bluuebunny/crossref_metadata_2025 huggingface dataset:
Material flows and Embodied Energy of Direct Air Capture
Authors: Simon Balint
Published: February 2022

: Direct air capture (DAC) is an essential nexus of CO2 chemistry and climate mitigation. Life cycle assessment (LCA) is often deployed to validate the environmental potentials of such future emerging technologies. Consequently, an increased number of ex-ante LCAs are expected in this field. However, recently a comprehensive life cycle inventory for LCA is missing from the international literature, which is essential for transparency. To fill this gap, the present paper analyses three selected DAC technologies to create an inventory for LCAs. Amine-based adsorption and -absorption, as well as, alkali-based absorption was modelled. Energy consumption of the operation, the cradle-to-gate embodied energy and sensitivity analysis based on parameter variations were carried out. The maximum energy released by the formation of CO2 (8.94-18.2 GJ/t CO2) were also considered in the evaluation. However several studies state that DAC is a negative emission technology, its energy requirement often lies in the range or above the formation energy of CO2. Accordingly, theoretically more energy is required for the capture as can be obtained during the formation of CO2. The calculation model includes over 60 parameters resulting in an array of the possible energy and material requirements. The use of this wide range of figures in life cycle assessment sheds light on the real opportunities of direct air capture in future product systems. The option of varying parameters enables tailoring the calculation to a particular situation or design. In this way, the calculator offers a common base for LCA fostering the early-stage analysis of DAC technologies.
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
Authors: Johansson Simon Viet , Gummesson Svensson Hampus , Bjerrum Esben , Schliep Alexander , Chehreghani Morteza Haghir , Tyrchan Christian , Engkvist Ola
Published: February 2022

Computer aided synthesis planning is a rapidly growing field for suggesting synthetic routes for molecules of interest. The methods used are usually dependent on access to large datasets for training, but with a finite experimental budget there are limitations on how much data can be obtained from experiments. Active learning, which has been used in recent studies with success, is a strategy to identify which data points impact model accuracy the most. However, little has been done to explore the robustness of the methods predicting reaction yield. This study aims to investigate the influence of machine learning algorithms and the number of initial data points on reaction yield prediction for two public high-throughput experimentation datasets. Our results show that active learning based on output margin reached a pre-defined accuracy (AUROC) faster than using passive learning. Feature importance analysis of the trained machine learning models suggested active learning had larger influence on the model accuracy when only a few features were important for the model prediction.
Revisiting the Key Optical and Electrical Characteristics in Reporting Photocatalysis of Semiconductors
Authors: Bui Dai-Phat , Pham Minh-Thuan , Tran Hong-Huy , Nguyen Thanh-Dat , Cao Minh Thi , Pham Van Viet
Published: February 2022

Photocatalysis has been studied and considered as a green and effective approach in addressing environmental pollution. However, factors that affect photocatalytic performance have not been systematically studied. In this work, we have presented a comprehensive roadmap for characterizing, interpreting, and reporting semiconductors' electrical and optical properties through routinely used techniques (XPS, DRS, PL) in the context of photocatalysis. Having deeply and precisely studied the band structure of three representative photocatalysts, we have presented and highlighted essential information and details, which are critical and beneficial for studies of (1) band alignments, (2) redox potentials, and (3) defects. Further works with a comprehensive understanding of band structure are desirable and hold great promise.
Phosphine-catalysed reductive coupling of Dihalophosphanes
Authors: Hering-Junghans Christian , Siewert Jan-Erik , Schumann André
Published: February 2022

Classically, tetraorgano diphosphanes have been synthesized through Wurtz-type reductive coupling of halophosphanes R2PX or more recently, through the dehydrocoupling of phosphines R2PH. Catalytic variants of the dehydrocoupling reaction have been reported but are limited to R2PH compounds. Using PEt3 as a catalyst, we now show that TipPBr2 (Tip = 2,4,6-iPr3C6H2) is selectively coupled to give the dibromodiphosphane (TipPBr)2 (1), a compound not accessible using classic Mg reduction. Surprisingly, when using DipPBr2 (Dip = 2,6-iPr3C6H3) in the PEt3-catalysed reductive coupling the diphosphene (PDip)2 (2) with a P=P double was formed selectively. In benzene solutions (PDip)2 has a half life-time of ca. 28 days and can be utilized with NHCs to access NHC-phosphinidene adducts. Control experiments show that [BrPEt3]Br is a potential oxidation product in the catalytic cycle, which can be then debrominated by using Zn dust as sacrificial reductant.
A new approach to optimize pH buffers
Authors: Blétry Marc
Published: February 2022

Buffer solutions are pervasive in chemistry, biochemistry, analytical chemistry, etc. A better understanding of buffer properties and what controls them is susceptible to be of interest in many scientific and technological fields. For instance, linear pH gradients are commonly used in electrophoresis and their optimization rests on numerical optimization of the concentrations of various weak species. It is probably generally assumed that no basic progress could be made on optimization approaches. We introduce here a new strategy to buffer optimization, based on a parametric study of the roots of the first derivative of the buffer index. In this way, it is possible to find mathematically optimal sets of parameters (pKa and concentrations). The method is applied to mixtures of 2, 3 and 4 monovalent species, which represent simple cases that do not call for overly elaborate numerical optimization techniques, but are nevertheless of practical interest in various branches of analytical chemistry.
Machine Learning Dynamic Correlation in Chemical Kinetics
Authors: Kim Changhae Andrew , Ricke Nathan D. , Van Voorhis Troy
Published: February 2022

