bluuebunny/crossref_metadata_2025 huggingface dataset:
OS100: A Benchmark Set of 100 Digitized UV-Visible Spectra and Derived Experimental Oscillator Strengths
Authors: Tarleton Astrid , Garcia-Alvarez Jorge , Wynn Anah , Awbrey Cade , Roberts Tomas , Gozem Samer
Published: February 2022

Excited-state quantum chemical calculations typically report excitation energies and oscillator strengths, ƒ, for each electronic transition. On the other hand, UV-visible spectrophotometric experiments report energy-dependent molar extinction/attenuation coefficients, ε(v), that determine the absorption band line shapes. ε(v) and ƒ are related, but this relation is complicated by various broadening and solvation effects. We fit and integrated experimental UV-visible spectra to obtain ƒexp values for absorption bands and estimated the uncertainty in the fitting. We derived 164 ƒexp values from 100 organic molecules ranging in size from 6-34 atoms. The corresponding computed oscillator strengths (ƒcomp) were obtained with time-dependent density functional theory and a polarizable continuum solvent model. By expressing experimental and computed absorption strengths using a common quantity, we directly compared ƒcomp and ƒexp. While ƒcomp and ƒexp are well correlated (linear regression R2=0. 921), ƒcomp in most cases significantly overestimates ƒexp (regression slope=1.34). The agreement between absolute ƒcomp and ƒexp values was substantially improved by accounting for a solvent refractive index factor, as suggested in some derivations in the literature. The 100 digitized UV-visible spectra are included as plain text files in the supporting information to aid in benchmarking computational or machine-learning approaches that aim to simulate realistic UV-visible absorption spectra.
Electrochemical Fluorination of Vinyl Boronates Through Donor-Stabilized Vinyl Carbocation Intermediates
Authors: Wigman Benjamin , Lee Woojin , Wei Wenjing , Houk Ken , Nelson Hosea
Published: February 2022

The electrochemical generation of vinyl carbocations from vinyl boronic esters and boronates is reported. Using easy-to-handle nucleophilic fluoride reagents, these intermediates are trapped to form fully substituted vinyl fluorides. Mech-anistic studies support the formation of dicoordinated car-bocations through sequential single-electron oxidation events. Notably, this electrochemical fluorination features fast reaction times and mild conditions. This transfor-mation provides a complementary method to access vinyl fluorides with simple fluoride salts such as TBAF.
Machine Learning based Framework for Quick Prediction of Tg and Td of OLED Materials
Authors: ZHAO YIHUAN , FU CAIXIA , FU Lin , LU Zhiyun , PU XUEMEI
Published: February 2022

Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, further development and commercialization of OLEDs requires higher-quality OLED materials, including high thermal stability associated with the glass transition temperature (Tg) and decomposition temperature (Td). Experimental determinations of the two important properties genernally involve a time-consuming and laborious process. Thus, it is highly desired to develop a quick and accurate prediction tool. Motivated by the changelle, we explored machine learning based framework by constructing new dataset with more than one thousand samples collected from a wide range of literaturesm, throngh which ensemble learning models were explored. Models trained with the LightGBM algorithm exhibit the best prediction performance, where the values of MAE, RMSE, and R2 are 17.15 K, 24.63 K, and 0.77 for Tg prediction, 24.91 K, 33.88 K, and 0.78 for Td prediction. The prediction performance and the generalization of the machine learning models are further tested by out-of-sample dataset, also exhibiting satisfactory results. Experimental verification further demonstrates the reliability and the practical potential of the ML-based model. In order to extend the practice application of the ML-based models, an online prediction platform was constructed, including the optimal predition models and all the thermal stability data under study, which are freely available at http://oledtppxmpugroup.com. We expect that they will become a useful tool for experimental investigations on Tg and Td, in turn accelerating the design of the OLED materials with high performance.
Data-driven machine learning models for the quick and accurate prediction of thermal stability properties of OLED materials
Authors: Zhao Yihuan , Fu Caixia , Fu Ling , Lu Zhiyun , Pu Xuemei
Published: February 2022

Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, the further development and commercialization of OLEDs requires higher-quality OLED materials, including materials with a high thermal stability. Thermal stability is associated with the glass transition temperature (Tg) and decomposition temperature (Td), but experimental determinations of these two important properties genernally involve a time-consuming and laborious process. Thus, the development of a quick and accurate prediction tool is highly desirable. Motivated by the challenge, we explored machine learning (ML) by constructing a new dataset with more than one thousand samples collected from a wide range of literature, through which ensemble learning models were explored. Models trained with the LightGBM algorithm exhibited the best prediction performance, where the values of MAE, RMSE, and R2 were 17.15 K, 24.63 K, and 0.77 for Tg prediction and 24.91 K, 33.88 K, and 0.78 for Td prediction. The prediction performance and the generalization of the machine learning models were further tested by out-of-sample data, which also exhibited satisfactory results. Experimental validation further demonstrated the reliability and the practical potential of the ML-based model. In order to extend the practical application of the ML-based models, an online prediction platform was constructed. This platform includes the optimal prediction models and all the thermal stability data under study, and it is freely available at http://oledtppxmpugroup.com. We expect that this platform will become a useful tool for experimental investigation of Tg and Td, accelerating the design of OLED materials with desired properties.
On the electro-oxidation of small organic molecules: towards a fuel cell catalyst testing platform with realistic reaction environment
Authors: Zhang Damin , Du Jia , Quinson Jonathan , Arenz Matthias
Published: February 2022

