Profile
| Keywords: | Machine learning, Solid state chemistry, Inorganic materials |
Arthur Mar leads an outstanding research program in inorganic solid-state chemistry at the University of Alberta. He is an international leader recognized for his authoritative expertise in inorganic materials (Zintl phases, intermetallics, pnictides, chalcogenides), characterization methods (especially X-ray crystallography), and applications (thermoelectric, ferromagnetic, superconducting, and optical materials). Over the past 30 years, Mar has attained a distinguished international reputation in intermetallic chemistry, having published >255 articles and given >135 invited presentations. He has led pioneering efforts to apply machine-learning approaches to guide materials discovery, making groundbreaking advances to predict crystal structures, to identify thermoelectric materials, and to improve efficiencies of energy-conversion materials. He has served on the editorial boards of Chemistry of Materials, Journal of Solid State Chemistry, and Acta Crystallographica. He was chair for the Gordon Conference on Solid State Chemistry (2024). In addition to being recognized as an excellent researcher (through the Faculty of Science Research Award at the University of Alberta and the Canadian Light Source T.K. Sham Award in Materials Chemistry), he is an outstanding, award-winning teacher who is highly valued for his enthusiastic contributions to chemical education. He was a Professeur invité at the Université de Rennes 1 (2003), a Distinguished Visiting Scholar at Beijing Normal University (2017), and a Distinguished Overseas Professor at Shanghai University of Engineering Science (2019). FES Funded ProjectsOutputs
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| Structure and optical properties of LixAg1-xGaSe2 and LixAg1-xInSe2T12-P01 University of Alberta | Publication | 2023-04-28 | Mohammad Jomaa, Vidyanshu Mishra, Dundappa Mumbaraddi, Ritobroto Sikdar, "Diganta Sarkar ", "Mengran Sun ", "Jiyong Yao ", Michaelis, V., Mar, A. | | Machine-learning prediction of new Laves phases with experimental validationT12-P01 University of Alberta | Activity | 2022-06-16 | Ritobroto Sikdar, Balaranjan Selvaratnam, "Partha Jana ", "Nilanjan Roy ", Mar, A. | | Ahead by a Century: Discovery of Laves Phases Assisted by Machine LearningT12-P01 University of Alberta | Publication | 2024-03-19 | Ritobroto Sikdar, "Nilanjan Roy ", Balaranjan Selvaratnam, Vidyanshu Mishra, Dundappa Mumbaraddi, "Amit Mondal ", "Krishnendu Buxi ", Partha Pratim Jana, Mar, A. | | Crystal growth of multivalent rare-earth intermetallics using metal fluxesT12-P01 University of Alberta | Activity | 2023-06-06 | Dundappa Mumbaraddi, Vidyanshu Mishra, Ritobroto Sikdar, Mar, A. | | Machine-learning classification of Laves phases and prediction of new compoundsT12-P01 University of Alberta | Activity | 2023-06-08 | Ritobroto Sikdar, Balaranjan Selvaratnam, Vidyanshu Mishra, "Nilanjan Roy ", Partha Pratim Jana, Mar, A. | | Effect of Li Addition on the Nonlinear Optical Activity of Ag1-xLixMSe2 (M = Ga, In)T12-P01 University of Alberta | Activity | 2023-06-08 | Mohammad Jomaa, Vidyanshu Mishra, Dundappa Mumbaraddi, Ritobroto Sikdar, "Diganta Sarkar ", "Mengran Sun ", "Jiyong Yao ", Michaelis, V., Mar, A. | | Effect of Li Addition on the Nonlinear Optical Activity of Ag1-xLixMSe2 (M = Ga, In)T12-P01 University of Alberta | Activity | 2023-08-01 | Mohammad Jomaa, Vidyanshu Mishra, Dundappa Mumbaraddi, Ritobroto Sikdar, "Diganta Sarkar ", "Mengran Sun ", "Jiyong Yao ", Michaelis, V., Mar, A. | | Structure and optical properties of LixAg1–xAlSe2T12-P01 University of Alberta | Publication | 2024-07-29 | "Mohammed Jomaa ", Vidyanshu Mishra, Dundappa Mumbaraddi, "Diganta Sarkar ", Ritobroto Sikdar, "Mengran Sun ", "Jiyong Yao ", Michaelis, V., Mar, A. | | Is there a simple descriptor to predict Laves phases?T12-P01 University of Alberta | Publication | 2025-01-27 | Ritobroto Sikdar, Balaranjan Selvaratnam, Vidyanshu Mishra, Mar, A. | | Unlocking the perovskite of intermetallics with interpretable machine learningT12-P01 University of Alberta | Activity | 2024-07-24 | Dundappa Mumbaraddi, Ritobroto Sikdar, Vidyanshu Mishra, Mar, A. | | Ahead by a Century: Discovery of Laves Phases Assisted by Machine LearningT12-P01 University of Alberta | Activity | 2024-07-24 | | | Are selenides the same as sulfides? Structure, spectroscopy, and properties of narrow-gap rare-earth semiconductors RE2Sn(S1-xSex)5 (RE = La, Ce; x = 0-0.8)T12-P01 University of Alberta | Publication | 2024-05-24 | | | Rare-earth-doped La3Si2S8I: Potential materials for phosphor-converted white LEDsT12-P01 University of Alberta | Activity | 2024-06-03 | Trinanjan Dey, Dundappa Mumbaraddi, Riley Hooper, Al Meldrum, Mar, A. | | Discovery of inorganic solids with desired structure motifs guided by machine learningT12-P01 University of Alberta | Activity | 2024-06-03 | Volodymyr Gvozdetskyi, "Bryan Owens-Baird ", Allison Thomé, "Arka Sarkar ", Balaranjan Selvaratnam, "Mohammed Jomaa ", "Kirill Kovnir ", Mar, A. | | Expanding the compositional space of quaternary multi-principal element alloys through interpretable machine learning and experimental validationT12-P01 University of Alberta | Activity | 2024-06-03 | Volodymyr Gvozdetskyi, Allison Thomé, Balaranjan Selvaratnam, Mar, A. | | Discovery of Intermetallic Compounds from Traditional to Machine-Learning ApproachesAn invited review article on machine-learning approaches to materials discovery in a special issue of Accounts of Chemical Research on "Advancing Chemistry through Intermetallic Compounds." This paper was highlighted on the journal cover.T12-P01 University of Alberta | Publication | 2017-12-15 | | | Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABCThis paper illustrates that apparently "ambiguous" predictions (with probabilities in an intermediate range not close to zero or one) made by machine-learning methods can be interpreted in a meaningful way by relating them to the likely occurrence of structural polymorphism, as illustrated here for ternary phases ABC. The work is an important breakthrough in machine-learning methods for structural predictions.T12-P01 University of Alberta | Publication | 2017-11-13 | Anton Oliynyk, Lawrence Adutwum, Brent W Rudyk, Harshil Pisavadia, "Sogol Lotfi ", "Viktor Hlukhyy ", James J Harynuk, Mar, A., "Jakoah Brgoch " | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2018-04-20 | | | Prediction of Novel Compounds and Rapid Property Screening through a Machine Learning ApproachT12-P01 University of Alberta | Activity | 2018-04-06 | Anton Oliynyk, "Jakoah Brgoch ", Mar, A. | | Searching for Missing Binary Equiatomic Phases: Complex Crystal Chemistry in the Hf–In SystemThis paper applies a combined approach of machine learning, first-principles calculations, and experimental validation to discover a new binary intermetallic compound. The important insight gained from this work is that despite complexities such as disorder and site mixing, machine-learning methods can nevertheless be useful in helping to predict