The kinetics of surface reactions are often described using a lattice model. Since it is expensive to propagate the configuration probabilities of the entire lattice, it is practical to consider the occupation probabilities of a typical site or a cluster of sites instead. This amounts to a moment closure approximation of the chemical master equation (CME). Unfortunately, simple closures, such as the mean-field (MF) and the pair approximation (PA), exhibit weaknesses in systems with significant long-range correlation. In this paper, we show that machine learning (ML) can be used to construct accurate moment closures in chemical kinetics, using the lattice Lotka-Volterra model (LLVM) as a model system. We trained feed-forward neural networks (FFNNs) to estimate the three-site occupation probabilities, using kinetic Monte Carlo (KMC) results at select values of rate constants and initial conditions. Given the same level of input as PA, the machine learning moment closure (MLMC) gave drastic improvements in the simulated dynamics and descriptions of the dynamical regimes throughout the parameter space. In this way, MLMC is a promising tool to interpolate KMC simulations or construct pre-trained closures that would enable researchers to extract useful insight at a fraction of the computational cost.
Constructing Ultralong Near-infrared Organic Phosphorescence Materials with 732 nm through One-axis Two-wing Guest-Host Strategy for Bioimaging
Authors: Xiao Fuming , Gao Heqi , lei yunxiang , Liu Miaochang , Zheng Xiaoyan , Cai Zhengxu , Huang Xiaobo , Wu Huayue , Ding Dan
Published: February 2022

In this work, we have obtained organic room temperature phosphorescence/RTP materials with long wavelengths (657-732 nm) and long lifetimes (102-324 ms) for the first time through the one-axis two-wing guest-host strategy. The one axis refers to that the guest molecule has sufficient conjugation to reduce the lowest triplet energy level and the two wings refer to that the host assists the guest in exciton transfer and inhibits the non-radiative transition of guest excitons. These materials exhibit good tissue penetration in bioimaging. Thanks to the characteristic of long lifetime and long wavelength emissive RTP materials, the tumor imaging in living mice with a signal to background ratio value as high as 43 is successfully realized. This work provides a practical solution for the construction of organic RTP materials with both long wavelengths and long lifetimes used in bioimaging.
Discovery and characterization of benzyloxy piperidine based dopamine 4 receptor antagonists
Authors: Tolentino Kirsten , Mashinson Viktoriya , Vadukoot Anish , Hopkins Corey
Published: February 2022

Abstract: The dopamine receptor 4 (D4R) is highly expressed in both motor, associative and limbic subdivisions of the coritico-basal ganglia network. Due to the distribution in the brain, there is mounting evidence pointing to a role for the D4R in the modulation of this network and its subsequent involvement in L-DOPA induced dyskinesias in Parkinson’s disease. As part of our continued effort in the discovery of novel D4R antagonists, we report the discovery and characterization of a new 3- or 4-benzyloxypiperidine scaffold as D4R antagonists. We report several D4R selective compounds (>30-fold vs. other dopamine receptor subtypes) with improved in vitro and in vivo stability over previously reported D4R antagonists.
From Theory to Experiment: Transformer-Based Generation Enables Rapid Discovery of Novel Reactions
Authors: Wang Xinqiao , Yao Chuansheng , Zhang Yun , Yu Jiahui , Qiao Haoran , Zhang Chengyun , Wu Yejian , Bai Renren , Duan Hongliang
Published: February 2022

Deep learning methods have been proven their potential roles in the chemical field, such as reaction prediction and retrosynthesis analysis. However, the de novo generation of unreported reactions using artificial intelligence technology remains not be completely explored. Inspired by molecular generation, we proposed the task of novel reaction generation. In this work, we applied the Heck reactions to train the transformer model, state-of-art natural language process model and obtained 4717 generated reactions after sampling and processing. We then confirmed that 2253 novel Heck reactions by organizing chemists to judge the generated reactions, and adopted organic synthesis experiment to verify the feasibility of unreported reactions. In this process, it only took 15 days from Heck reaction generation to experimental verification, proving that our model learns reaction rules in-depth and can make great contributions in the novel reaction discovery.
Conformational analysis between 6M71 (SARS COV2 RNA-dependent RNA polymerase) and CHEMBL3120791 using GROMACS Molecular Dynamic simulation.
Authors: Gudipati Pavan
Published: February 2022

We analyzed molecular dynamic simulation using GROMACS to study the interaction between SARS-Cov-2 cryo-EM structure of RNA-dependent RNA polymerase (PDB ID: 6M71) and compound CHEMBL3120791 with 20ns simulation using NVIDIA GPU for high performance. SARS Cov2 RNA-dependent RNA polymerase (RdRp) is an enzyme that catalyzes the synthesis and replication of viral RNA from an RNA template. CHEMBL3120791 is in clinical trial for the treatment of HCV (Hepatitis C Virus) infections, and HCV Viruses are like SARS viruses. In our study, we found amino acids LYS47, ASN138, ASN781, THR141, THR710, SER709, SER778, SER784, TYR129 can potentially form hydrogen bonds with the drug molecule. Among all the amino acids mentioned in the list Asparagine 138 and Serine 709 may form hydrogen bonds with CHEMBL3120791 and this interaction can cause changes in conformation between coil and Helix. These amino acids are located around the active site of the enzyme and can be utilized for protein ligand interaction. ASN138, SER709 will actively play and change in conformation during Protein-ligand bond interactions
Graphene Encapsulated Ni@N/C Catalyst for Highly Selec- tive Semi-hydrogenation of Terminal Alkynes
Authors: liu Jianguo , Sun Jiangmin , Lin Shanshan , Ma Longlong
Published: February 2022