The electrocatalytic oxidation of small organic compounds such as methanol or formic acid has been the subject of numerous investigations in the last decades. The motivation for these studies is often their use as fuel in so-called direct methanol or direct formic acid fuel cells, promising alternatives to hydrogen-fueled proton exchange membrane fuel cells. The fundamental research spans from screening studies to identify the best performing catalyst materials to detailed mechanistic investigations of the reaction pathway. These investigations are commonly performed in standard three electrode electrochemical cells with a liquid supporting electrolyte to which the methanol or formic acid is added. In fuel cell devices, however, no liquid electrolyte will be present, instead membrane electrolytes are used. The question therefore arises, to which extend results from conventional electrochemical cells can be extrapolated to conditions found in fuel cells. We previously developed a gas diffusion electrode setup to mimic “real-life” reaction conditions and study electrocatalysts for oxygen gas reduction or water splitting. It is here demonstrated that the setup is also suitable to investigate the properties of catalysts for the electro-oxidation of small organic molecules. Using the gas diffusion electrode setup, it is seen that employing a catalyst - membrane electrolyte interface as compared to conventional electrochemical cells can lead to significantly different catalyst performances. Therefore, it is recommended to implement gas diffusion electrode setups for the investigation of the electro-oxidation of small organic molecules.
Pulsed Blue Laser Diode Thermal Desorption Microplasma Imaging Mass Spectrometry
Authors: Knodel Alexander , Marggraf Ulrich , Hoffmann-Posorske Edeltraut , Burhenn Sebastian , Brandt Sebastian , Ahlmann Norman , Foest Daniel , Lorenz Kristina , Franzke Joachim
Published: February 2022

An ambient air laser desorption, plasma ionization imaging method is developed and presented using a microsecond pulsed laser diode for desorption and the flexible microtube plasma for ionization of the neutral desorbate. Inherent parameters such as the laser repetition rate and pulse width are optimized to the imaging application. For the desorption substrate, copper spots on a copper-glass sandwich structure are used. This novel design enables imaging without ablating the metal into the mass spectrometer. On this substrate, fixed calibration markers are used to decrease the positioning error in the imaging process, featuring a 3D offset correction within the experiment. The image is both screened spot-by-spot and per line scanning at a constant speed, which allows direct comparison. In spot-by-spot scanning, a novel algorithm is presented to unfold and to reconstruct the imaging data. This approach significantly decreases the time required for the imaging process, which allows imaging even at decreased sampling rates and thus higher mass resolution. After the experiment, the raw data is automatically converted and interpreted by a second algorithm, which allows direct visualization of the image from the data, even on low-intensity signals. Mouse liver microtome cuts have been screened for dehydrated cholesterol, proving good agreement of the unfolded data with the morphology of the tissue. The method optically resolves 30 μm, with 30 μm diameter copper spots and a 10 μm gap. No conventional chemical matrices or vacuum conditions are required.
Crystal-chemical and biological controls of trace and minor element incorporation into magnetite nanocrystals
Authors: Amor Matthieu , Faivre Damien , Chevrier Daniel M.
Published: February 2022

Magnetite nanoparticles possess numerous fundamental, biomedical and industrial applications, many of which depend on tuning the magnetic properties. This is often achieved by the incorporation of trace and minor elements into the magnetite lattice. Such incorporation was shown to depend strongly on the magnetite formation pathway (i.e., abiotic vs biological), but the mechanisms controlling element partitioning between magnetite and its surrounding precipitation solution remain to be elucidated. Here, we used a combination of theoretical modelling (lattice and crystal field theories) and experimental evidence (high-resolution inductively coupled plasma mass spectrometry and X-ray absorption spectroscopy) to demonstrate that element incorporation into abiotic magnetite nanoparticles is controlled principally by cation size and valence. Elements from the first series of transition metals (Cr to Zn) constituted exceptions to this finding as their incorporation appeared to be also controlled by the energy levels of their unfilled 3d orbitals, in line with crystal field mechanisms. We then show that element incorporation into biological magnetite nanoparticles produced by magnetotactic bacteria (MTB) cannot be explained by crystal-chemical parameters alone, which points to the biological control exerted by the bacteria over the element transfer between MTB growth medium and the intracellular environment. This screening effect generates biological magnetite with a purer chemical composition than the abiotic materials formed in a solution of similar composition. Our work establishes a theoretical framework for understanding the crystal-chemical and biological controls of trace and minor cation incorporation into magnetite, thereby providing predictive methods to tailor the composition of magnetite nanoparticles for improved control over magnetic properties.
Investigating Tetrel based Neutral Frustrated Lewis Pairs for Hydrogen Activation
Authors: Sarkar Pallavi , Das Shubhajit , Pati Swapan K.
Published: February 2022

