harynuk, J.J.; Mar, A. Classifying crystal structures of binary compounds AB through cluster resolution feature selection and support vector machine analysis. Chemistry of Materials 28, 2016, 6672–6681. [DOI]
16. Oliynyk, A.O.; Sparks, T.D.; Gaultois, M.W.; Ghadbeigi, L.; Mar, A. Gd12Co5.3Bi and Gd12Co5Bi, crystalline doppelgänger with low thermal conductivities. Inorganic Chemistry 55, 2016, 6625–6633. [DOI]
15. Gaultois, M.W.; Oliynyk, A.O.; Mar, A.; Mulholland, G.J.; Sparks, T.D.; Meredig, B. Web-based machine learning models for real-time screening of thermoelectric materials properties. APL Materials 4, 2016, 053213-1–053213-11. [DOI]
14. Lomnytska, Ya.; Babizhetskyy, V.; Oliynyk, A.O.; Toma, O.; Dzevenko, M.; Mar, A. Interaction of tantalum, chromium, and phosphorus at 1070 K: Phase diagram and structural chemistry. Journal of Solid State Chemistry 235, 2016, 50–57. [DOI]
13. Sparks, T.D.; Gaultois, M.W.; Oliynyk, A.O.; Brgoch, J.; Meredig, B. Data mining our way to the next generation of thermoelectrics Scripta Materialia 111, 2016, 10–15. [DOI]
12. Oliynyk, A.O.; Stoyko, S.S.; Mar, A. Many metals make the cut: quaternary rare-earth germanides RE4M2InGe4 (M = Fe, Co, Ni, Ru, Rh, Ir) and RE4RhInGe4 derived from excision of slabs in RE2InGe2. Inorganic Chemistry 54, 2015, 2780–2792. [DOI]
11. Lomnytska, Ya.; Dzevenko, M.; Oliynyk, A.; Kushnir, I.; Toma, O. The phase equilibria and crystal structure of the phases in the Hf–Ti–P system. Journal of Alloys and Compounds 633, 2015, 75–82. [DOI]
10. Oliynyk, A.O.; Djama-Kayad, K.; Mar, A. Investigation of phase equilibria in the quaternary Ce–Mn–In–Ge system and isothermal sections of the boundary ternary systems at 800 °C. Journal of Alloys and Compounds 622, 2015, 837–841. [DOI]
9. Rudyk, B.W.; Stoyko, S.S.; Oliynyk, A.O.; Mar, A. Rare-earth transition-metal gallium chalcogenides RE3MGaCh7 (M=Fe, Co, Ni; Ch=S, Se). Journal of Solid State Chemistry 210, 2014, 79–88. [DOI]
8. Oliynyk, A.O.; Djama-Kayad, K.; Mar, A. Ternary rare-earth manganese germanides RE3Mn2Ge3 (RE = Ce–Nd) and a possible oxygen-interstitial derivative Nd4Mn2Ge5O0.6. Journal of Alloys and Compounds 602, 2014, 130–134. [DOI]
7. Toma, O.; Dzevenko, M.; Oliynyk, A.; Lomnytska, Ya. The Ti–Fe–P system: phase equilibria and crystal structure of phases. Central European Journal of Chemistry 11, 2013, 1518–1526. [DOI]
6. Oliynyk, A.O.; Mar, A. Rare-earth manganese germanides RE2+xMnGe2+y (RE = La, Ce) built from four-membered rings and stellae quadrangulae of Mn-centred tetrahedral. Journal of Solid State Chemistry 206, 2013, 60–65. [DOI]
5. Oliynyk, A.O.; Stoyko, S.S.; Mar, A. Quaternary germanides RE4Mn2InGe4 (RE = La–Nd, Sm, Gd–Tm, Lu). Inorganic Chemistry 52, 2013, 8264–8271. [DOI]
4. Oliynyk, A.O.; Stoyko, S.S.; Mar, A. New ternary germanides RE3M2Ge3 (RE = Gd–Tm, Lu; M = Ru, Ir). Journal of Solid State Chemistry 202, 2013, 241–249. [DOI]
3. Oliynyk, A.O.; Lomnytska, Ya.F; Dzevenko, M.V.; Stoyko, S.S.; Mar, A. Phase equilibria in the Mo−Fe−P system at 800 °C and structure of ternary phosphide (Mo1−xFex)3P (0.10 ≤ x ≤ 0.15). Inorganic Chemistry 52, 2013, 983–991. [DOI]
2. Oliynyk, A.O.; Oryshchyn, S.V.; Lomnytska, Ya.F. New compounds and phase equilibria in the Zr–Ti–P system. Journal of Alloys and Compounds 545, 2012, 80–84. [DOI]
1. Lomnytska, Ya.; Oliynyk A. The refinement of the components interaction in the system Zr–Nb–P. Visnyk of the Lviv University. Series Chemistry 53, 2012, 36–41.