Although precious transition metals such as palladium, platinum, and iridium have been widely used in hydro- genation reactions, the earth-abundant transition metal-catalyzed highly selective semi-hydrogenation of alkynes, especially terminal alkynes to terminal alkenes remains challenging and poor developed. We demonstrate herein that excellent selective, cost-effective semi-hydrogenation of terminal alkynes can be realized via novel none precious graphene encapsulated Ni@N/C catalyst. The precise regulation of the graphene layer for the encapsulated nano-catalyst Ni@N/C can avoid metal leaching and increase catalytic stability significantly. Nitrogen has strong interaction with Ni nanoparticles, which regulate the activity of Ni towards selective semi-hydrogenation of terminal alkynes. The substrate having un-functionalized as well as functionalized substituents, challenging hydrogenation sensitive functional groups (olefins, ketones), were semi-hydrogenated with excellent conversion (up to 99%) and selectivity (up to 99%).
‘Cookies on a tray’: Superselective Hierarchical Microstructured Poly(L-lactide) Surface As a Decoy For Cells
Authors: Kryszak Bartłomiej , Szustakiewicz Konrad , Dzienny Paulina , Junka Adam , Paleczny Justyna , Szymczyk-Ziółkowska Patrycja , Hoppe Viktoria , Grzymajło Michał , Antończak Arkadiusz
Published: February 2022

In this research we developed a micro-sized hierarchical structures on a poly(L-lactide) (PLLA) surface. The obtained structures consist of round-shaped protrusions with a diameter of ~20 µm, a height of ~3 µm, and the distance between them ~ 30 µm. We explored the effect of structuring PLLA to design a non-cytotoxic material with increased roughness to encourage cells to settle on the surface. The PLLA foils were prepared using the casting melt extrusion technique and were modified using ultra-short pulse irradiation – a femtosecond laser operating at λ=1030 nm. A hierarchical microstructure was obtained resembling 'cookies on a tray'. The cellular response of fibro- and osteoblasts cell lines was investigated. The conducted research has shown that the laser-modified surface is more conducive to cell adhesion and growth (compared to unmodified surface) to such an extent that allows the formation of highly-selectively patterns consisting of living cells. In contrast to eukaryotic cells, the pathogenic bacteria Staphylococcus aureus covered modified and unmodified structures in an even, non-preferential manner. In turn, adhesion pattern of eukaryotic fungus Saccharomyces boulardii resembled that of fibro- and osteoblast cells rather than that of Staphylococcus. The discovered effect can be used for fabrication of personalized and smart implants in regenerative medicine.
Point-of-Need Disposable ELISA System for COVID-19 Serology Testing
Authors: Carrell Cody , Link Jeremy , Jang Ilhoon , Terry James , Scherman Michael , Call Zachary , Panraksa Yosita , Dandy David S. , Geiss Brian J. , Henry Charles
Published: February 2022

A disposable enzyme-linked immunosorbent assay (dELISA) device for ate-home or doctor’s office use was developed to detect SARS-CoV-2 antibodies. Serology testing for SARS-CoV-2 antibodies is currently run using well-plate ELISAs in centralized laboratories. However, the scale of serology testing needed for epidemiological and clinical screening studies will overwhelm existing clinical laboratory resources. Instead, a point-of-need device that can be used at home or in doctor’s offices for COVID-19 serology testing must be developed and is one of four target products prioritized by the World Health Organization. Lateral flow assays are common and easy to use, but lack the sensitivity needed to reliably detect SARS-CoV-2 antibodies in clinical samples. This work describes a disposable ELISA device that is as simple to use as a lateral flow assay, but as sensitive as a well-plate ELISA. The device utilizes capillary-driven flow channels made of transparency films and double-sided adhesive combined with paper pumps to drive flow. The geometry of the channels and storage pads enables automated sequential washing and reagent addition steps with two simple end-user steps. An enzyme label is used to produce a colorimetric signal instead of a nanoparticle label in order to amplify signal and increase sensitivity, while the integrated washing steps decrease false positives and increase reproducibility. Naked-eye detection can be used for qualitative results or a smartphone camera for quantitative analysis. The device can detect antibodies at 2.8 ng/mL from whole blood, which was very close the concentration of detectable target in a well-plate ELISA (1.2 ng/mL). In this study the dELISA system was used to detect SARS-CoV-2 antibodies, but we believe that the device represents a fundamental step forward in point-of-care technology that will enable sensitive detection of many other analytes outside of a centralized laboratory.
Classical Ab Initio Molecular Dynamics Run at an Elevated Temperature is Not a Good Model for the Nuclear Quantum Effects in Water at Ambient Temperature
Authors: Li Chenghan , Paesani Francesco , Voth Gregory A.
Published: February 2022