Tetrel Lewis acids are a prospective alternative to commonly employed neutral boranes in frustrated Lewis pair (FLP) chemistry. While cationic tetrylium Lewis acids, being isolobal and iso(valence)electronic, are a natural replacement to boranes, neutral tetrel Lewis acids allude as less trivial options due to the absence of a formally empty p orbital on the acceptor centre. Recently a series of intramolecular geminal FLPs (C2F5)3E-CH2-P(tBu)2 (E= Si, Ge, Sn) featuring neutral tetrel atoms as acceptor site, were reported for activation of small molecules including H2. In this work, through density functional theory computations, we elucidate the general mechanistic picture of H2 activation by this family of FLPs. Our findings reveal that the acceptor atom derives the required Lewis acidity utilizing the antibonding orbitals of its adjacent bonds with the individual contributions depending on the identity of the acceptor and the donor atoms. By varying the identity of the Lewis acid and Lewis base atoms and attached substituents, we unravel their interplay on the energetics of the H2 activation. We find that switching the donor site from P to N significantly affects the synchronous nature of the bond breaking/formations along the reaction pathway and as a result, N-bearing FLPs have a more favourable H2 activation profile than those with P. Our results are quantitatively discussed in detail within the framework of Activation Strain Model of reactivity along with the Energy Decomposition Analysis method. Finally, the reductive elimination decomposition route pertinent to the plausible extension of the H2 activation to catalytic hydrogenation by these FLPs is also examined
Efficient Synthesis of Azido Sugars using Fluorosulfuryl Azide Diazotransfer Reagent
Authors: Capicciotti Chantelle J. , Kofsky Joshua M. , Daskhan Gour C. , Macauley Matthew S.
Published: February 2022

Azide-containing sugars are important tools for the synthesis of biologically relevant 1,2-cis-glycosides and for bioconjugation chemistry. Previous strategies for the installation of a non-participating C2-azido functionality use harsh conditions and long reaction times. Herein, we report the synthesis of azido sugars using fluorosulfuryl azide (FSO2N3; 1) with a Cu(II) catalyst as a safe and efficient diazotransfer reagent. Common hexosamine substrates were converted to 2-azido-2-deoxy sugars in less than 5 minutes in quantitative yield. Glycosyl donors with orthogonal protecting groups were readily prepared from these azido sugars with good overall yield and a single column purification. The diazotransfer protocol was also efficiently used on other amino sugar derivatives, including aminoglycosides and substrates with amine-containing linkers. This optimized method will expand access to important non-participating C2-azido protecting groups and other azido sugar derivatives.
Tuning the Electrochemical and Photophysical Properties of Osmium Complexes for Application in Photoredox Catalysis
Authors: Goldschmid Samantha , Bednarova Eva , Beck Logan , Xie Katherine , Tay Nicholas , Ravetz Benjamin , Li Jun , Joe Candice , Rovis Tomislav
Published: February 2022

Photocatalysis driven by visible and ultraviolet irradiation is a fundamental tool for synthetic chemists. Recently, expansion of this tool to near-infrared (NIR) light has gained in popularity. Herein, we report the detailed photophysical characterization of a library of OsII polypyridyl photosensitizers that absorb NIR irradiation. By tuning ligand scaffold and electron density, we access a range of synthetically useful excited state energies and redox potentials.
Combining Generative Adversarial Network and First-Principles Based Microkinetics for Heterogeneous Catalyst Design
Authors: Ishikawa Atsushi
Published: February 2022

Microkinetic analysis based on density functional theory (DFT) was combined with a generative adversarial network (GAN) to enable artificial proposal of heterogeneous catalysts based on the DFT-calculated dataset. The approach was applied to the NH3 formation reaction on Ru-Rh alloy surfaces as an example. The NH3 formation turnover frequency (TOF) was calculated by DFT-based microkinetics. Specifically, six elementary reactions (N2 dissociation, H2 dissociation, NHx (x = 1–3) formation, and NH3 desorption) were explicitly considered, and their reaction energies were evaluated by DFT. On the basis of TOF values and atomic compositions, new alloy surfaces were generated using the GAN. This approach successfully generated the surfaces not included in the initial dataset but have higher TOF values. The N2 dissociation reaction was more exothermic for the generated surfaces, leading to higher TOF. The present study shows that automatic improvement of catalyst materials is possible by using the iterative steps of DFT calculation and sample generation by GAN.
Using automated serendipity to discover how trace water promotes and inhibits lead halide perovskite crystal formation
Authors: Nega Philip , Li Zhi , Ghosh Victor , Thapa Janak , Sun Shijing , Hartono Noor Titan Putri , Nellikkal Mansoor Ani Najeeb , Norquist Alexander J. , Buonassisi Tonio , Chan Emory M. , Schrier Joshua
Published: February 2022

We use a data-driven approach to discover the influence of trace amounts of water on perovskite crystal formation. Statistical analysis of 8,470 inverse-temperature crystallization lead iodide perovskite synthesis reactions, performed over 20 months using a robotic system, revealed discrepancies between the empirical crystal formation rate in experiments conducted under different ambient relative humidity conditions. We used the robotic system to conduct 1,296 controlled interventional experiments in which small amounts of water were deliberately introduced to the reactions. Addition of trace amounts of water promotes crystal formation for 4-methoxyphenylammonium lead iodide and iso-propylammonium lead iodide and inhibits crystal formation for dimethylammonium lead iodide and acetamidinium lead iodide. We also performed thin-film syntheses of these four materials and determined the grain size distributions using scanning electron microscopy. Addition of water results in smaller grain sizes for dimethylammonium and larger grain sizes for isopropylammonium, consistent with earlier or delayed nucleation, respectively.
EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
Authors: Heid Esther , Goldman Samuel , Sankaranarayanan Karthik , Coley Connor W. , Flamm Christoph , Green William H.
Published: February 2022

