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Dadmun Published in Chemical Reviews

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Deep eutectic solvents (DESs) are an emerging class of mixtures characterized by significant depressions in melting points compared to those of the neat constituent components. These materials are promising for applications as inexpensive “designer” solvents exhibiting a host of tunable physicochemical properties.

Mark Dadmun, professor and ORNL-UT joint faculty member, contributed to this collaborative piece “Deep Eutectic Solvents: A Review of Fundamentals and Applications” in Chemical Reviews.

A detailed review of the current literature reveals the lack of predictive understanding of the microscopic mechanisms that govern the structure–property relationships in this class of solvents. Complex hydrogen bonding is postulated as the root cause of their melting point depressions and physicochemical properties; to understand these hydrogen bonded networks, it is imperative to study these systems as dynamic entities using both simulations and experiments.

This review emphasizes recent research efforts in order to elucidate the next steps needed to develop a fundamental framework needed for a deeper understanding of DESs. It covers recent developments in DES research, frames outstanding scientific questions, and identifies promising research thrusts aligned with the advancement of the field toward predictive models and fundamental understanding of these solvents.

Vogiatzis Wins OpenEye Outstanding Junior Faculty Award

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Kostas Vogiatzis, assistant professor with the Department of Chemistry, is one of the recipients of the American Chemical Society, Computers in Chemistry Division (ACS COMP) OpenEye Outstanding Junior Faculty Award for Spring 2021.

This competitive and prestigious award identifies junior faculty of promise in the area of computational chemistry and modeling. Vogiatzis will present his research in the upcoming (online) National Meeting of the American Chemical Society. The title of his talk is “Data-driven Computational Chemistry for Noncovalent Interactions of CO2”.

For more information about the award visit https://www.acscomp.org/awards/the-comp-acs-outstanding-junior-faculty-award.

For more information about Dr. Vogiatzis’ research visit https://vogiatzis.utk.edu.

Zhao Receives Excellence in Research Award

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Each year, Dean Theresa Lee and members of her cabinet, with help from department heads, recognize faculty in the College of Arts and Sciences for their excellence in teaching, research and creative activity, and lifetime achievements.

Due to the ongoing pandemic, however, we were unable to host the annual awards banquet in-person. Each faculty member received a plaque and congratulations from the dean. We posted a video to the college YouTube channel here, which features each faculty award winner.

We seek to recognize faculty members who excel in scholarship and creative activity while also being fully engaged in the other responsibilities of faculty jobs, primarily teaching and service. To this end, the college honors faculty in three stages of their research careers – early, mid, and senior – with awards for excellence in research or creative achievement, as well as honoring a faculty with an award for Distinguished Research Career at UT.

Bin ZhaoBin Zhao is the Paul and Wilma Ziegler Professor in the Department of Chemistry, received a senior career excellence in research award. He has made significant contributions to the field of macromolecular brush materials, from precise synthesis to fundamental understanding and potential applications of surface brushes, polymer brush-grafted particles (hairy particles), and brush polymers. He is widely recognized, nationally and internationally, as one of the leading figures in this field. His work on stimuli-responsive polymers has also received wide attention. Zhao is a dedicated research mentor who seeks to use research opportunities to cultivate scientific reasoning and spirit in his graduate and undergraduate students.

“I am very excited to receive this great honor and recognition from our college” Zhao said. “I look forward to continuing contributing to the research mission of our university in the years ahead.”

Musfeldt Group Published in Nano Letters

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The Musfeldt Group published their work “Excitations of Intercalated Metal Monolayers in Transition Metal Dichalcogenides” in Nano Letters.

They combine Raman scattering spectroscopy and lattice dynamics calculations to reveal the fundamental excitations of the intercalated metal monolayers in the FexTaS2 (x = 1/4, 1/3) family of materials. Both in- and out-of-plane modes are identified, each of which has trends that depend upon the metal–metal distance, the size of the van der Waals gap, and the metal-to-chalcogenide slab mass ratio.

They test these trends against the response of similar systems, including Cr-intercalated NbS2 and RbFe(SO4)2, and demonstrate that the metal monolayer excitations are both coherent and tunable.