It is a common practice in ab initio molecular dynamics (AIMD) simulations of water to use an elevated temperature to overcome the over-structuring and slow diffusion predicted by most current density functional theory (DFT) models. The simulation results obtained in this distinct thermodynamic ensemble are then compared with experimental data at ambient temperature based on the rationale that a higher temperature effectively recovers nuclear quantum effects (NQEs) that are missing in the classical AIMD simulations. In this work, we systematically examine the foundation of this assumption for several DFT models as well as for the many-body MB-pol model. We find for the cases studied that a higher temperature does not correctly mimic NQEs at room temperature, which is especially manifest in significantly different three-body correlations as well as dynamics. In many of these cases, the effects of NQEs are exactly the opposite of the effects of carrying out the simulations at an elevated temperature.
Static and Dynamic Statistical Correlations in Water: Comparison of Classical Ab Initio Molecular Dynamics at Elevated Temperature With Path Integral Simulations at Ambient Temperature
Authors: Li Chenghan , Paesani Francesco , Voth Gregory A.
Published: February 2022

It is a common practice in ab initio molecular dynamics (AIMD) simulations of water to use an elevated temperature to overcome the over-structuring and slow diffusion predicted by most current density functional theory (DFT) models. The simulation results obtained in this distinct thermodynamic state are then compared with experimental data at ambient temperature based on the rationale that a higher temperature effectively recovers nuclear quantum effects (NQEs) that are missing in the classical AIMD simulations. In this work, we systematically examine the foundation of this assumption for several DFT models as well as for the many-body MB-pol model. We find for the cases studied that a higher temperature does not correctly mimic NQEs at room temperature, which is especially manifest in significantly different three-molecule correlations as well as hydrogen bond dynamics. In many of these cases, the effects of NQEs are the opposite of the effects of carrying out the simulations at an elevated temperature.
Disruption of water networks is the cause of human/mouse species selectivity in urokinase plasminogen activator (uPA) inhibitors derived from hexamethylene amiloride (HMA)
Authors: El Salamouni Nehad , Buckley Benjamin , Jiang Longguang , Huang Mingdong , Ranson Marie , Kelso Michael , Yu Haibo
Published: February 2022

The urokinase plasminogen activator (uPA) plays a critical role in tumor cell invasion and migration and is a promising anti-metastasis target. 6-Substituted analogs of 5-N,N-(hexamethylene)amiloride (HMA) are potent and selective uPA inhibitors that lack the diuretic and anti-kaliuretic properties of the parent drug amiloride. However, the compounds display pronounced selectivity for human over mouse uPA, thus confounding interpretation of data from human xenografted mouse models of cancer. Here, computational and experimental findings reveal that residue 99 is a key contributor to the observed species selectivity, whereby enthalpically unfavorable expulsion of a water molecule by the 5-N,N-hexamethylene ring occurs when residue 99 is Tyr (as in mouse uPA). Analog 7 lacking the 5-N,N-hexamethylene ring maintained similar water networks when bound to human and mouse uPA and displayed reduced selectivity, thus supporting this conclusion. The study will guide further optimization of dual-potent human/mouse uPA inhibitors from the amiloride class as anti-metastasis drugs.
Huzinaga Projection Embedding for Efficient and Accurate Energies of Systems with Localized Spin-densities
Authors: Graham Daniel , Wen Xuelan , Chulhai Dhabih V. , Goodpaster Jason
Published: February 2022

We demonstrate the accuracy and efficiency of the restricted open-shell and unrestricted formulation of the absolutely localized Huzinaga projection operator embedding method. Restricted open-shell and unrestricted Huzinaga projection embedding in the full system basis is formally exact to restricted open-shell and unrestricted Kohn-Sham density functional theory, respectively. By utilizing the absolutely localized basis, we significantly improve the efficiency of the method, while maintaining high accuracy. The open-shell embedding method is shown to calculate electronic energies of a variety of systems to within 1 kcal/mol accuracy of the full system wave function result. For certain highly localized reactions, such as spin transition energies on transition metals, we find that very few atoms are necessary to include in the wave function region, in order to achieve desired accuracy. Here we apply our method to several representative examples such as spin splitting energies, catalysis on transition metals, and radical reactions.
Preparation of Multicore Colloidosomes: Nanoparticle-Assembled Capsules with Adjustable Size, Internal Structure, and Functionalities for Oil Encapsulation
Authors: Brossault David F.F. , McCoy Thomas M. , Routh Alexander F.
Published: February 2022

Colloidosomes, also known as Pickering emulsion capsules, have attracted attention for encapsulation of hydrophilic and hydrophobic actives. However, current preparation methods are limited to single core structures and require the use of modified/engineered nanoparticles for forming the shell. Here, we report a fast, simple, and versatile method for producing multi-oil core silica colloidosomes via salt-driven assembly of purely hydrophilic commercial nanoparticles dispersed within an Oil-In-Water-In-Oil (O/W/O) double emulsion template. The internal structure and overall diameter of the capsules can be adjusted by altering the primary and secondary emulsification conditions. With this approach, 7 to 35 µm diameter multicore colloidosomes containing 0.9 to 4.2 µm large oil cores were produced. The capsules can easily be functionalized depending on the type of nanoparticles used in the preparation process. Here, metal oxide nanoparticles, such as Fe3O4, TiO2 and ZnO, were successfully incorporated within the structure, conferring specific functional properties (i.e. magnetism, photocatalysis) to the final microcapsules. These capsules can also be ruptured using ultrasound, enabling easy access to the internal core environments. Therefore, we believe this work offers a promising approach for producing multicore colloidosomes with adjustable structure and functionalities for the encapsulation of hydrophobic actives.
The Contrasting Role of Water and Acid Within Organic Phase Amphiphile Aggregation
Authors: Sadhu Biswajit , Clark Aurora E.
Published: February 2022