an initial model.T12-P01 University of Alberta | Publication | 2018-06-21 | Anton Oliynyk, "Michael Gaultois ", "Martin Hermus ", "Andrew Morris ", Mar, A., "Jakoah Brgoch " | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2018-02-23 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2018-02-21 | | | How to look for compoundsT12-P01 University of Alberta | Activity | 2017-05-22 | | | How to look for compoundsT12-P01 University of Alberta | Activity | 2017-05-16 | | | How to look for compoundsT12-P01 University of Alberta | Activity | 2017-05-02 | | | Excellence in Undergraduate TeachingAwarded by Interdepartmental Science Students' Society every yearT12-P01 University of Alberta | Award | 2018-01-11 | | | Excellence in Undergraduate TeachingAwarded by Interdepartmental Science Students' Society every yearT12-P01 University of Alberta | Award | 2017-01-09 | | | Students' Choice Honour Roll Awarded to instructors of Science courses attaining >75% percentile average on student evaluationsT12-P01 University of Alberta | Award | 2018-04-04 | | | Hexagonal Double Perovskite Cs2AgCrCl6Published in a special issue celebrating the 60th birthday of Thomas Fässler (a renowned main-group
inorganic chemist at the Technical University of Munich), this invited paper reports on a new double
perovskite (belong to the family of halide perovskites that are of current popular interest as photovoltaic materials) that is unexpectedly not cubic but rather hexagonal.T12-P01, T12-P02 University of Alberta | Publication | 2018-10-31 | "Yuqiao Zhou ", "Abdelrahman Askar ", Jan Poehls, Abishek K Iyer, Anton Oliynyk, Shankar, K., Mar, A. | | How To Optimize Materials and Devices via Design of Experiments and Machine Learning: Demonstration Using Organic PhotovoltaicsThis widely publicized paper, in the form of a “Perspective,” was the result of an ongoing collaboration between the Buriak and Mar group, illustrating how machine learning is applied to optimize several experimental conditions so that efficiencies of photovoltaic devices can be rapidly improved. [To date, this paper has been viewed over 7100 times in just over a year.]T12-P01, T12-P04 University of Alberta | Publication | 2018-07-01 | Bing Cao, Lawrence Adutwum, Anton Oliynyk, Erik Luber, Brian Olsen, Mar, A., Jillian Mary Buriak | | 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 ConductivityThis paper tackles two scientific challenges, the first in the synthesis of a large number (73) of intermetallic quaternary germanides (more than doubling the previously known examples) and the second in validating machine-learning predictions for discovering compounds with low thermal conductivity (a key criterion for thermoelectric materials, which provide a possible solution for energy conversion of heat to electricity). A reviewer of this paper noted that “Mar is a pioneer in the application of machine learning for inorganic chemistry.”T12-P01, T12-Z01 University of Alberta | Publication | 2018-10-26 | Dong Zhang, Anton Oliynyk, "Gabriel Duarte ", "Abishek Iyer ", "Leila Ghadbeigi ", "Steven Kauwe ", "Taylor Sparks ", Mar, A. | | Synthesis, structure, and properties of rare-earth germanium sulfide iodides RE3Ge2S8I (RE = La, Ce, Pr)Mixed-anion compounds in general are relatively scarce, so the synthesis of a new series of chalcogenide halides reported here is a significant achievement; they offer greater flexibility for controlling band gaps of semiconducting compounds.T12-P01, T12-Z01 University of Alberta | Publication | 2019-03-18 | Dundappa Mumbaraddi, "Abishek Iyer ", "Ebru Üzer ", Vidyanshu Mishra, Anton Oliynyk, "Tom Nilges ", Mar, A. | | Thermoelectric properties of inverse perovskites A3TtO (A = Mg, Ca; Tt = Si, Ge): Computational and experimental investigationsPublished in a special issue dedicated to the topic of “Advanced Thermoelectrics,” this invited paper reports high-level computational predictions of an unusual class of solids, namely inverse perovskites, that have
rarely been reported as thermoelectric materials; the predictions were validated by experimental
measurements of physical transport properties.T12-P01, T12-Z01 University of Alberta | Publication | 2019-07-12 | | | Solving the Colouring Problem in Half-Heusler Structures: Machine-Learning Predictions and Experimental ValidationThis paper tackles a significant challenge in inorganic structural chemistry known as the “colouring problem,” namely how atoms are distribution over different sites in a crystal structure. For the first time, we successfully apply a machine-learning approach to predict the site distributions in the very large family several hundred compounds) of half-Heusler compounds, which find many applications as thermoelectric and spintronic materials. Unique to our approach, we validate these predictions with experimental measurements.T12-P01, T12-Z01 University of Alberta | Publication | 2019-06-25 | Alex Gzyl, Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Crystallography in Chemistry and Materials ScienceThis was an invited talk to a crystallography workshop, where I discussed how crystallography is used on a practical level for materials science research, and includes an introduction to how machine learning can help advance understanding in structural chemistry.T12-P01 University of Alberta | Activity | 2018-05-24 | | | Ternary and quaternary rare‐earth germanides: discovery of intermetallic compounds from traditional to machine‐learning approachesT12-P01 University of Alberta | Activity | 2018-09-05 | | | Accelerating the discovery of solid state materials: From traditional to machine- learning approachesThis was an invited talk to a small (~25 participants) select group of experts in machine-learning at the Telluride Science Workshops.T12-P01 University of Alberta | Activity | 2018-10-01 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesThis was an invited talk to the Chemical and Materials Engineering department as part of their "D. B. Robinson Distinguished Speakers Series."T12-P01 University of Alberta | Activity | 2018-09-20 | | | High-Throughput Approaches for Discovering Thermoelectric MaterialsThis was an invited seminar to the University of Waterloo as part of their seminar series for their CREATE program known as "HEATER" focused on the development of thermoelectric materials. The seminar was simultaneously broadcast to McMaster University and the University of Toronto.T12-P01, T12-Z01 University of Alberta | Activity | 2018-10-26 | | | How large is an atom?Contributed talk. We employed a machine-learning approach to gain chemical insight on the factors that affect atomic size, with implications on how this revises some fundamental concepts in crystal chemistry such as radius ratio rules. This model also accurately predicts interatomic distances in hypothetical compounds, which can be valuable information when investigating experimentally challenging systems containing expensive or radioactive elements.T12-P01 University of Alberta | Activity | 2018-05-28 | Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Discovery of Noncentrosymmetric Ternary