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Dai Group Published in Nano Energy and Chem. Commun.

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The Dai Group published their work “Room temperature synthesis of high-entropy Prussian blue analogues” in Nano Energy.

High-entropy Prussian blue analogues (HEPBAs) integrating the highly dispersed active sites of high-entropy materials with intrinsic 3D diffusion channels and the redox-active sites of Prussian blue analogues have great potential in electrochemical applications but have not been realized. In this work, a series of HEPBAs were successfully synthesized under room temperature combining mechanochemistry with wet chemistry for the first time.

High-entropy Prussian blue analogues (HEPBAs) were fabricated by combining mechanochemistry with wet chemistry. As an optimal element combination, high-entropy K(MgMnFeNiCu)Fe(CN)6 exhibited enhanced higher capacitances than all the single-component PBAs.

The group also published their work “Overcoming the phase separation within high-entropy metal carbide by poly(ionic liquid)s†” in Chemical Communications. 

High-entropy crystalline materials are attracting more attention. In principle, high-entropy metal carbides (HMCs) that contain five or more metal ions, possess more negative free energy value during catalysis. But its preparation is challenging because of the immiscibility of multi metal cations in a single carbide solid solution.

Here, a rational strategy for preparing HMC is proposed via a coordination-assisted crystallization process in the presence of Br-based poly(ionic liquids). Through this method, Mo0.2W0.2V0.2Cr0.2Nb0.2C nanoparticles, with a single cubic phase structure, incorporated on porous carbon, are obtained (HMC@NC). By combination of well dispersed small particle size (∼4 nm), high surface area (∼270 m2 g−1), and high-entropy phase, HMC@NC can function as a promising catalyst for the dehydrogenation of ethylbenzene. Unexpected activity (EB conv.: 73%) and thermal stability (>100 h on steam) at 450 °C are observed. Such a facile synthetic strategy may inspire the fabrication of other types of HMCs for more specific tasks.

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.

Nemykin Published in Angewandte Chemie-International Edition

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Viktor Nemykin was published in a collaborative piece “β-Isoindigo-azaDIPYs: Fully Conjugated Hybrid Systems with Broad Absorption in the Visible Region” in Angewandte Chemie-International Edition.

A one-step synthetic pathway for the preparation of fully conjugated β-isoindigo-azaDIPY hybrid chromophores comprised of β-isoindigo and azadipyrromethene moieties is reported. The target compounds were characterized by spectroscopic, crystallographic, and theoretical methods and show unprecedented broad absorption across the visible region of the electromagnetic spectrum. The X-ray crystal structure of the octa(n-butyl)-β-isoindigo-azaDIPY derivative revealed that a trans-configuration of the β-isoindigo fragment accompanies a planar conjugated core.

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.

Graduate Student Research Aids in Search for Extraterrestrial Life

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In 1996, NASA administrators made a historic announcement: proof that life had existed on Mars at some point in its history. Their proof was a Martian rock that they claimed contained the same combination of minerals and carbon compounds as those created by microbes on Earth. Searching for chemicals that indicate the presence of life is at the heart of the research being done by Grace Sarabia, a doctoral candidate in the Department of Chemistry.

Although most scientists now agree that the Martian rock presented in 1996 does not prove the existence of life on Mars, it could possibly point in that direction. Scientists have continued the search for extraterrestrial life through the Mars Rover program.

The Mars 2020 Perseverance Rover is scheduled to land this month, continuing the search for signs of ancient life. Perseverance will collect rock and soil samples that will help advance the understanding of Martian geologic history by identifying organic compounds and minerals that are indicative of past life on Mars.

In addition to geologic surveys, Perseverance is also testing technologies that could be used to identify potentially habitable extraterrestrial environments. Sarabia’s research centers on one such technology, called Raman spectroscopy, which provides a structural fingerprint to identify molecules. This non-destructive process examines how light is scattered from a sample when illuminated by a laser. Because the scatter is the result of chemical bonding and structure, it is unique to each compound—like a fingerprint is unique to each person.

In the laboratory, Sarabia attempts to mimic extraterrestrial environments, such as Martian soil or icy worlds like Europa, one of Jupiter’s 79 moons. Then, with the use of Raman spectroscopy, Sarabia is able to analyze these artificial environments to detect biosignatures—clues that indicate a planet’s atmosphere has been influenced by life. This research could not only provide insight into whether life has existed in the past, but also the potential for supporting life in the future.

Currently, her research provides her the opportunity to combine a lifelong curiosity about space with an inherited interest in chemistry. “My grandfather was a chemist, so he used to talk to me about different chemistry concepts when I was small,” Sarabia explains. “My mom used to tell him I didn’t understand him, so he should cut it out. It must have made an impact on me, however, because I did end up pursuing chemistry in college.”

Before coming to the University of Tennessee, Sarabia graduated from Berry College in Georgia, where she majored in Chemistry. Sarabia credits her career path to the terrific chemistry teachers she had there. “I attribute my interest in chemistry not only to my grandfather,” Sarabia said, “but also my terrific chemistry teachers, especially during my freshman year of college.”

Sarabia hopes that her research will assist the scientific community with analysis and, building upon the findings made during the Perseverance mission, possibly pave the way for future human expeditions to the red planet. Raman spectroscopy is just one of the technologies that Perseverance will test to determine the possibility of supporting human presence on Mars. Discoveries made on Mars could be applied to other planets and moons throughout the solar system.

Sarabia plans to continue her work in Raman spectroscopy, while also keeping her eyes on the stars. “Ideally, I would like to continue working with space-based research using Raman spectroscopy,” Sarabia explained. “It would be amazing to find life or signs of life beyond Earth. The implications for something like that would be major for everyone!”

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.

Bailey Lab Published in ChemBioChem

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The Bailey Lab also published “Site Directed Mutagenesis of Modular Polketide Synthase Ketoreductase Domains for Altered Stereochemical Control” in ChemBioChem.

Bacterial modular type I polyketide synthases (PKSs) are complex multidomain assembly line proteins that produce a range of pharmaceutically relevant molecules with a high degree of stereochemical control. Due to their colinear properties, they have been considerable targets for rational biosynthetic pathway engineering. Among the domains harbored within these complex assembly lines, ketoreductase (KR) domains have been extensively studied with the goal of altering their stereoselectivity by site-directed mutagenesis, as they confer much of the stereochemical complexity present in pharmaceutically active reduced polyketide scaffolds. Here we review all efforts to date to perform site-directed mutagenesis on PKS KRs, most of which have been done in the context of excised KR domains on model diffusible substrates such as beta-keto N-acetyl cysteamine thioesters. We also discuss the challenges around translating the findings of these studies to alter stereocontrol in the context of a complex multidomain enzymatic assembly line.

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.”