The self-assembly of amphiphiles is often modified by the presence of co-solutes and significant study has examined this behavior in aqueous systems. Much less is known about the role of polar co-solutes upon amphiphile aggregation within non-polar media, however such conditions are relevant to a variety of industrial processes - not the least of which are separations systems like those found in liquid-liquid extraction (LLE). Therein, surface active amphiphiles extract water, acid, and other solutes of interest. Intriguing increases to amphiphile aggregates have been experimentally observed upon water and acid extraction, however a myriad of competitive intermolecular interactions have thus far prevented a fundamental understanding of the individual and dual role of these solutes upon amphiphile self-assembly. Toward this end, this work employs classical molecular dynamics and graph theory analyses to deconstruct the individual affects of water and nitric acid upon the self-assembly of N,N,N',N'-tetraoctyl-3-oxapentanediamide (TODGA), a prevalent amphiphile extractant used in metal ion separations. In the absence of acid, and at low water concentration, H2O is found to promote local dimer and trimer formation of TODGA, however as [H2O]org increases, the preferential solvation of water with itself causes the formation of large water clusters that serve to link large TODGA clusters on the periphery (causing extended aggregation). Addition of HNO3 to the humid solutions disrupts the water hydrogen bond network and inhibits the formation of large water clusters - thus preventing extended aggregation behavior. We rationalize the prior experimental observations as being attributed primarily to the role of water in the self-assembly of TODGA rather than co-extracted HNO3, thus providing valuable new insight into the means by which extractant aggregation can be tuned within LLE processes. In addition, this work differentiates the role of polar solutes upon amphiphile self-assembly via their individual hydrogen bonding capabilities and competitive interactions that disrupt preferred solvation environments.
The Contrasting Role of Water and Acid Within Organic Phase Amphiphile Aggregation
Authors: Sadhu Biswajit , Clark Aurora E.
Published: February 2022

Hypothesis: Amphiphile self-assembly in non-polar media is often enhanced by polar co-solutes, as observed upon amphiphile mediated transport of water and acid into organic solution. Such co-extraction precludes understanding the individual roles of polar solutes upon self-assembly. Using this liquid-liquid extraction (LLE) system as a test-bed, we hypothesize that co-solute competition and hydrogen bond (HB) characteristics cause different size/shape distributions of assembled amphiphiles and alter self-assembly mechanisms in non-polar solvents. Experiments: Concentration dependent classical molecular dynamics simulation and intermolecular network analyses identified the correlating relationships between HB properties of H2O and HNO3 upon the aggregation of N,N,N,N-tetraoctyl-3-oxapentanediamide (TODGA), a prevalent LLE amphiphile extractant. Findings: Concentration dependent competition of hydrogen bonding fundamentally impacts amphiphile self-assembly in non-polar media. H2O bridges TODGA and enhances self-assembly, however as [H2O]org increases, preferential self-solvation leads to large (H2O)n clusters that cause TODGA clusters to sorb to the (H2O)n periphery and form extended aggregation. HNO3 restricts the (H2O)n size by disrupting the HB network. At large [H2O]org, HNO3 modulates TODGA self-assembly from extended to local aggregation. We attribute prior experimental observations to the role of water rather than co-extracted HNO3, thus providing valuable new insight into the means by which extractant aggregation can be tuned.
Catalyzed Reaction of Isocyanates (RNCO) with Water
Authors: Wolf Mark , Vandezande Jonathon , Schaefer Henry
Published: February 2022

The reactions between substituted isocyanates (RNCO) and other small molecules (e.g. water, alcohols, and amines) are of significant industrial importance, particularly for the development of novel polyurethanes and other useful polymers. We present very high-level ab initio computations on the HNCO + H2O reaction, with results targeting the CCSDT(Q)/CBS//CCSD(T)/cc-pVQZ level of theory. Our results affirm that hydrolysis can occur across both the N=C and C=O bonds of HNCO via concerted mechanisms to form carbamate or imidic acid with 0 K enthalpy barrier heights of 38.5 and 47.5 kcal mol^-1 A total of 24 substituted RNCO + H2O reactions were studied. Geometries obtained with a composite method and refined with CCSD(T)/CBS single point energies determine that substituted RNCO species have a significant influence on these barrier heights, with an extreme case like fluorine lowering both barriers by close to 20 kcal mol^-1 and most common alkyl substituents lowering both by approximately 4 kcal mol^-1. Natural Bond Orbital (NBO) analysis provides evidence that the predicted barrier heights are strongly associated with the occupation of the in-plane C-O* orbital of the RNCO reactant. Key autocatalytic mechanisms are considered in the presence of excess water and RNCO species. Additional waters (one or two) are predicted to lower both barriers significantly at the CCSD(T)/aug-cc-pV(T+d)Z level of theory with strongly electron withdrawing RNCO substituents also increasing these effects, similar to the uncatalyzed case. The 298 K Gibbs energies are only marginally lowered by a second catalyst water molecule, indicating that the decreasing 0 K enthalpy barriers are offset by the loss of translational entropy with more than one catalyst water. Two-step 2RNCO + H2O mechanisms are characterized for the formation of carbamate and imidic acid. The second step of these two pathways exhibits the largest barrier and presents no clear pattern with respect to substituent choice. Our results indicate that an additional RNCO molecule might catalyze imidic acid formation but have less influence on the efficiency of carbamate formation. We expect that these results lay a firm foundation for the experimental study of substituted isocyanates and their relationship to the energetic pathways of related systems.
Rational Design of Stable Four-Electron-Accepting Carbonyl-N-methylpyridinium Species for High-Performance Lithium-Ion Batteries
Authors: He Xiaoming , Wang Xiujuan , Xue Wenhao , Gao Guangyuan , Chen Ling , Baumgartner Thomas
Published: February 2022