Compounds from Elemental Composition: A Machine-Learning ApproachContributed talk. The absence of an inversion centre in crystalline solids is an important prerequisite for many useful electrical and optical properties in materials applications such as piezoelectric and nonlinear optical devices. Here, we apply machine-learning approaches to discover new noncentrosymmetric compounds based solely on their composition.T12-P01 University of Alberta | Activity | 2018-05-28 | Lawrence Adutwum, Anton Oliynyk, Jan Poehls, "Yuqiao Zhou ", Mar, A. | | Classification of Half-Heusler Compounds through Machine Learning ApproachesContributed talk. Half-Heusler compounds have many applications as thermoelectric materials, spintronic materials, superconductors, and topological insulators. We have applied machine-learning approaches to classify, verify, and predict half-Heusler compounds.T12-P01, T12-Z01 University of Alberta | Activity | 2018-05-28 | Alex Gzyl, Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Ternary Germanides in the Ce–M–Ge (M = Rh, Co) SystemsContributed talk. The Ce–Rh–Ge system was investigated as part of the search for new cerium intermetallics, which are excellent candidates to observe unusual magnetic and heavy-fermion behaviour.T12-Z01 University of Alberta | Activity | 2018-05-28 | Dong Zhang, Anton Oliynyk, "Gabriel Duarte ", "Abishek Iyer ", Mar, A. | | Quaternary Rare-Earth Transition-Metal Germanides RE4M2CdGe4 and RE4M2AgGe4 (RE = La–Sm, Gd–Tm, Lu; M = Mn–Ni)Contributed poster.T12-P01, T12-Z01 University of Alberta | Activity | 2018-05-29 | Dong Zhang, Anton Oliynyk, "Abishek Iyer ", "Gabriel Duarte ", "Leila Ghadbeigi ", "Taylor Sparks ", Mar, A. | | In Search of Coloured IntermetallicsContributed poster.T12-P01, T12-Z01 University of Alberta | Activity | 2018-05-29 | | | Structure and Luminescence Properties of Rare-Earth Chalcohalides RE3Ge2Ch8X (Ch = S, Se; X = Cl, Br, I)Contributed poster.T12-P01, T12-Z01 University of Alberta | Activity | 2018-05-29 | Dundappa Mumbaraddi, "Abishek Iyer ", "Ebru Üzer ", "Tom Nilges ", Mar, A. | | Classification of Half-Heusler Compounds through Machine-Learning ApproachesContributed poster.T12-P01, T12-Z01 University of Alberta | Activity | 2018-07-25 | Alex Gzyl, Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Accelerating the Discovery of Solid State Materials with Machine-Learning ApproachesContributed poster.T12-P01 University of Alberta | Activity | 2018-07-25 | | | Introduction to Machine Learning: A Practical WorkshopThis full-day workshop to introduce machine learning for materials discovery and analysis was organized and offered by several members of FES.
This workshop provided an overview of machine learning applied by UofA researchers at
Engineering and Chemistry departments. The introduction to the practical application included
data processing and preparation aspects, as well as creating and running machine-learning models
on free demo version software. Participants had an opportunity to learn step-by-step how to
handle the data, use the models, and interpret the results.
This workshop was offered twice, first on August 13, 2018 and second on August 16, 2018.T12-P01 University of Alberta | Activity | 2018-08-13 | Anton Oliynyk, Lawrence Adutwum, Mar, A., "Ajay Ganesh ", "Anjana Puliyanda ", "Kaushik Sivaramakrishnan ", Gokul Sai Subraveti, Kasturi Nagesh Pai, Prasad, V. | | Machine Learning and Models: How we find optimal materials for Solar and CCS technologiesFuture Energy Systems hosted its first Interdisciplinary Lunch and Learn, Machine Learning and Models: How we find optimal materials for Solar and CCS technologies. The session brought together two research groups from different themes and faculties that had never previously had an opportunity to collaborate.T02-P02, T12-P01 University of Alberta | Activity | 2018-05-15 | Anton Oliynyk, Alex Gzyl, Jan Poehls, Mar, A., Rajendran, A., Gokul Sai Subraveti, Kasturi Nagesh Pai, Prasad, V. | | Computational workshopThis workshop involved discussion of advanced techniques for computation of electronic structure, especially for highly disordered structures, which is relevant for many materials used for solar energy conversion. It was led by a visiting professor, Vitaliy Romaka, from Lviv Polytechnic University, who is an expert in this area.T12-P01 University of Alberta | Activity | 2018-09-13 | "Vitaliy Romaka ", Anton Oliynyk, Mar, A., Alex Gzyl, Vidyanshu Mishra | | USchool: Materials and InformaticsMini-lesson (2 hours) taught to Grade 8 students about materials and informatics, including several demonstrations on superconductivity, magnetism, solar cells, and thermoelectrics. Students and teachers were highly appreciative of this exciting lesson.T12-P01 University of Alberta | Activity | 2019-03-08 | Anton Oliynyk, Alex Gzyl, "Yuqiao Zhou ", "Yu Qiu ", Dundappa Mumbaraddi, Mar, A. | | Accelerating the Discovery of Materials: Machine-Learning ApproachThis was an invited seminar to the Carnegie Institution for Science.T12-P01 University of Alberta | Activity | 2019-02-25 | | | Accelerating the Discovery of Materials with Machine Learning: Potential Roadblocks and How to Overcome ThemThis was an invited seminar to a workshop about machine learning.T12-P01 University of Alberta | Activity | 2019-04-05 | | | Ternary and Quaternary Rare-Earth Transition-Metal GermanidesThis is the M.Sc. thesis for my graduate student Dong Zhang.T12-P01, T12-Z01 University of Alberta | Publication | 2019-01-16 | | | Effectively Exploring Parameter Space: Design of Experiments and Machine Learning-assisted Organic Solar Cell Efficiency OptimizationInvited talk at the annual American Physical Society meeting, Boston, MA
https://meetings.aps.org/Meeting/MAR19/Session/B55.7T12-P04 University of Alberta | Activity | 2019-03-04 | Erik Luber, Brian Olsen, Mar, A., Anton Oliynyk, Lawrence Adutwum, Jillian Mary Buriak | | Invited talk: ACS national meeting, Boston Invited seminar at NASA symposium on space exploration. Seminar was about solar energy optimization. Talk by Buriak.T12-P04 University of Alberta | Activity | 2019-04-18 | Jillian Mary Buriak, Mar, A., Anton Oliynyk, Lawrence Adutwum, Erik Luber, Brian Olsen | | Quarternary Rare-earth Transition-Metal Germanides: RE4M2CdGe4 and RE4M2AgGe4 (RE=La-SM, Gd-Lu, M=Mn-Ni)Conference poster.T12-Z01 University of Alberta | Activity | 2018-05-28 | Dong Zhang, Anton Oliynyk, G M Duarte, Ashwin K. Iyer, "L Ghadbeigi ", T D Sparks, Mar, A. | | Ternary Germanides in Ce-M-Ge System (M=Rh, Co)Conference presentation.T12-Z01 University of Alberta | Activity | 2018-05-30 | Dong Zhang, Anton Oliynyk, G M Duarte, Mar, A. | | Alkaline Earth Metal-Organic Frameworks with Tailorable Ion Release: A Path for Supporting BiomineralizationT02-Z01 University of Alberta | Publication | 2019-08-01 | Michelle Ha, M A Matlinska ", "B Hughton ", Anton Oliynyk, Ashwin K. Iyer, Guy Bernard, G Lambkin ", M C Lawrence, M J Katz ", Mar, A., Michaelis, V. | | Quaternary rare-earth sulfides RE3M0.5M'S7 (M = Zn, Cd; M' = Si, Ge)T12-P01 University of Alberta | Publication | 2019-08-15 | "Yuqiao