Data-driven computer-aided synthesis planning utilizing organic or biocatalyzed reactions from large databases has gained increasing interest in the last decade, sparking the development of numerous tools to extract, apply and score general reaction templates. The generation of reaction rules for enzymatic reactions is especially challenging, since substrate promiscuity varies between enzymes, causing the optimal levels of rule specificity and optimal number of included atoms to differ between enzymes. This complicates an automated extraction from databases and has promoted the creation of manually curated reaction rule sets. Here we present EHreact, a purely data-driven open-source software tool to extract and score reaction rules from sets of reactions known to be catalyzed by an enzyme at appropriate levels of specificity without expert knowledge. EHreact extracts and groups reaction rules into tree-like structures, Hasse diagrams, based on common substructures in the imaginary transition structures. Each diagram can be utilized to output a single or a set of reaction rules, as well as calculate the probability of a new substrate to be processed by the given enzyme by inferring information about the reactive site of the enzyme from the known reactions and their grouping in the template tree. EHreact heuristically predicts the activity of a given enzyme on a new substrate, outperforming current approaches in accuracy and functionality.
Ultrafast intersystem crossing in xanthone from wavepacket dynamics simulations
Authors: Alías Rodríguez Marc , De Graaf Coen , Huix-Rotllant Miquel
Published: February 2022

Most aromatic ketones containing first-row elements undergo unexpectedly fast intersystem crossing in few tens of picosecond and a quantum yield close to unity. Among them, xanthone (9H-xanthen-9-one) possesses one of the fastest intersystem crossing rates of ~1.5 ps, despite containing only first-row elements. The exact mechanism of this unusually fast singlet-triplet transition is still under debate. Here, we perform a complete wavepacket dynamics simulation of the internal conversion and intersystem crossing reactions of xanthone in the gas phase. We show that xanthone follows El-Sayed's rule for intersystem crossing. From the second singlet excited state, the mechanism is sequential: (i) an internal conversion between singlets 1pipi*-1npi* (~0.14 fs), (ii) an intersystem crossing 1npi*-3pipi* (~1.8 ps), and (iii) an internal conversion between triplets 3pipi*-3npi* (~27 ps). Each transfer finds its origin in a barrierless access to electronic state intersections. These intersections are close to minimum energy structures, allowing for an efficient radiationless transition from 1pipi* to 3npi*.
Vinylcyclopropane [3+2] Cycloaddition with Acetylenic Sulfones Based on Visible Light Photocatalysis
Authors: Luque Adriana , Groß Jonathan , Opatz Till
Published: February 2022

We describe the first intermolecular visible light [3+2] cycloaddition reaction being performed on a meta photocycloadduct employing acetylenic sulfones. The developed methodology exploits the advantages of combining UV and Visible light in a two-step sequence that provides a photogenerated cyclopropane which, through a strain-release process, generates a new cyclopentane ring while increasing significally the molecular complexity. This strategy could be extended to simpler vinylcyclopropanes.
Coverage-dependent adsorption model of atomic oxygen on Ag(111)
Authors: Mize Carson , Isbill Sara , Roy Sharani
Published: February 2022

Theoretical gas-surface models that describe adsorption over a wide range of coverages can provide qualitative insight into chemical phenomena that occur at intermediate to high coverages, such as subsurface adsorption, surface reconstruction, and industrial heterogeneous catalysis. However, most atomistic, quantum-mechanical models of gas-surface adsorption are limited to low adsorbate coverage due to the large computational cost of models built using many surface atoms and adsorbates. To investigate adsorption in the subsurface of a crystalline solid at high coverage, we present a lattice-gas adsorption model that includes surface and subsurface sites of the solid, and is fully parametrized using density functional theory. We apply the model to study the coverage-dependent adsorption of atomic oxygen on the Ag(111) surface. Oxygen population distributions calculated using the model show the onset of subsurface adsorption at a total coverage of approximately 1/4 monolayer, the saturation of surface adsorption at a total coverage of approximately 1/3 monolayer, and a greater accumulation of oxygen in the second rather than the first subsurface at total coverages greater than 1/2 monolayer. Computation of core-electron binding energies and projected density of states of an oxygen distribution predicted by the model reveal qualitative differences in oxygen-silver bonding at the surface and subsurface, suggesting that oxygen adsorbed in the two regions could play distinct roles in surface chemistry.
Robust ligand-protein docking using an advanced genetic algorithm
Authors: Williams David , Kita David , Chang Eric , Pahel Douglas , Wang Qiang
Published: February 2022

Computational prediction of ligand-protein binding is an essential part of overcoming the synthesis bottleneck for rapid development of small-molecule drugs. Nevertheless, an accurate prediction of binding free energy is challenging without first establishing a ligand binding pose. Reported in this paper is an advanced optimization algorithm that is capable of providing multiple, high-fidelity solutions to a ligand-protein pose even for complicated systems with large numbers of degrees of freedom. This algorithm achieves high performance by incorporating several important features, such as niching and force-field annealing. Results from several challenging use cases are presented and discussed.
The Importance of Decarbonylation Mechanisms in the Atomic Layer Deposition of High-Quality Ru Films by Zero-Oxidation State Ru(DMBD)(CO)3
Authors: Schneider Joel , de Paula Camila , Lewis Jacqueline , Woodruff Jacob , Raiford James , Bent Stacey
Published: February 2022