Development of novel organics that exhibit multiple and stable redox states, limited solubility and improved conductivity is a highly rewarding direction for improving the performance of lithium-ion batteries (LIBs). As biologically derived organic molecules, carbonylpyridinium compounds have desirable and tunable redox properties, making them suitable candidates for battery applications. In this work, we report a structural evolution of carbonylpyridinium-based redox-active organics, from 2-electron accepting BMP to 4-electron accepting small, conjugated molecules (1, 2), and then to the corresponding conjugated polymers (CP1, CP2). Through suppression of dissolution and increasing electrochemical conductivity, the LIBs performance can be gradually enhanced. At a relatively high current of 0.5 A g-1, high specific capacities for 1 (100 mAh g-1), 2 (260 mAh g-1), CP1 (360 mAh g-1) and CP2 (540 mAh g-1) can be reached after 240 cycles. Particularly, the rate performance and cycling stability of CP2 surpasses many reported commercial inorganic and organic electrode materials. This work provides a promising new carbonylpyridinium-based building block featured with multiple redox centers, on the way to high performance Li-organic batteries.
Data-driven design of bi-selective OSDAs for intergrowth zeolites
Authors: Schwalbe-Koda Daniel , Corma Avelino , Román-Leshkov Yuriy , Moliner Manuel , Gómez-Bombarelli Rafael
Published: February 2022

Zeolites are inorganic materials with wide industrial applications due to their topological diversity. Tailoring confinement effects in zeolite pores, for instance by crystallizing intergrown frameworks, can improve their catalytic and transport properties, but controlling zeolite crystallization often relies on heuristics. In this work, we use computational simulations and data mining to design organic structure-directing agents (OSDAs) to favor the synthesis of intergrown zeolites. First, we propose design principles to identify OSDAs which are selective towards both end members of the disordered structure. Then, we mine a database of hundreds of thousands of zeolite-OSDA pairs and downselect OSDA candidates to synthesize known intergrowth zeolites such as CHA/AFX, MTT/TON, and BEC/ISV. The computationally designed OSDAs balance phase competition metrics and shape selectivity towards the frameworks, thus bypassing expensive dual-OSDA approaches typically used in the synthesis of intergrowths. Finally, we propose potential OSDAs to obtain hypothesized disordered frameworks such as AEI/SAV. This work may accelerate zeolite discovery through data-driven synthesis optimization and design.
Wetting Behavior of Zirconia Nanotubes
Authors: Vakamulla Raghu Swathi Naidu , Killian Manuela Sonja
Published: February 2022

In this work, we investigate the wettability of ZrO2 nanotubes (ZrNT) synthesized via electrochemical anodization of Zirconium. The ZrNT surface shows superhydrophilic behavior while the octadecylphosphonic acid (C18H37PO(OH)2) modified surface shows superhydrophobic behavior. We demonstrate that the wetting properties are independent of ZrO2 nanotube geometry and length.
On the Mechanistic Origins of the pH-Dependency in Au-Catalyzed Glycerol Electro-Oxidation: Insight from First Principles Calculations
Authors: Verma Anand Mohan , Melander Marko , Honkala Karoliina
Published: February 2022

Electrocatalytic oxidation of glycerol (EOG) is an attractive approach to convert surplus glycerol to value-added products. Experiments have shown that EOG activity and selectivity depend on the electrocatalyst, but also on the electrode potential, the pH, and the electrolyte. For broadly employed gold (Au) electrocatalysts, experiments have demonstrated high EOG activity under alkaline conditions with glyceric acid as a primary product, whereas under acidic and neutral conditions Au is rather inactive producing only small amounts of dihydroxyacetone. In the present computational work, we have performed an extensive mechanistic study to understand the pH- and potential-dependency of Au-catalyzed EOG. Our results show that activity and selectivity are controlled by the presence of surface-bound hydroxyl groups. Under alkaline conditions and close to the experimental onset potential, modest OH coverage is preferred according to our constant potential calculations. This indicates that both Au(OH)ads and Au can be active sites and they cooperatively facilitate the thermodynamically and kinetically feasible formation of glyceric acid thus explaining the experimentally observed high activity and selectivity. Under acidic conditions, hydroxide coverage is negligible and the dihydroxyacetone emerges as the favored product. Calculations predict slow reaction kinetics, however, which explains the low activity and selectivity towards dihydroxyacetone reported in experiments. Overall, our findings highlight that computational studies should explicitly account for pH and coverage effects under alkaline conditions for electrocatalytic oxidation reactions to reliably predict electrocatalytic behaviour.
On the Mechanistic Origins of the pH-Dependency in Au-Catalyzed Glycerol Electro-Oxidation: Insight from First Principles Calculations
Authors: Verma Anand Mohan , Laverdure Laura , Melander Marko , Honkala Karoliina
Published: February 2022