Zhou ", Abishek K Iyer, Anton Oliynyk, Manon Heyberger, "Yixuan Lin ", "Yu Qiu ", Mar, A. | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2019-05-06 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2019-05-10 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2019-05-15 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2019-05-17 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2019-05-24 | | | Accelerating the Discovery of Solid State Materials: From Traditional to Machine-Learning ApproachesT12-P01 University of Alberta | Activity | 2019-05-27 | | | Rare-earth transition-metal oxyselenidesContributed talk.T12-P01 University of Alberta | Activity | 2019-06-06 | Vidyanshu Mishra, Abishek K Iyer, Dundappa Mumbaraddi, Anton Oliynyk, Mar, A. | | Exploring the colours of gold alloys with machine learningContributed posterT12-P01 University of Alberta | Activity | 2019-06-06 | Anton Oliynyk, Vidyanshu Mishra, Dundappa Mumbaraddi, Mar, A. | | Discovery of ternary noncentrosymmetric compounds: A machine-learning approach with experimental proofContributed oral presentationT12-P01 University of Alberta | Activity | 2019-06-07 | Lawrence Adutwum, Anton Oliynyk, Vidyanshu Mishra, Mar, A. | | Accelerating the Discovery of Materials with Machine Learning: Potential Roadblocks and How to Overcome ThemContributed oral presentationT12-P01 University of Alberta | Activity | 2019-06-07 | Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Accelerated discovery of perovskites and prediction of band gaps using machine-learning methodsContributed oral presentationT12-P01 University of Alberta | Activity | 2019-06-07 | Alex Gzyl, Jonathan Trach, Anton Oliynyk, Mar, A. | | X-ray diffraction short courseThis was a half-day technical short course presented to the Atums students.T12-Z01 University of Alberta | Activity | 2019-07-18 | | | Machine-learning predictions of half-Heusler structuresT12-P01, T12-Z01 University of Alberta | Activity | 2019-10-01 | | | Design of Experiments and Machine Learning-Assisted Organic Solar Cell Efficiency OptimizationOrganic solar cells (OSCs) represent a cost-effective way to transform solar energy into electricity due to their potential for low-cost and high-throughput roll-to-roll production.[1] Improving OSC efficiency and stability are two of the most important tasks on the way toward commercialization. While much effort has been focused on developing new materials, there is enormous room with respect to optimization of the processing of OSCs to achieve optimal performance of a particular photoactive material. Morphology of the bulk heterojunction, the most important layer within an OSC, results from nanoscale phase segregation that depends extensively upon processing. However, the optimization process for an OSC is tedious, time-consuming and expensive involving many parameters. Conventional optimization uses unimodal approach where one parameter is optimized while all others are kept constant. This can take months or years. Moreover, there is an associated risk of missing the optimal results because all experimental combinations for all parameters cannot be performed. Herein, we report an approach that uses Design of Experiments (DOE) along with machine learning statistical data analysis to effectively and efficiently optimize solar cell efficiency. Machine learning algorithms are trained to find patterns in datasets which could greatly assist data analysis and parameter importance evaluation, hence predict the results for future experiments.[2] DOE methods allow experimentalists to explore a larger parameter space with fewer experimental trials while obtaining valid and objective conclusions. We show that, using the principles of DOE to plan experiments combined with using machine learning assist in the prediction of optimized solar cells. Specific examples of concrete improvement of the power conversion efficiency of OSCs will be described. T12-P04 University of Alberta | Activity | 2018-05-25 | Bing Cao, Lawrence Adutwum, Brian Olsen, Anton Oliynyk, Erik Luber, Tate Hauger, Mar, A., Jillian Mary Buriak | | Influence of hidden halogen mobility on local structure of CsSn(Cl1-xBrx)3 mixed-halide perovskites by solid-state NMRT12-Z01, T12-Q01 University of Alberta | Publication | 2021-01-01 | | | Comparison of computational and experimental inorganic crystal structuresThis paper tackles one of the most compelling problems in materials discovery: Density functional theory calculations rely on crystal structures to predict properties, but how accurate are the structural parameters? This study is the first to evaluate the accuracy for >10,000 crystal structures of inorganic compounds reported both computationally and experimentally, to gauge their internal consistency. Within a day of the paper being published, I received this unsolicited message from a materials scientist: “These results will be fundamentally valuable for our computational materials design community!”T12-P01 University of Alberta | Publication | 2020-07-19 | Jan Poehls, Manon Heyberger, Mar, A. | | Half-Heusler Structures with Full-Heusler Counterparts: Machine-Learning Predictions and Experimental ValidationIn this manuscript, we present a machine-learning approach to confront a significant problem in the crystal chemistry of half-Heusler compounds, which belong to the larger family of Heusler compounds and which have important applications as thermoelectric and spintronic materials. In particular, we wish to identify new half-Heusler compounds that have existing full-Heusler counterparts, because the occurrence of such pairs enables thermoelectric and magnetic properties to be controlled and improved. What distinguishes our contribution from the majority of machine-learning studies targeted to discovering new materials is that the predictions made in our investigation are supported by experimental verification.T12-P01, T12-Z01 University of Alberta | Publication | 2020-09-01 | | | Coloured intermetallic compounds LiCu2Al and LiCu2GaThis paper describes the search for coloured metallic substances, which are very rare (in contrast to coloured semiconductors or insulators, which are typically compounds with significant ionic character, such as halides and oxides). T12-P01 University of Alberta | Publication | 2020-09-02 | Vidyanshu Mishra, Abishek K Iyer, Dundappa Mumbaraddi, Anton Oliynyk, "Guillaume Zuber ", "Aurélien Boucheron ", "Grygoriy Dmytriv ", Guy Bernard, Michaelis, V., Mar, A. | | Experimental validation of high thermoelectric performance in RECuZnP2 predicted by high-throughput DFT calculationsThis investigation of RECuZnP2 (RE = rare earth) is the first in-depth study of transport properties in quaternary CaAl2Si2-type compounds, a promising class of thermoelectric materials. The new concept demonstrated is the combined application of DFT calculations with advanced physics-based scattering calculations to gain insight on the underlying mechanisms of thermoelectric properties. In contrast to existing research, which is impeded by restrictions of conventional DFT methods, our approach accurately