Achieving facile nucleation of noble metal films through atomic layer deposition (ALD) is extremely challenging. To this end, η4-2,3-dimethylbutadiene ruthenium tricarbonyl (Ru(DMBD)(CO)3), a zero-valent complex, has recently been reported to achieve good nucleation by ALD at relatively low temperatures and mild reaction conditions. We study the growth mechanism of this precursor by in situ quartz-crystal microbalance and quadrupole mass spectrometry during Ru ALD, complemented by ex situ film characterization and kinetic modeling. These studies reveal that Ru(DMBD)(CO)3 produces high-quality Ru films with excellent nucleation properties. This results in smooth, coalesced films even at low film thicknesses, all important traits for device applications. However, Ru deposition follows a kinetically limited decarbonylation reaction scheme, akin to typical CVD processes, with a strong dependence on both temperature and reaction timescale. The non-self-limiting nature of the kinetically driven mechanism presents both challenges for ALD implementation and opportunities for process tuning. By surveying reports of similar precursors, we suggest that the findings can be generalized to the broader class of zero-oxidation state carbonyl-based precursors used in thermal ALD, with insight into the design of effective saturation studies.
Lewis acid-mediated Suzuki–Miyaura Cross-Coupling Reaction
Authors: Niwa Takashi , Uetake Yuta , Isoda Motoyuki , Takimoto Tadashi , Nakaoka Miki , Hashizume Daisuke , Sakurai Hidehiro , Hosoya Takamitsu
Published: February 2022

The palladium-catalysed Suzuki–Miyaura cross-coupling (SMC) reaction of organohalides and organoborons is a reliable method for carbon–carbon bond formation. This reaction involves a base-mediated transmetalation process, but the presence of a base also promotes competitive protodeborylation, which reduces the efficiency. Herein, we established an SMC reaction via Lewis acid-mediated transmetalation of an organopalladium(II) intermediate with organoborons. Experimental and theoretical investigations indicate that the controlled release of the transmetalation-active intermediate enabled base-independent transmetalation under heating conditions and enhanced the applicable scope of this process. This system enabled us to avoid the addition of a base, and thus, rendered substrates with base-sensitive moieties available. Results from this research further expand the overall utility of cross-coupling chemistry.
Lower Heating Value of Jet Fuel from Hydrocarbon Class Concentration Data and Thermo-Chemical Reference Data: An Uncertainty Quantification
Authors: Boehm Randall , Yang Zhibin , Bell David , Feldhausen John , Heyne Joshua
Published: February 2022

A detailed assessment is presented on the calculation and uncertainty of the lower heating value (net heat of combustion) of conventional and sustainable aviation fuels, from hydrocarbon class concentration measurements, reference molecular heats of formation, and the uncertainties of these reference heats of formation. Calculations using this paper’s method and estimations using ASTM D3338 are reported for 17 fuels of diverse compositions and compared against reported ASTM D4809 measurements. All the calculations made by this method and the reported ASTM D4809 measurements agree (i.e., within 95% confidence intervals). The 95% confidence interval of the lower heating value of fuel candidates that are comprised entirely of normal- and iso-alkanes is less than 0.1 MJ/kg by the method described here, while high cyclo-alkane content leads to 95% confidence bands that approach 0.2 MJ/kg. Taking a possible bias into account, the accuracy and precision of the method described in this work could be as high as 0.23 MJ/kg for some samples.
Low-cost, Electro-Active C@Fe3C/Fe3O4 composite derived using bagasse for the oxygen reduction reaction
Authors: Manippady Rashmi , Khan Ziyauddin , Samal Akshaya , Saxena Manav
Published: February 2022

As the world is heading towards a sustainable future, it is highly important to develop low-cost electrocatalysts for energy generation devices. Herein, we report the synthesis of iron-carbon hybrid (C@Fe3C/Fe3O4) nanocomposite for oxygen reduction reaction (ORR), synthesized using bagasse as a carbon source material and Fe(III) precursor at 900 ˚C. The synthesized C@Fe3C/Fe3O4 composite exhibits a high surface area of ~930 m2/g. The electrode material has a 0.86 V overpotential vs RHE. Moreover, the electrocatalyst shows catalytic stability upto 18 h at the static potential of 0.25 V vs RHE at the rotation speed of 1600 rpm. Herein, the electron transfer number is close to 4 which suggests that our electrocatalyst may have an impact on efficient electrocatalyst designing for ORR in alkaline solution.
Direct and indirect role of Fe doping in NiOOH monolayer for water oxidation catalysis
Authors: Kumar Manish , Piccinin Simone , Srinivasan Varadharajan
Published: February 2022