Electrocatalytic oxidation of glycerol (EOG) is an attractive approach to convert surplus glycerol to value-added products. Experiments have shown that EOG activity and selectivity depend on the electrocatalyst, but also on the electrode potential, the pH, and the electrolyte. For broadly employed gold (Au) electrocatalysts, experiments have demonstrated high EOG activity under alkaline conditions with glyceric acid as a primary product, whereas under acidic and neutral conditions Au is almost inactive producing only small amounts of dihydroxyacetone. In the present computational work, we have performed an extensive mechanistic study to understand the pH- and potential- dependency of Au-catalyzed EOG. Our results show that activity and selectivity are controlled by the presence of surface-bound hydroxyl groups. Under alkaline conditions and close to the experimental onset potential, modest OH coverage is preferred accord- ing to our constant potential calculations. This indicates that both Au(OH)ads and Au can be active sites and they cooperatively facilitate the thermodynamically and kinetically feasible formation of glyceric acid thus explaining the experimentally observed high activity and selectivity. Under acidic conditions, hydroxide coverage is negligi- ble and the dihydroxyacetone emerges as the favored product. Calculations predict slow reaction kinetics, however, which explains the low activity and selectivity towards dihydroxyacetone reported in experiments. Overall, our findings highlight that com- putational studies should explicitly account for pH and coverage effects under alkaline conditions for electrocatalytic oxidation reactions to reliably predict electrocatalytic behaviour.
First-Principles Plane-Wave-Based Exploration of Cathode and Anode Materials for Li and Na-ion Batteries
Authors: Ertural Christina , Stoffel Ralf , Müller Peter Christian , Vogt Christian Alexander , Dronskowski Richard
Published: February 2022

We present a first-principles study based on plane-wave derived Löwdin population analysis and other local bonding descriptors to investigate cathode and anode materials for lithium and sodium ion batteries. By comparing the Löwdin charges of common graphite-based anode materials such as LiC6 and LiC12 to other phases such as salts of dicyanamide and nanoporous carbon-based compounds, new conclusions of an improved intercalation behavior of the latter are derived. In addition, we explore the stability of the dicyanamide salts concerning the removal of Li and Na atoms from the compounds with some of them resulting in dimerized structures. In particular, having a look at the different kinds of bonds and the corresponding covalency indicators reveals new insights into the change of the bonds during dimerization. Considering the generally high thermal stability of metal dicyanamide salts, which are solid at room temperature, their electrochemical activity as well as non-toxicity of alkali metal-based compounds, these materials are potential alternatives to commercially available electrodes, particularly for sodium ion batteries, to pristine graphite-based anode materials.
Secondary Phosphine Oxide-Activated Nickel Catalysts for Site-Selective Alkene Isomerization and Remote Hydrophosphination
Authors: Huang Lin , Lim En Qi , Koh Ming Joo
Published: February 2022

Catalytic systems that are readily modifiable to achieve olefin migration or remote functionalization are highly sought-after in chemical synthesis. Here, we show that the combination of a commercially available nickel(II) pre-catalyst and a secondary phosphine oxide ligand enables site- and stereoselective alkene transposition for up to nine double-bond migrations within terminal and internal olefins under mild reductive conditions. Substrates bearing diverse functionalities including Brønsted acidic and reducible carbonyl groups are tolerated. Mechanistic and spectroscopic studies revealed the in situ generation of a catalytically active nickel-hydride species triggered by oxidative addition of the phosphine oxide. The reaction is amenable to regioconvergent isomerization as well as β-selective remote hydrophosphination when stoichiometric secondary phosphine oxide/base were employed.
A close-up look at the chemical space of commercially available building blocks for medicinal chemistry
Authors: Zabolotna Yuliana , Volochnyuk Dmitriy , Ryabukhin Sergey , Horvath Dragos , Gavrylenko Kostiantyn , Marcou Gilles , Moroz Yurii , Oksiuta Olexandr , Varnek Alexandre
Published: February 2022

The ability to efficiently synthesize desired compounds can be a limiting factor for chemical space exploration in drug discovery. This ability is conditioned not only by the existence of well-studied synthetic protocols but also by the availability of corresponding reagents, so-called building blocks (BB). In this work, we present a detailed analysis of the chemical space of 400K purchasable BB. The chemical space was defined by corresponding synthons – fragments contributed to the final molecules upon reaction. They allow an analysis of BB physicochemical properties and diversity, unbiased by the leaving and protective groups in actual reagents. The main classes of BB were analyzed in terms of their availability, rule-of-two-defined quality, and diversity. Available BBs were eventually compared to a reference set of biologically relevant synthons derived from ChEMBL fragmentation, in order to illustrate how well they cover the actual medicinal chemistry needs. This was performed on a newly constructed universal generative topographic map of synthon chemical space, allowing to visualize both libraries and analyze their overlapping and library-specific regions.
1- and 2-Azetines via Visible Light-Mediated [2+2]-Cycloadditions of Alkynes and Oximes
Authors: Schindler Corinna , Wearing Emily , Blackmun Dominique , Becker Marc
Published: February 2022