They discuss the consequences of intercalated metal monolayer excitations for material properties and developing applications.

Computational Chemistry and Machine Learning in the Vogiatzis Group

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Research in the Vogiatzis Group centers on the development of computational methods based on electronic structure theory and machine learning algorithms for describing chemical systems relevant to clean, green technologies.

“We are particularly interested in new methods for non-covalent interactions and bond-breaking reactions of small molecules with transition metals,” Vogiatzis said. “Our overall objectives are to elucidate the fundamental physical principles underlying the reactivity and properties of molecules and materials, as well as to assist in the interpretation of experimental data.”

In June 2020, the group was published in Nature Communications for their work “Representation of molecular structures with persistent homology for machine learning applications in chemistry.” This was a unique collaborative opportunity between chemistry department’s Jacob Townsend, graduate student, John Hymel, undergraduate student, Konstantinos Vogiatzis, assistant professor, along with Cassie Micucci and Vasileios Maroulas, Department of Mathematics. The group presents a novel molecular representation method based on persistent homology, an applied branch of topology, which encodes the atomistic structure of molecules.

They began their study by computing with density functional theory (DFT) the CO2 interaction energies of 100 organic molecules. “Since the initial, limited 100 data points were not capturing the diversity of the GDB-9 database, we applied a technique called active learning in order to incrementally obtain data which helped us efficiently screen the 133,885 molecules,” Vogiatzis said. “We found out that the combination of PIs with active learning performed well with data (interaction energies) from only 220 molecules in order to identify new molecules with stronger CO2 binding.”

Their data-driven methodology was able to identify molecular patterns previously unknown to us that increase the CO2 affinity of organic molecules.

The Vogiatzis Group broke a record with their work “Transferable MP2-Based Machine Learning for Accurate Coupled-Cluster Energies.” 

Machine learning methods have enabled the low-cost evaluation of molecular properties such as energy at an unprecedented scale. While many of such applications have focused on molecular input based on geometry, few studies consider representations based on the underlying electronic structure.

Directing the attention to the electronic structure offers a unique challenge that allows for a more detailed representation of the underlying physics and how they affect molecular properties. The target of this work is to efficiently encode a lower-cost correlated wave function derived from MP2 to predict a higher-cost coupled-cluster singles-and-doubles (CCSD) wave function based on correlation-pair energies and the contributing electron promotions (excitations) and integrals.

The new molecular representation explores the short-range behavior of electron correlation and utilizes distinct models that differentiate between two-electron promotions from the same molecular orbital or from two different orbitals. The group presents a re-engineered set of input features that provide an intuitive description of the orbital properties involved in electron correlation. The overall models are found to be highly transferable and size extensive, necessitating very few training instances to approach the chemical accuracy of a broad spectrum of organic molecules.

“Coupled-cluster theory is the level of theory that provides the most accurate quantum chemical results in a reasonable computational time. Typically, we need ~10 minutes for computing the energy of a small molecule with coupled-cluster and for a database with ~133,000 small molecules, we will need ~1,330,000 minutes or ~2.5 years of computations,” Vogiatzis said. “In this work, we demonstrated that we can use the results from only 100 coupled-cluster calculations for training a machine learning model that can predict, without loss of accuracy, the energy of the full 133,000 molecule database a few hours.”

 

 

 

Larese Group Featured Cover on J. Chem. Phys. C

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The Larese Group’s research Adsorption of Pentane and Hexane Thin Films on the Surface of Graphite(0001) was featured on the cover of The Journal of Physical Chemistry C.

Surface adsorption plays an important role in a variety of industrial and technological processes, especially in energy conversion, storage, and transformation. As a result, there is a growing need for advancing the current understanding of fundamental interactions that govern these types of processes. 

This research characterizes the interaction of n-pentane and n-hexane with graphite using high-resolution volumetric adsorption isotherms along with molecular dynamic simulations. The thermodynamics of adsorption were obtained for n-pentane and n-hexane adsorbed on the basal plane of graphite in the temperature ranges 190–235 and 230–280 K, respectively, using high-resolution volumetric adsorption isotherms. These linear molecules exhibit a van der Waals interaction with the surface of graphite(0001) and yield an overall greater binding than on boron nitride and MgO(100).