models thermoelectric properties of complex materials exhibiting disorder, a pervasive feature of real materials. The results directly challenge the usual assumption that acoustic phonon scattering is the limiting factor of electron transport in most thermoelectric materials; instead, polar optical phonon scattering is likely more important than previously believed. Moreover, the calculations shed light on the unexpectedly low lattice thermal conductivity in RECuZnP2: despite high bulk moduli and speeds of sounds, strongly anharmonic bonding can significantly reduce the thermal conductivity. These insights on the mechanisms of electron and heat transport have broader implications to the materials science community, by guiding researchers to discover more efficient thermoelectric materials in applying new concepts to optimize their properties. The low computational cost of these methods could also herald an exciting era of DFT-guided materials discovery.T12-P01, T12-Z01 University of Alberta | Publication | 2020-11-04 | Jan Poehls, "Sevan Chanakian ", "Junsoo Park ", Alex M Ganose, "Alexander Dunn ", Nick Friesen, Amit Bhattacharya, "Brea Hogan ", "Sabah Bux ", "Anubhav Jain ", Mar, A., "Alexandra Zevalkink " | | Revealing the Local Sn and Pb Arrangements in CsSnxPb1–xBr3 Perovskites with Solid-State NMR SpectroscopyT12-Z01 University of Alberta | Publication | 2021-01-25 | | | Rare-earth indium selenides RE3InSe6 (RE = La-Nd, Sm, Gd, Tb): Structural evolution from tetrahedral to octahedral sitesThis manuscript presents a detailed analysis of a series of ternary rare-earth selenides RE3InSe6 revealing new insight on a previously unrecognized structural feature, in which substitution with smaller RE atoms is accompanied by a gradual change in the coordination of In atoms within a linear stack from tetrahedral to octahedral geometry. Importantly, this analysis draws a connection between the various series RE3MCh6 (M = Ga, In; Ch = S, Se) indicating that there is a continuum from noncentrosymmetric to centrosymmetric structures, and suggests that these other series need to be reexamined with a more critical eye. Optical measurements show direct band gaps (1.2-1.4 eV) that match closely with those desirable for solar cells, and thus these compounds may be attractive as photovoltaic materials. We hope that the results will interest structural chemists investigating chalcogenides as well as materials scientists looking for promising new candidates.T12-P01 University of Alberta | Publication | 2021-02-27 | Vidyanshu Mishra, Dundappa Mumbaraddi, Abishek K Iyer, Mar, A. | | Machine learning in solid-state chemistry: Heusler compoundsT12-P01, T12-Z01 University of Alberta | Publication | 2021-04-27 | | | Accelerating the Discovery of Solid State MaterialsAs part of a satellite meeting to the North American Solid State Chemistry Conference (Colorado School of Mines, Golden, CO), I was one of the instructors in an intensive weekend workshop entitled "Introduction to Machine Learning for Solid State Chemistry: A Practical Workshop" held on July 29-30, 2019. The audience consisted of active researchers in the solid state chemistry community wishing to apply machine learning to their own work. I discussed practical examples of machine learning.T12-P01 University of Alberta | Activity | 2019-07-29 | | | USchool: Materials and InformaticsIn continuation of our commitment to this program, run by the University of Alberta Senate "to introduce and connect students in Grades 4 to 9 from socially vulnerable communities," my research group led a morning class on March 11, 2020 (two days before the university restricted in-person activities) to grade 5 students from St. Anne School to teach them about "Materials and Informatics." Two of my researchers and myself presented demonstrations about materials science (superconductivity, thermoelectrics) and informatics (Google Quick Draw). A second event scheduled for "Energy Week" on May 6, 2020 was cancelled.T12-P01 University of Alberta | Activity | 2020-03-11 | Dundappa Mumbaraddi, Hussien Osman, Mar, A. | | Accelerating the Discovery of Solid State MaterialsThe event was the annual meeting of the ATUMS CREATE program (between U of A and Technical University of Munich), and the focus is on student presentations. However, this year, short presentations were given by faculty members.T12-P01 University of Alberta | Activity | 2019-11-11 | | | Solving the Colouring Problem in Half- Heusler Structures: Machine-Learning Predictions and Experimental ValidationPoster presentation at the North American Solid State Chemistry Conference.T12-P01 University of Alberta | Activity | 2019-07-31 | Alex Gzyl, Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Machine-Learning Predictions and Experimental Validation of Heusler StructuresVirtual invited seminar at the University of Guelph.T12-P01 University of Alberta | Activity | 2020-11-25 | | | Machine-Learning Predictions and Experimental Validation of Full and Half-Heusler StructuresThe American Chemical Society Division of Inorganic Chemistry (DIC) is organizing monthly, Zoom-based symposia covering each subdivisions. The format is 2 speakers for 20 minute talks each, with each talk followed by 10 min Q&A. One will be 20-minute emerging faculty lecture (assistant professors), and the other a 20-minute established faculty lecture.T12-P01 University of Alberta | Activity | 2020-11-18 | | | Machine-Learning Predictions and Experimental Validation of Full and Half-Heusler StructuresInvited virtual departmental colloquium at University of SaskatchewanT12-P01 University of Alberta | Activity | 2020-10-30 | | | Experimental Validation of High Thermoelectric Performance in RECuZnP2 Predicted by High-Throughput DFT CalculationsOral presentation given by Jan Poehls at the Virtual Conference on Thermoelectrics 2020T12-P01, T12-Z01 University of Alberta | Activity | 2020-07-21 | Jan Poehls, "Sevan Chanakian ", "Junsoo Park ", "Alex Ganose ", "Alex Dunn ", Nick Friesen, Amit Bhattacharya, "Anubhav Jain ", "Alexandra Zevalkink ", Mar, A. | | Machine-learning predictions and experimental validation of full- and half-Heusler structuresInvited presentation at the Solid Compounds of Transition Elements Conference, held virtually at Wrocław, Poland.T12-P01 University of Alberta | Activity | 2021-04-12 | | | Minority report: Structure and bonding of YbNi3Ga9 and YbCu3Ga8 obtained in gallium fluxThis manuscript presents a detailed investigation of two ternary gallides, YbNi3Ga9 and YbCu3Ga8. To contend with difficulties in preparing Yb-containing intermetallics through conventional routes, gallium flux reactions were performed. Although flux methods are well known, predicting their outcomes is not obvious, and we test a previously proposed stability diagram for determining whether crystals of ternary intermetallics are likely to be obtained. YbNi3Ga9 has been recently identified as an intermediate valence compound but its structure was not clear. Here, we have finally succeeded in performing a structure determination of YbNi3Ga9, which suffers from severe twinning