The oxygen evolution reaction (OER) activity of pristine NiOOH is enhanced by doping with Fe. However, the precise role of Fe is still being debated. Here, we use the first-principles DFT+U approach to study three different types of active sites: one on pristine and the other two on Fe-doped NiOOH monolayers to account for the direct and indirect roles of Fe. To compare the activity of the active sites, we consider two mechanisms of OER based on the source of O-O bond formation. Our results show that the mechanism involving the coupling of lattice oxygen is generally more favorable than water nucleophilic attack on lattice oxygen. On doping with Fe, the overpotential of NiOOH is reduced by 0.33 V in excellent agreement with experimental findings. Introducing Fe at active sites results in different potential determining steps (PDS) in the two mechanisms, whereas Ni sites in pristine and Fe-doped NiOOH have the same PDS regardless of the mechanism. The Fe sites not only have the lowest overpotential but also decrease the overpotential for Ni sites.
RegioML: Predicting the regioselectivity of electrophilic aromatic substitution reactions using machine learning
Authors: Ree Nicolai , Göller Andreas H. , Jensen Jan H.
Published: February 2022

We present RegioML, an atom-based machine learning model for predicting the regioselectivities of electrophilic aromatic substitution reactions. The model relies on CM5 atomic charges computed using semiempirical tight binding (GFN1-xTB) combined with the ensemble decision tree variant light gradient boosting machine (LightGBM). The model is trained and tested on 21,201 bromination reactions with 101K reaction centers, which is split into a training, test, and out-of-sample datasets with 58K, 15K, and 27K reaction centers, respectively. The accuracy is 93% for the test set and 90% for the out-of-sample set, while the precision (the percentage of positive predictions that are correct) is 88% and 80%, respectively. The test-set performance is very similar to the graph-based WLN method developed by Struble et al. (React. Chem. Eng. 2020, 5, 896) though the comparison is complicated by the possibility that some of the test and out-of-sample molecules are used to train WLN. RegioML out-performs our physics-based RegioSQM20 method (J. Cheminform. 2021, 13:10) where the precision is only 75%. Even for the out-of-sample dataset, RegioML slightly outperforms RegioSQM20. The good performance of RegioML and WLN is in large part due to the large datasets available for this type of reaction. However, for reactions where there is little experimental data, physics-based approaches like RegioSQM20 can be used to generate synthetic data for model training. We demonstrate this by showing that the performance of RegioSQM20 can be reproduced by a ML-model trained on RegioSQM20-generated data.
Beyond conformational control: effects of noncovalent interactions on electronic properties of conjugated polymers
Authors: Liu Bin , Rocca Dario , Yan He , Pan Ding
Published: February 2022

Noncovalent intramolecular interactions have been often used as conformational control to enhance the planarity of polymers or molecules. However, it is little known if noncovalent interactions may alter the electronic properties of conjugated polymers through some mechanism other than the conformational control. Here, we studied the effects of six common noncovalent interactions on electronic properties of polymers with planar geometry using unconstrained and constrained density functional theory. We found that the sulfur-nitrogen intramolecular interaction may reduce the band gaps of polymers and enhance the charge transfer more obviously than other noncovalent interactions. Our findings are also consistent with the experimental data. For the first time, our study shows that noncovalent interactions may directly affect the electronic structure of polymers, which is not due to the enhancement of molecular planarity. Our work suggests a new mechanism to manipulate the electronic properties of polymers to design high-performance small-molecule-polymer and all-polymer solar cells.
Natural reaction orbitals
Authors: Ebisawa Suichi , Hasebe Msatoshi , Tsutsumi Takuro , Tsuneda Takao , Taketsugu Tetsuya
Published: February 2022

Natural reaction orbital (NRO) for analyzing chemical reactions from the viewpoint of the electronic theory is presented. The pair of the occupied and virtual NROs that drives chemical reaction are automatically extracted from the solutions of the coupled-perturbed self-consistent-field (CPSCF) equation for the perturbation of the nuclear displacement along the reaction path. Applying the NRO-based reaction analysis method to the H2CO– + H3CCl reaction, it was found that the sum of squared singular values of the solutions of the CPSCF equation gives the maximum peak at the transition state structure and the shoulder of the potential energy curve, which clearly explains the process of electron transfer and bond formation in this reaction. The NRO-based reaction analysis method has been demonstrated to be universal and robust for describing sophisticated reaction mechanisms.
Syntheses of Hydrocarbazole Derivatives via Brønsted acid-Initiated Diels-Alder Cycloaddition/retro-Michael Addition Cascade Reaction of Azepino[4,5-b]indoles and Acrolein
Authors: Xie Fukai , Li Xiang , Xu Liangyu , Ma Jun , Sun Lei , Zhang Bo , Lin Bin , Cheng Maosheng , Liu Yongxiang
Published: February 2022

A unique approach to hydrocarbazoles bearing an all-carbon quaternary center at C4a position was developed via a Brønsted acid-initiated Diels-Alder cycloaddition/retro-Michael addition cascade process from facilely prepared azepino[4,5-b]indoles and commercially available acrolein. The method provided a range of hydrocarbazoles in good to excellent yields. The practi-cality of this transformation was demonstrated by scale-up experiment and various transformations to several hydrocarbazole derivatives.
Molecular stabilization of chemically exfoliated bare MnPS3 layers
Authors: Torres-Cavanillas Ramon , Brotons-Alcazár Isaac , Forment-Aliaga Alicia , Coronado Eugenio , Morant-Giner Marc , Mañas-Valero Samuel , Cvik Martin
Published: February 2022