The averaged areas per molecule calculated for the fluid monolayer phases were determined to be 52.03 and 61.35 Å2 for pentane and hexane, respectively, which are in agreement with previous diffraction measurements performed for the monolayer solid. MD simulations were performed in order to provide additional microscopic insight.

Density profiles normal to the graphite substrate revealed that the stabilization of the layer nearest to the surface by the fluid multilayer exists for linear alkanes as small as pentane, however to a much lesser extent than that observed previously for adsorption on boron nitride and MgO. Intermolecular radial distribution functions and diffusion coefficients derived from the molecular trajectories suggest that a liquid crystal phase exists in the layer nearest the surface at temperatures well above the bulk triple-point temperatures.

Dai Group Published in ACS Energy Letters

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The Dai group published their research “Surpassing the Organic Cathode Performance for Lithium-Ion Batteries with Robust Fluorinated Covalent Quinazoline Networks” in  ACS Energy Letters.

Organic electrode materials have promising application prospects in energy storage, but issues including rapid capacity fading and poor power capacity restrict their practical applications. Herein, nanoporous fluorinated covalent quinazoline networks (F-CQNs) were constructed by condensation of fluorinated aromatic aminonitrile precursors via an ionothermal pathway.

Precise control of the reaction parameters afforded F-CQN-1-600 material featuring high surface area, permanent porosity, high nitrogen content (23.49 wt %), extended π-conjugated architecture, layered structure, and bipolar combination of benzene and tricycloquinazoline. Synergy among these unique properties leads to a good performance as a cathode source for lithium-ion batteries (LIBs) in terms of high capacity (250 mA h g–1 at 0.1 A g–1), high rate capability (105 mA h g–1 at 5.0 A g–1), and impressive cycling stability (95.8% retention rate after 2000 cycles at 2.0 A g–1 together with a high Coulombic efficiency of 99.95%), surpassing most of the previous organic cathode counterparts

Dai Published in Chem

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In a collaborative piece, UT Chemistry’s Sheng Dai and Pasquale Fulvio from Texas A&M’s Department of Nuclear Engineering published their work “Porous Liquids: The Next Frontier” in Chem.

Porous liquids are a new class of molecular- and colloidal-size porous materials that combine permanent porosity of solid sorbents and fluid properties of liquids. Different from transient molecular clathrates, porous liquids have the potential to reinvent materials syntheses and unify homogeneous and heterogeneous separations and catalytic and energy-related processes, previously ascribed to liquids and porous solids, respectively.

Surface areas and pore volumes of the first examples of porous liquids based on porous molecular organic cages restricted their potential for technological applications. Recent advances in ionic liquid-based colloidal suspensions or covalently stabilized nanocomposites have improved the adsorption properties and increased our ability to tailor chemical composition and pore architecture. These hybrid porous liquids, however, still present challenges such as high melting temperatures, density, and viscosity.

This critical review discusses these challenges and presents opportunities for selected emerging applications based on analogous structure to that of traditional colloidal systems.

Darko Lab Published in Dalton Transactions

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The Darko Lab published their work “Tuning Rh(ii)-catalysed cyclopropanation with tethered thioether ligands” in Dalton Transactions. 

Dirhodium(II) paddlewheel complexes have high utility in diazo-mediated cyclopropanation reactions and ethyl diazoacetate is one of the most commonly used diazo compounds in this reaction. In this study, the lab reports efforts to use tethered thioether ligands to tune the reactivity of RhII-carbene mediated cyclopropanation of olefins with ethyl diazoacetate.

Microwave methods enabled the synthesis of a family of RhII complexes in which tethered thioether moieties were coordinated to axial sites of the complex. Different tether lengths and thioether substituents were screened to optimise cyclopropane yields and minimise side product formation.

Good yields were obtained when equimolar diazo and olefin were used. Structural and spectroscopic investigation revealed that tethered thioethers changed the electronic structure of the rhodium core, which was instrumental in the performance of the catalysts. Computational modelling of the catalysts provided further support that the tethered thioethers were responsible for increased yields.