problems. YbCu3Ga8 is a new, apparently metastable, ternary phase in the Yb-Cu-Ga, in which many other Ga-rich phases are known. By applying the concept of “crystal orbital bond index,” developed recently by Dronskowski, we provide evidence for multicentre bonding containing significant covalent character within the anionic Ga networks in these compounds, confirming assertions of electron transfer that have often been proposed, but rarely confirmed, for such gallides.T12-P01 University of Alberta | Publication | 2022-04-20 | Dundappa Mumbaraddi, Vidyanshu Mishra, "Sven Lidin ", Mar, A. | | Semiconducting Sm3GaSe5O with trigonal bipyramidal GaSe5 unitsThis manuscript presents the new oxyselenide, Sm3GaSe5O, obtained after longstanding efforts to prepare mixed-anion compounds, which offer the promise of greater tunability of physical properties. The results are remarkable in several respects. First, the structure type is new and features unprecedented trigonal bipyramidal GaSe5 units (CN5), in contrast to the more typical tetrahedral GaSe4 units (CN4) found in known Ga-containing selenides. To our knowledge, this is the first observation of five-coordinate Ga surrounded by Se atoms; for comparison, even GaO5 units are quite rare. Second, statements often made in the literature that oxychalcogenides can be partitioned into “more ionic” oxide and “more covalent” chalcogenide blocks, but these claims have rarely been evaluated. By analyzing electron localization function (ELF) plots, we have obtained evidence that agrees surprisingly well with this assertion. Third, although most oxychalcogenides have relatively large band gaps (typically >2 eV), Sm3GaSe5O has a nearly direct band gap of 1.2 eV, similar to that of silicon. Thus, this compound may be a good candidate as an optical material.T12-P01 University of Alberta | Publication | 2022-01-13 | Vidyanshu Mishra, Dundappa Mumbaraddi, Abishek K Iyer, "Wenlong Yin ", Mar, A. | | Coloured intermetallic compounds Li2ZnGa and Li2ZnInThis manuscript describes continuing efforts in our research group to identify new coloured intermetallics, which remaining exceedingly rare (perhaps ~102, or <1% of known intermetallic compounds) and largely limited to combinations with very expensive precious metals (e.g., Au, Pt). The origin for the appearance of colour in these compounds differs from the more familiar cases of inorganic semiconductors or insulators because there are no band gaps, charge transfer, or d-d/f-f transitions. The combination of colour and metallic lustre makes these compounds particularly attractive as decorative coatings and jewellery; more ambitiously, they may prove to be possible candidates for plasmonic materials. Our hypothesis is that Li-containing intermetallics synthesized with less expensive elements (e.g., Cu, Zn) would possess similar crystal and electronic structures as the previously known analogues, and thus be fruitful targets for new, more accessible coloured intermetallics. We report here the two new coloured intermetallics Li2ZnGa and Li2ZnIn, determine their crystal structures by powder X-ray diffraction methods, confirm the location of Li atoms (difficult to detect by XRD) through solid state 7Li NMR spectroscopy, quantitatively characterize the colour through optical reflectance measurements and extraction of CIE colour coordinates, and perform electronic structure calculations.T12-P01 University of Alberta | Publication | 2021-11-30 | Mohammad Jomaa, Vidyanshu Mishra, Dundappa Mumbaraddi, Madhu Sudan Chaudhary, "Grygoriy Dmytriv ", Michaelis, V., Mar, A. | | Ternary rare-earth-metal nickel indides RE23Ni7In4 (RE = Gd, Tb, Dy) with Yb23Cu7Mg4-type structureT12-P01 University of Alberta | Publication | 2021-11-21 | Yurij B Tyvanchuk, "Matthew Fecica ", "Griheydi Garcia ", Mar, A., Anton Oliynyk | | Lost horses on the frontier: K2BiCl5 and K3Bi2Br9This manuscript addresses the absence of some members of the defect perovskite halides A3Bi2X9, of which the most well known are the iodides, especially Cs3Bi2I9, which have been identified as promising candidates for lead-free alternatives to the halide semiconductors APbX3 for photovoltaic materials. In particular, among the bromides, A3Bi2Br9 is known for A = Rb, Cs, Tl, but not K, and among the chlorides, A3Bi2Cl9 is known only for A = Cs. It is curious that there remain such missing members despite the enormous effort of numerous research groups embarked on the investigation of these compounds. Have these missing members simply been lost, or have they been neglected because their expected band gaps may have been assumed to be unsuitably large? In this study, we present the attempted preparation of K3Bi2Cl9 and K3Bi2Br9. Although we failed to prepare K3Bi2Cl9, obtaining K2BiCl5 instead, we confirmed the existence of K3Bi2Br9. The most significant result is that the measured band gap of K3Bi2Br9 is 2.2 eV, not that much different from those of the iodides (1.92.1 eV) and contradicting various predictions of a much larger band gap. T12-P01 University of Alberta | Publication | 2021-09-28 | "Yuqiao Zhou ", "Yu Qiu ", Vidyanshu Mishra, Mar, A. | | Three Rh-rich ternary germanides in the Ce-Rh-Ge systemThis manuscript presents a lengthy analysis of the Rh-rich region of the Ce-Rh-Ge phase diagram, culminating in the discovery and detailed structural characterization of three new ternary germanides: Ce3Rh11Ge5, Ce6Rh30Ge19.5, and CeRh3Ge2. Each of these compounds would have been worthy of separate papers, but we have opted to combine these results to achieve a unified presentation. For context, ternary Ce-Rh-Ge phases have been a particularly rich source of exotic physical phenomena (e.g., heavy fermion behaviour, superconductivity, valence fluctuations), so the identification of new phases in this system opens up even more opportunities to uncover unusual properties in these materials. Early efforts were made nearly 30 years ago to investigate the Ce-Rh-Ge phase diagram systematically, but about half of the 20 claimed ternary phases have never been properly characterized. Two of the compounds we have prepared are probably unrelated to these previously claimed phases, indicating that the Ce-Rh-Ge system is much more complicated than originally imagined. The structure determinations of these compounds were not trivial, and we have expended significant effort to describe these structures in relation to known types, including developing group-subgroup relationships. Finally, we have carried out a bonding analysis using electron localization functions (ELF) to demonstrate that charge transfer occurs from Ce atoms, not to Ge but rather to Rh atoms, indicating the presence of negatively charged Rh species in these polar intermetallic compounds. T12-P01 University of Alberta | Publication | 2021-09-11 | | | Mere anarchy is loosed: Structural disorder in Cu2Zn1-xCdxSnS4T12-P01 University of Alberta | Publication | 2021-06-03 | | | Classification of crystal structures: Machine-learning predictions and experimental validationThis was an invited presentation to a workshop organized by the Centre for