Transition metal chalcogenophosphates of general formula MPX3 have attracted recent interest in the field of 2D materials due to the possibility of tuning their properties when reaching the 2D limit. Several works address this challenge by dry mechanical exfoliation. However, only a few of them use a scalable approach. In this work, we apply a general chemical protocol to exfoliate MnPS3. The method uses in a first step chemical intercalation and liquid phase exfoliation, followed in a second step by the addition of molecules used as capping agents on the inorganic layers. Therefore, molecules of different nature prompts the quality of the exfoliated material and its stabilization in aqueous solution, opening the possibility of using these functionalized layers in several fields. Here we illustrate this possibility in electrochemistry. Thus, we show that when polyethylenimine is used as capping agent, it is possible to reach a compromise between the stability of high quality MnPS3 flakes in aqueous suspension and their optimum performance as an electrocatalytic system for HER activity.
Validation of a hemiacetal intermediate during absolute Soai autocatalytic amplification under heterogenous phase
Authors: Amedjkouh Mohamed , Rotunno Giuseppe
Published: February 2022

Absolute asymmetric synthesis produces chiral molecules without any chiral polarization and is an interesting rational for the origin of homochirality. Remarkably, in the Soai reaction absolute asymmetric amplification of alkanol product is observed under heterogenous conditions. Reaction of iPr2Zn vapor on solid carbaldehyde produced corresponding alkanol with up to 96% ee. In a parallel amplification process, a chiral ester is produced with 98% ee. The latter is attributed to disproportionation of starting aldehyde into hemiacetal followed by a subsequent Claisen-Tishchenko mechanism. This observation provide evidence for the debated transient intermediate, and opens new perspectives in the elucidation of the mechanism of amplification of chirality in the Soai reaction.
Bioorthogonal photocatalytic decaging-enabled spatiotemporal proteomics
Authors: Huang Zongyu , Liu Ziqi , Xie Xiao , Zeng Ruxin , Chen Zujie , Kong Linghao , Fan Xinyuan , Chen Peng
Published: February 2022

Spatiotemporally resolved dissection of subcellular proteome is crucial to our understanding of cellular functions in health and disease. Although enzyme-based proximity labeling strategies have emerged as powerful methods to portray the compartmentalized proteome of diverse organelles, current approaches still suffer from limitations such as the genetic operation that is not compatible with hard-to-transfect cells as well as overexpression of the fusion protein that may cause altered intracellular localization. We herein report a non-genetic strategy termed bioorthogonal and photocatalytic decaging-mediated proximity labeling (CAT-Prox) for spatiotemporally resolved proteome profiling in living cells. Our systematic survey of the organometallic photocatalysts has led to the identification of Ir(ppy)2bpy as a bioorthogonal and mitochondria-targeting complex that allowed photo-controlled, rapid rescue of azidobenzyl-caged quinone methide as a highly reactive Michael acceptor for proximity-based protein labelings. By coupling with quantitative mass spectrometry, CAT-Prox revealed the dynamic mitochondria proteome of cancer cells and macrophage cells under normal and stressed conditions. Furthermore, by targeting the photocatalyst to cell membrane receptors, CAT-Prox allowed microdomain proteome profiling on live cell surface. Together, CAT-Prox integrated the advantages of both enzymatic and chemical-based proximity labeling approaches as a general spatiotemporal proteomics platform for diverse subcellular spaces and cell types.
Remote-controlled exchange rates by photoswitchable internal catalysis of dynamic covalent bonds
Authors: Barsoum David , Kalow Julia
Published: February 2022

The transesterification of boronate esters with diols is tunable over at least 14 orders of magnitude. Rate acceleration is achieved by internal base catalysis, which lowers the barrier for the proton transfer step. Here we report a photoswitchable internal catalyst that tunes the rate of boronic ester/diol exchange over at least 4 orders of magnitude. We employed an acylhydrazone molecular photoswitch, which forms a thermally stable but photoreversible intramolecular H-bond, to gate the activity of the internal base catalyst in 8-quinoline boronic esters. The photoswitch can be cycled repeatedly, with high photostationary states. The intramolecular H-bond is found to be essential to the design of this photoswitchable internal catalyst, as protonating the quinoline with external sources of acid has little effect on the exchange rate.
Synthesis and Photoluminescence Properties of MoS2/Graphene Hetero-Structure by Liquid Phase Exfoliation
Authors: Kandhasamy Durai Murugan , Muthu Mareeswaran Paulpandian , Selvaraju Chellappan , Dhenadhayalan Namasivayam
Published: February 2022

Synthesis of MoS2/Graphene hetero-structure in single stage, liquid-phase exfoliation in 7:3 isopropyl alcohol /water mixture and its consequences on the photoluminescence behavior of MoS2 have been studied. Thus synthesized hetero-structure was characterized using UV-visible, micro-Raman spectroscopy, Transmission electron microscopy(TEM), and Dynamic Light Scattering (DLS) analysis. UV-Visible and micro-Raman analysis confirm improved exfoliation to the level of monolayer hetero-structure. The photophysical properties of the hetero-structure were analyzed using steady state and time resolved luminescence techniques. An enhanced photoluminescence observed in the case of hetero-structure probably due to increase in the defect sites or reduction in the rate of non-radiative decay upon formation of sandwiched hetero-structure. Applications of this hetero-structure for fluorescence live cell imaging carried out and the hetero-structure demonstrated a better luminescence contrast compared to its individual counterpart MoS2 in phosphate buffered saline (PBS).
Correlations between Precipitation Reactions and Electrochemical Performance of Lithium–Sulfur Batteries
Authors: Chien Yu-Chuan , Lacey Matthew J. , Steinke Nina-Juliane , Brandell Daniel , Rennie Adrian R.
Published: February 2022