Azetines, four-membered unsaturated nitrogen-containing heterocycles, hold great potential for drug design and development, but remain underexplored due to challenges associated with their synthesis. We report an efficient, visible light-mediated approach to-wards 1- and 2-azetines relying on alkynes and the unique triplet state reactivity of oximes, specifically 2-isoxazolines. While 2-azetine products are accessible upon intermolecular [2+2]-cycloaddition via triplet energy transfer from a commercially available iridi-um photocatalyst, the selective formation of 1-azetines proceeds upon a second, consecutive, energy transfer process. Mechanistic studies are consistent with a stepwise reaction mechanism via N-O bond homolysis following the second energy transfer event to result in the formation of 1-azetine products. Characteristic for this method is its operational simplicity, mild conditions and modular approach that allows for the synthesis of functionalized azetines and tetrahydrofurans via in situ hydrolysis from readily available precursors.
Tuning diazonium modification of gold nanoparticles for fuel cell application
Authors: Aghajani Atieh , Santoni Marie-Pierre , Mirzaei Peyman , Mohamed Ahmed , CHEHIMI Mohamed , Jouini Mohamed
Published: February 2022

Products made from alcohol oxidation are very important and used in food industry, pharmaceuticals and dryers to name but a few. In this regard, precious metals such as gold operate in various shapes and sizes as effective catalysts for the oxidation of alcohols. In this work, 20 nm-sized gold nanoparticles were synthesized and modified with either 4-carboxybenzenediazonium tetrafluoroborate (AB) (single salt catalyst) or a mixture of the latter with 3,5-dimethylbenzenediazonium tetrafluoroborate (AB-DMB, double-salt catalyst). The relative concentrations of the diazonium salts were tuned in order to maintain the electrocatalytic property of the arylated gold nanoparticles in the electro-oxidation of ethanol. The physicochemical properties (size, aryl layer thickness and composition) and electrocatalytic performances of the capped gold nanoparticles (in single and double salt catalyst systems) were investigated by means of TEM, XPS, UV-visible, TGA-DTA and electrochemistry. The aryl capping layer thickness is below 1 nm when the total salt concentration was 510-5 M, without any significant loss of current compared to pure gold nanoparticles. For 1 μL of pristine or arylated Au NPs, coated on 0.07 cm² glassy carbon electrode disk, we achieved a low oxidation potential of 200 mV and high current ethanol oxidation peak intensity levelling off at ~80 μA for the single diazonium arylation. It is demonstrated that dilution of the carboxylic acid-functionalized diazonium is more important than mixing this compound with 3,5-dimethylbenzene diazonium salt at equal total concentration. The dual arylation strategy returned lower ethanol oxidation intensity likely due to hydrophic effect imparted by the 3,5-dimethylphenyl groups, thus hindring access of ethanol to the nanocatalyst surface. This work demonstrates that arylated gold nanoparticles are unique nanocatalysts for ethanol oxidation reaction, with remarkable performances. This electrocatalytic performance of the nanoparticles was maintained through the use of finely tuned aryl capping layer. The strategy opens avenues for other arylated electrocatalysts and uses thereof.
Efficiently transforming from values of a function on a sparse grid to basis coefficients
Authors: CARRINGTON Tucker , Wodraszka Robert
Published: February 2022

In many contexts it is necessary to determine coefficients of a basis expansion of a function ${f}\left(x_1, \ldots, x_D\right) $ from values of the function at points on a sparse grid. Knowing the coefficients, one has an interpolant or a surrogate. For example, such coefficients are used in uncertainty quantification. In this chapter, we present an efficient method for computing the coefficients. It uses basis functions that, like the familiar piecewise linear hierarchical functions, are zero at points in previous levels. They are linear combinations of any, e.g. global, nested basis functions $\varphi_{i_k}^{\left(k\right)}\left(x_k\right)$. Most importantly, the transformation from function values to basis coefficients is done, exploiting the nesting, by evaluating sums sequentially. When the number of functions in level $\ell_k$ equals $\ell_k$ (i.e. when the level index is increased by one, only one point (function) is added) and the basis function indices satisfy ${\left\lVert\mathbf{i}-\mathbf{1}\right\lVert_1 \le b}$, the cost of the transformation scales as $\mathcal{O}\left(D \left[\frac{b}{D+1} + 1\right] N_\mathrm{sparse}\right)$, where $N_\mathrm{sparse}$ is the number of points on the sparse grid. We compare the cost of doing the transformation with sequential sums to the cost of other methods in the literature.
Ligand Conversion in Nanocrystal Synthesis: The Oxidation of Alkylamines to Fatty Acids by Nitrate
Authors: Calcabrini Mariano , Van den Eynden Dietger , Sánchez Ribot Sergi , Pokratath Rohan , Llorca Jordi , De Roo Jonathan , Ibáñez Maria
Published: February 2022

Ligands are a fundamental part of nanocrystals. They control and direct nanocrystal syntheses, and provide colloidal stability. Bound ligands also affect the nanocrystals’ chemical reactivity and electronic structure. Surface chemistry is thus crucial to understand nanocrystal properties and functionality. Here, we investigate the synthesis of metal oxide nanocrystals (CeO2-x, ZnO, and NiO) from metal nitrate precursors, in the presence of oleylamine ligands. Surprisingly, the nanocrystals are capped exclusively with a fatty acid instead of oleylamine. Analysis of the reaction mixtures with nuclear magnetic resonance spectroscopy revealed several reaction byproducts and intermediates that are common to the decomposition of Ce, Zn, Ni and Zr nitrate precursors. Our evidence supports the oxidation of alkylamine and formation of a carboxylic acid, thus unraveling this counterintuitive surface chemistry.