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At least 217 records · Page 12

Investigation of the role of hydrogen molecules in 1D simulation of divertor detachment

The role of neutral and charged hydrogenic molecules in detached regimes of tokamak plasmas is investigated using a simplified 1D numerical model. Using MAST Upgrade like conditions, simulations are implemented to study the rollover of target flux Γ in upstream density scan. It is found that if H 2 and H 2 + are considered in simulations a lower target temperature and a larger upstream density will be required to trigger divertor detachment under the same input power and particle flux, and the critical detachment threshold (the critical ratio of upstream static pressure to the power entering the recycling region) is found to be $^{ρ_{up}}_{ρ_{recl}}$ ~ 8.1 NMW -1 at rollover. Molecule–plasma interactions are found to be as crucial as atom–plasma interactions during divertor detachment, both of which account for the majority of plasma momentum loss in the cases studied here. Further analysis of the momentum loss decomposition shows molecule-plasma elastic collisions dominate molecule-plasma interactions, while molecular charge exchange cannot effectively reduce plasma momentum. In terms of H alpha emission, a strong rise of H alpha signal is found to be due to molecular excitation channels when the upstream density further increases after rollover.

SD1D↗

Opportunities for fundamental physics research with radioactive molecules

Molecules containing short-lived, radioactive nuclei are uniquely positioned to enable a wide range of scientific discoveries in the areas of fundamental symmetries, astrophysics, nuclear structure, and chemistry. Recent advances in the ability to create, cool, and control complex molecules down to the quantum level, along with recent and upcoming advances in radioactive species production at several facilities around the world, create a compelling opportunity to coordinate and combine these efforts to bring precision measurement and control to molecules containing extreme nuclei. In this paper, we review the scientific case for studying radioactive molecules, discuss recent atomic, molecular, nuclear, astrophysical, and chemical advances which provide the foundation for their study, describe the facilities where these species are and will be produced, and provide an outlook for the future of this nascent field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An initial investigation of accuracy required for the identification of small molecules in complex samples using quantum chemical calculated NMR chemical shifts

The majority of primary and secondary metabolites in nature have yet to be identified, representing a major challenge for metabolomics studies that currently require reference libraries from analyses of authentic compounds. Using currently available analytical methods, complete chemical characterization of metabolomes is infeasible for both technical and economic reasons. For example, unambiguous identification of metabolites is limited by the availability of authentic chemical standards, which, for the majority of molecules, do not exist. Computationally predicted or calculated data are a viable solution to expand the currently limited metabolite reference libraries, if such methods are shown to be sufficiently accurate. For example, determining nuclear magnetic resonance (NMR) spectroscopy spectra in silico has shown promise in the identification and delineation of metabolite structures. Many researchers have been taking advantage of density functional theory (DFT), a computationally inexpensive yet reputable method for the prediction of carbon and proton NMR spectra of metabolites. However, such methods are expected to have some error in predicted 13 >C and 1 H NMR spectra with respect to experimentally measured values. This leads us to the question–what accuracy is required in predicted 13 C and 1 H NMR chemical shifts for confident metabolite identification? Using the set of 11,716 small molecules found in the Human Metabolome Database (HMDB), we simulated both experimental and theoretical NMR chemical shift databases. We investigated the level of accuracy required for identification of metabolites in simulated pure and impure samples by matching predicted chemical shifts to experimental data. We found 90% or more of molecules in simulated pure samples can be successfully identified when errors of 1 H and 13 C chemical shifts in water are below 0.6 and 7.1 ppm, respectively, and below 0.5 and 4.6 ppm in chloroform solvation, respectively. In simulated complex mixtures, as the complexity of the mixture increased, greater accuracy of the calculated chemical shifts was required, as expected. However, if the number of molecules in the mixture is known, e.g., when NMR is combined with MS and sample complexity is low, the likelihood of confident molecular identification increased by 90%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Performance Advantaged Biobased Chemicals Utilizing Bioprivileged Molecules