A comprehensive description of the electrochemical processes in the positive electrode of lithium–sulfur batteries is crucial for the enhancement of sulfur utilization. However, the discharge mechanisms are complicated due to the various reactions in multiple phases and the tortuosity of the highly porous carbon matrix. While previous studies have focused on the precipitation of lithium sulfide, the effect of the limited mass transport inside the micropores and mesopores of an electrode with optimized surface area have largely been neglected. In this work, in-operando small-angle scattering with three different contrasts, and wide-angle scattering measurements are made while the internal and diffusion resistances are measured simultaneously. The results indicate that the precipitates grow mostly in number, not in size, and that the structure of the carbon matrix is not affected. The comparison of the small-angle and wide-angle scattering reveals the amorphous discharge products found at a low discharge rate. Further analyses demonstrate the correlation between the diffusion resistance and the composition of material in the mesopores at the end of discharge, which suggests that Li-ion deficiency is the limiting factor of sulfur utilization at a medium discharge rate.
Revealing Substrate Positioning Dynamics in Non-heme Fe(II)/αKG-dependent Halogenases Through Spectroscopically Guided Simulation
Authors: Mehmood Rimsha , Vennelakanti Vyshnavi , Kulik Heather
Published: February 2022

Non-heme iron halogenases, such as SyrB2, WelO5, and BesD, halogenate unactivated carbon atoms of diverse substrates at ambient conditions with exquisite selectivity seldom matched by non-biological catalysts. Although crystallography, spectroscopy, and kinetic measurements provide foundational knowledge of enzyme structure and function, critical gaps remain in our understanding of how the protein environment dynamically reorganizes to a catalytically active state capable of halogenation. Using experimentally-guided molecular dynamics (MD) simulations augmented with multi-scale (i.e., QM/MM) simulations of substrate-bound complexes of BesD and WelO5, we investigate substrate/active-site dynamics that enable selective halogenation. Our simulations reveal that active-site configurational isomerization is necessary in WelO5 to attain substrate/active-site geometry consistent with its observed chemo- and regioselectivity. Conversely, a slight reorientation of the substrate from its crystal-structure position is sufficient to enable regioselective chlorination in BesD without the need to invoke active-site isomerization. We observe how substrate-protein interactions evolve during experimentally-motivated MD of halogenases. We relate the nature of these interactions to the distinct substrates. For BesD, we resolve the uncertainty around the mechanistic relevance of Asn219 based on a prior mutagenesis study. By quantifying the presence of thermodynamically competitive C-H bonds on substrates of SyrB2, BesD, and WelO5, we confirm the need for the protein environment to strategically position the substrate to impart regioselectivity to halogenases. Our simulations reveal that the optimum substrate/active-site geometry also outweighs interactions between active site ligands and the protein environment in facilitating the required chemoselectivity in halogenases.
Explore protein conformational space with variational autoencoder
Authors: Tian Hao , Jiang Xi , Trozzi Francesco , Xiao Sian , Larson Eric , Tao Peng
Published: February 2022

Molecular dynamic (MD) simulations have been actively used in the study of protein structure and function. However, extensive sampling in the protein conformational space requires large computational resources and takes a prohibitive amount of time. In this study, we demonstrated that variational autoencoders (VAEs), a type of deep learning model, can be employed to explore the conformational space of a protein through MD simulations. VAEs are shown to be superior to autoencoders (AEs) through a benchmark study, with low deviation between the training and decoded conformations. Moreover, we show that the learned latent space in the VAE can be used to generate unsampled protein conformations. Additional simulations starting from these generated conformations accelerated the sampling process and explored hidden spaces in the conformational landscape.
Targeted Fluorogenic Cyanine Carbamates Enable In Vivo Analysis of Antibody-Drug Conjugate Linker Chemistry
Authors: Usama Syed , Marker Sierra , Caldwell Donald , Patel Nimit , Feng Yang , Kalen Joseph , St Croix Brad , Schnermann Martin
Published: February 2022

Antibody-drug conjugates (ADCs) are a rapidly emerging therapeutic platform. The chemical linker between the antibody and the drug payload plays an essential role in the efficacy and tolerability of these agents. New methods that quantitively assess cleavage efficiency in complex tissue settings could provide valuable insights into the ADC design process. Here we report the development of a near-infrared (NIR) optical imaging approach that measures the site and extent of linker cleavage in mouse models. This approach is enabled by a superior variant of our recently devised cyanine carbamate (CyBam) platform. We identify a novel tertiary amine-containing norcyanine, the product of CyBam cleavage, that exhibits dramatically in-creased cellular signal due to improved cellular permeability and lysosomal accumulation. The resulting cyanine lysosome-targeting carbamates (CyLBams) are ~50X brighter in cells, and we find this strategy is essential for high-contrast in vivo targeted imaging. Finally, we compare a panel of several common ADC linkers across two antibodies and tumor models. These studies indicate that cathepsin-cleavable linkers provide dramatically higher tumor activation relative to hindered or non-hindered disulfides – an observation that is only apparent with in vivo imaging. This strategy enables quantitative comparisons of cleavable linker chemistries in complex tissue settings with implications across the drug delivery landscape.