Nonlinear Studies, Los Alamos National Laboratory, on machine learning. Attendance was highly selective (only invited speakers).T12-P01 University of Alberta | Activity | 2021-05-13 | | | Predicting noncentrosymmetric quaternary tellurides using machine learningT12-P01 University of Alberta | Activity | 2021-07-28 | Balaranjan Selvaratnam, Anton Oliynyk, Lawrence Adutwum, Mar, A. | | Rare-earth transition-metal oxychalcogenidesT12-P01, T12-Z01 University of Alberta | Activity | 2021-07-28 | Vidyanshu Mishra, Dundappa Mumbaraddi, Abishek K Iyer, Mar, A. | | Ternary phases in the Yb-Cu-Ga and Yb-Ni-Ga systemsT12-P01 University of Alberta | Activity | 2021-07-28 | Dundappa Mumbaraddi, Vidyanshu Mishra, Anton Oliynyk, Mar, A. | | Investigation of Li-Zn-X (X = Ga, In) coloured intermetallicsT12-P01, T12-Z01 University of Alberta | Activity | 2021-07-28 | Mohammad Jomaa, Vidyanshu Mishra, Dundappa Mumbaraddi, Madhu Sudan Chaudhary, Michaelis, V., Mar, A. | | Comparison of computational and experimental inorganic crystal structuresT12-P01 University of Alberta | Activity | 2021-07-28 | Jan Poehls, Manon Heyberger, Mar, A. | | Symmetry in art and chemistry; machine learningThis was a 1-hour class for the Edmonton Lifelong Learners Association as part of a series on Modern Aspects of Chemistry. T12-P01 University of Alberta | Activity | 2022-02-17 | | | True colours shining through: Determining site distributions in coloured Li-containing quaternary Heusler compoundsT12-P01 University of Alberta | Publication | 2022-06-28 | Mohammad Jomaa, Vidyanshu Mishra, Madhu Sudan Chaudhary, Dundappa Mumbaraddi, Michaelis, V., Mar, A. | | La4Ga2Se6O3: A rare-earth oxyselenide built from one-dimensional stripsT12-P01 University of Alberta | Publication | 2022-07-25 | Vidyanshu Mishra, Alexander Zabolotnii, Mar, A. | | Mercurial possibilities: determining site distributions in Cu2HgSnS4 using 63/65Cu, 119Sn, and 199Hg solid-state NMR spectroscopyT12-P01, T12-P02 University of Alberta | Publication | 2022-09-21 | | | The centre cannot holdT12-P01 University of Alberta | Publication | 2022-09-13 | | | Revealing hidden patterns through chemical intuition and interpretable machine learning: A case study of binary rare-earth intermetallics RXT12-P01 University of Alberta | Publication | 2023-01-30 | Volodymyr Gvozdetskyi, Balaranjan Selvaratnam, Anton Oliynyk, Mar, A. | | Effect of aliovalent bismuth substitution on structure and optical properties of CsSnBr3T12-P01, T12-P02 University of Alberta | Publication | 2023-04-19 | Madhu Sudan Chaudhary, Abhoy Karmakar, Vidyanshu Mishra, Amit Bhattacharya, Dundappa Mumbaraddi, Mar, A., Michaelis, V. | | Coloured Li-containing intermetallic compoundsT12-P01 University of Alberta | Activity | 2022-06-16 | | | Mechanochemical processing of W-substituted solid-state electrolytes and its effects on electrochemical performance and crystal structure T12-P01, T06-Q02 University of Alberta | Activity | 2022-06-16 | | | Explainable machine learning in materials chemistry: Decision trees as scoring functionT12-P01 University of Alberta | Activity | 2022-06-16 | | | Predicting thermoelectric figures-of-merit for half-Heusler compounds using machine learningT12-P01 University of Alberta | Activity | 2022-06-16 | Balaranjan Selvaratnam, Volodymyr Gvozdetskyi, Mar, A. | | Rare-earth transition-metal oxyselenidesT12-P01 University of Alberta | Activity | 2022-06-16 | | | Cerium-containing chalcohalides as tunable photoluminescent materialsT12-P01 University of Alberta | Activity | 2022-06-16 | Dundappa Mumbaraddi, Vidyanshu Mishra, Mohammad Jomaa, Abhoy Karmakar, Andrew P Grosvenor, Michaelis, V., Al Meldrum, Mar, A. | | Investigating ordering in chalcogenide solid electrolytes using solid-state NMR spectroscopyT12-P01 University of Alberta | Activity | 2022-06-15 | | | Searching for new spinels using machine learningT12-P01 University of Alberta | Activity | 2022-06-17 | Vidyanshu Mishra, Balaranjan Selvaratnam, Mar, A. | | NSERC discovery grant roundtableT12-P01 University of Alberta | Activity | 2022-07-04 | | | Solid state chemistry - Influence of structure and form on propertiesT12-P01 University of Alberta | Activity | 2022-06-17 | | | Gordon Research Conference in Solid State ChemistryT12-P01 University of Alberta | Activity | 2022-07-24 | | | Revealing hidden patterns through chemical intuition and interpretable machine learning: A case study of binary rare-earth intermetallics RXT12-P01 University of Alberta | Activity | 2022-07-27 | Volodymyr Gvozdetskyi, Balaranjan Selvaratnam, Anton Oliynyk, Mar, A. | | Searching for new spinels using machine learningT12-P01 University of Alberta | Activity | 2022-07-27 | Vidyanshu Mishra, Balaranjan Selvaratnam, Mar, A. | | Luminescence properties of rare-earth chalcohalides RE3Ge2-xSixS8I (RE = La, Ce, Pr) and Ce3Si2S8-ySeyI for potential application in phosphor-converted white LEDsT12-P01 University of Alberta | Activity | 2022-07-27 | Dundappa Mumbaraddi, Vidyanshu Mishra, Mohammad Jomaa, Xiaoyuan Liu, Abhoy Karmakar, "Sambhavi Thirupurasanthiran ", Al Meldrum, Andrew P Grosvenor, Michaelis, V., Mar, A. | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2022-08-24 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2022-08-25 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2022-08-26 | | | New quaternary metallic phosphidesT12-P01 University of Alberta | Activity | 2022-11-08 | | | The effect of electrolyte structure, ion conductivity, and decomposition due to mechanochemical processingT12-P01, T06-Q02 University of Alberta | Activity | 2022-11-08 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2022-11-21 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2023-02-17 | | | Interpretable machine learning in solid state chemistry, with applications to perovskites, spinels, and rare-earth intermetallics: Finding descriptors using decision treesT12-P01 University of Alberta | Publication | 2023-06-30 | Balaranjan Selvaratnam, Anton Oliynyk, Mar, A. | | Controlling the luminescence of rare-earth chalcogenide iodides RE3(Ge1–xSix)2S8I (RE = La, Ce, and Pr) and Ce3Si2(S1–ySey)8IT12-P01 University of Alberta | Publication | 2023-07-18 | Dundappa Mumbaraddi, Vidyanshu Mishra, Mohammad Jomaa, Xiaoyuan Liu, Abhoy Karmakar, "Sambhavi Thirupurasanthiran ", Michaelis, V., Andrew P Grosvenor, Al Meldrum, Mar, A. | | Mechanochemistry in sodium thioantimonate solid electrolytes: Effects on structure, morphology, and electrochemical performanceT12-P01 University of Alberta | Publication | 2023-08-09 | Fuwei Wen, Xie, G., "Ning Chen ", Qichao Wu, Madhu Sudan Chaudhary, Xiang You, Michaelis, V., Mar, A., Sang, L. | | Drop that activation energy: Tetragonal to cubic transformations in Na3PS4−xSex for solid state sodium ion battery materialsT12-P01 University of Alberta | Publication | 2023-12-14 | Madhu Sudan Chaudhary, Arkadii Pominov, Dundappa Mumbaraddi, "Bryce Allen ", "Jan Meyer ", Anna Maria Kirchberger, Guy Bernard, "Tom Nilges ", Mar, A., Michaelis, V. | | Quaternary rare-earth oxyselenides RE4Ga2Se7O2 (RE = Pr, Nd) with trigonal bipyramidal GaSe5 units: Evaluation of optical, thermoelectric, and electrocatalytic propertiesT12-P01 University of Alberta | Publication | 2024-01-02 | Vidyanshu Mishra, Ibrahim Munkaila Abdullahi, Dundappa Mumbaraddi, Mohammad Jomaa, Louis Guérin, "Manashi Nath ", Mar, A. | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2023-07-07 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2023-07-10 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2023-07-08 | | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2023-06-07 | Volodymyr Gvozdetskyi, Balaranjan Selvaratnam, Anton Oliynyk, Mar, A. | | Revisiting the classification of spinels through machine learningT12-P01 University of Alberta | Activity | 2023-06-06 | Vidyanshu Mishra, Balaranjan Selvaratnam, Mar, A. | | Controlling the luminescence of rare-earth chalcohalides Ce3Ge2–xSixS8I and Ce3Si2S8–ySeyIT12-P01 University of Alberta | Activity | 2023-06-06 | Dundappa Mumbaraddi, Vidyanshu Mishra, Mohammad Jomaa, Xiaoyuan Liu, Abhoy Karmakar, "Sambhavi Thirupurasanthiran ", Al Meldrum, Andrew P Grosvenor, Michaelis, V., Mar, A. | | Rare earth gallium oxyselenides with unprecedented GaSe5 units as potential optical and thermoelectric materialsT12-P01 University of Alberta | Activity | 2023-06-07 | Vidyanshu Mishra, Dundappa Mumbaraddi, Mohammad Jomaa, Abishek K Iyer, "Wenlong Yin ", Mar, A. | | Quaternary rare-earth transition-metal phosphides RE5M3Ni16P12 (M = Zr, Hf)T12-P01 University of Alberta | Activity | 2023-06-08 | | | Materials and informaticsT12-P01 University of Alberta | Activity | 2023-01-09 | | | Some concepts in machine learning, with applications to materials discoveryT12-P01 University of Alberta | Activity | 2023-07-31 | | | Machine learning in solid state chemistry: A workshop for the rest of usAnton and I organized a two-day workshop on machine learning for solid state chemistry, as a satellite meeting to the North American Solid State Chemistry Conference.T12-P01 University of Alberta | Activity | 2023-07-31 | | | Can we use machine learning to find synthesizable compounds?T12-P01 University of Alberta | Activity | 2023-08-04 | Balaranjan Selvaratnam, Vidyanshu Mishra, Dundappa Mumbaraddi, "Maxwell Wallace ", Arkadii Pominov, Mar, A. | | Session chair at North American Solid State Chemistry ConferenceT12-P01 University of Alberta | Activity | 2023-08-02 | | | Discovery of Li-containing compounds with channel structures guided by machine learningT12-P01 University of Alberta | Activity | 2023-08-01 | Volodymyr Gvozdetskyi, Mohammad Jomaa, Balaranjan Selvaratnam, Mar, A. | | Bridging chemistry from high school to universityT12-P01 University of Alberta | Activity | 2024-01-25 | | | Bridging chemistry from high school to universityT12-P01 University of Alberta | Activity | 2024-02-15 | | | Bridging chemistry from high school to university: A Canadian perspectiveT12-P01 University of Alberta | Activity | 2024-03-22 | | | Materials discovery of intermetallics through machine learning: Experimental validation and interpretable modelsT12-P01 University of Alberta | Activity | 2023-09-25 | Volodymyr Gvozdetskyi, Balaranjan Selvaratnam, Anton Oliynyk, Mar, A. | | Discovery of ternary antimonides A–Al–Sb (A = Rb or Cs) with desired structural motifs guided by machine learningEditor's Choice. Special issue in memory of Frank DiSalvo.T12-P01 University of Alberta | Publication | 2024-06-09 | "Bryan Owens-Baird ", Volodymyr Gvozdetskyi, "Arka Sarkar ", Balaranjan Selvaratnam, Mar, A., "Kirill Kovnir " | | In search of coloured alloys resembling gold: Structure and optical properties of LiCu2Ga1−xAlx and Li(Cu1–yNiy)2GaT12-P01 University of Alberta | Publication | 2024-07-20 | "Mohammed Jomaa ", Dundappa Mumbaraddi, Vidyanshu Mishra, Madhu Sudan Chaudhary, "Brenton Mah ", Diane Delaruelle, Michaelis, V., Mar, A. | | How to separate two Ts in a pod: Classifying T- and T′-type Ruddlesden-Popper cuprates by machine learningT12-P01 University of Alberta | Publication | 2025-02-07 | Dmitry Vrublevskiy, "Loic Robert ", Balaranjan Selvaratnam, Mar, A. | | USchool: Materials and informatics: What are things made of? How do we discover them?Together with 3 of my research students, I led a one-hour class to Grade 5 students from John
A. McDougall School, as part of "U School," a program run by the University of Alberta Senate to introduce and connect grade school students from vulnerable communities. We gave lessons and demonstrations about "Materials and Informatics" to introduce these students to materials science and machine learning.T12-P01 University of Alberta | Activity | 2024-05-03 | Mar, A., Vidyanshu Mishra, "Pritam Das ", Qichao Wu | | USchool: Materials and informatics: What are things made of? How do we discover them?Together with 3 of my research students (Vidyanshu Mishra, Pritam Das, Qichao Wu), I led a one-hour class each to Grade 5 students from Katherine Therrien School, as part of "U School," a program run by the University of Alberta Senate to introduce and connect grade school students from vulnerable communities. We gave lessons and demonstrations about "Materials and Informatics" to introduce these students to materials science and machine learning.T12-P01 University of Alberta | Activity | 2024-05-06 | Mar, A., Vidyanshu Mishra, "Pritam Das ", Qichao Wu | | Discovery of inorganic solids guided by machine learningT12-P01 University of Alberta | Activity | 2024-05-21 | | | What is a lattice?T12-P01 University of Alberta | Activity | 2024-06-04 | | | Phase transformations in lithium-containing chalcogenidesT12-P01 University of Alberta | Activity | 2024-06-04 | "Pritam Das ", Dundappa Mumbaraddi, Vidyanshu Mishra, "Diganta Sarkar ", "Mohammed Jomaa ", Michaelis, V., Mar, A. | | Noncentrosymmetric rare-earth chalcogenides RE3M1.67Ch7 (M = Ga, In; Ch = S, Se) as potential nonlinear optical materialsT12-P01 University of Alberta | Activity | 2024-06-03 | Qichao Wu, "Pritam Das ", Vidyanshu Mishra, Mar, A. | | Discovery of inorganic solids guided by machine learningT12-P01 University of Alberta | Activity | 2024-11-15 | | | Discovery of inorganic solids with desired structure motifs guided by machine learningT12-P01 University of Alberta | Activity | 2024-07-24 | "Bryan Owens-Baird ", Volodymyr Gvozdetskyi, "Arka Sarkar ", Balaranjan Selvaratnam, Mar, A., "Kirill Kovnir " | | New rare-earth gallium oxyselenides as potential electrocatalytic and thermoelectric materialsT12-P01 University of Alberta | Activity | 2024-07-24 | Vidyanshu Mishra, "Ibrahim Abdullahi ", Dundappa Mumbaraddi, "Mohammed Jomaa ", Louis Guérin, "Manashi Nath ", Mar, A. | | Discovery of inorganic solids guided by machine learningT12-P01 University of Alberta | Activity | 2024-06-19 | | | Public speaking and performance techniques for teaching chemistryI organized a teaching workshop, enlisting the aid of drama instructors to train instructors (including graduate teaching assistants) to apply drama and improvisational techniques for communicating science to diverse learners.T12-P01 University of Alberta | Activity | 2024-05-24 | |
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