Two technology areas were advanced; a) novel molecules with improved performance in the end use application of organic corrosion inhibitors and flame retardant nylon polymers and b) development of a systematic process for identifying biomass-derived molecules with improved performance in end use applications. In total 17 novel organic corrosion inhibitors were identified that had significantly better performance than the commercial reference organic corrosion inhibitor and 7 novel nylons were synthesized with improved flame retardant properties relative to standard nylon-6,6. While an end-to-end systematic process for identifying biomass-derived molecules with improved end use performance was not completed, important progress was made computational tools for mining chemical structures from the literature and databases as well as establishing reaction network generation algorithms to aid in the discovery of novel molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Statistically-driven Experimental Design to Improve Reference-free Quantification of Small Molecules by Liquid Chromatography-Mass Spectrometry

Non-targeted analysis of small molecules and metabolites in unknown, complex samples using liquid chromatography-tandem mass spectrometry remains challenging. One of the main bottlenecks is the extensive unannotated regions of metabolomics mass spectrometry data, resulting in knowledge gaps. Small molecule annotation in mass spectrometry data has conventionally relied on reference standards and libraries for compound identification and confirmation, which can constrain compound identification to those molecules already known, thus limiting the ability to discover new knowledge and new markers. Retention time prediction can facilitate and expedite unknown compound identification in non-targeted analysis of complex metabolomics samples. Additionally, accurate retention time predictions can also inform sample mixture design for LC-MS/MS analyses. However, current machine learning-based methods for retention time prediction are typically developed for specific chromatographic platforms and are not generalizable across scales. And while technologies and methods to improve reference-free metabolite identification for more comprehensive annotation of unknowns has received much attention, development of the same for quantitation without reference standards has been much more limited, despite its importance in toxicological, environmental, food safety, forensics, and clinical applications. We believe that a reference-free quantitation strategy that exploits mass spectrometry data already collected for reference-free identification can provide much more insight on unknowns, and move the metabolomics field for more complete unknowns characterization. As such, we pursue two efforts to improve upon current state-of-the-art methods in non-targeted analysis: (1) machine learning-based retention time prediction and (2) statistical design of experiments framework for reference-free quantitation. In this work, we develop and demonstrate (1) a generalizable retention time prediction capability across chromatographic conditions and scales, and (2) a statistical design-based framework for response factor contribution elucidation and reference-free quantitation. Evaluation of our retention time prediction model, PrediToR, showed approximately 24% improvement over current models, and we observed approximately 10X improvement in concentration estimation accuracy from our statistical design-based response factor model over a primarily ionization efficiency-based model. We expect that future efforts to improve upon these new capabilities will further advance non-targeted analysis of small molecules towards truly reference-free metabolomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser Spectroscopy of Exotic Atoms and Molecules Containing Octupole-Deformed Nuclei

This project investigated the nuclear, atomic, and molecular structure of exotic atoms and molecules containing actinide isotopes. These short-lived radioactive systems are challenging to produce and study in the laboratory, yet they offer unique opportunities for fundamental science. These nuclei are predicted to exhibit pear-shaped (octupole) deformation, a rare collective nuclear behavior that dramatically enhances their sensitivity to fundamental physics phenomena such as time-reversal- and parity-violating effects. Such enhancements make them ideal probes for exploring open questions in our understanding of the universe such as the origin of the matter–antimatter asymmetry of the universe. To realize these measurements, the project led the development of a new laser spectroscopy experiment at MIT, and later commissioned at the Facility for Rare Isotope Beams (FRIB) at Michigan State University: the Resonance Ionization Spectroscopy Experiment (RISE). RISE combines the spectroscopic precision of collinear laser spectroscopy with the sensitivity of particle-detection techniques, enabling measurements of rare isotopes produced at rates as low as a few ions per second. The beamline was designed, built, and installed, and was successfully commissioned at FRIB during the grant period. RISE is now a permanent capability of the FRIB facility, and has produced several results on the study of rare atoms and molecules for nuclear structure and fundamental symmetries. In parallel with the FRIB program, the project contributed to the first precision laser-spectroscopy measurements of short-lived radioactive molecules. Working with international collaborators at CERN's ISOLDE facility, the team conducted pioneering experiments on radium monofluoride (RaF) and actinium monofluoride (AcF). The results from this work have been published in major journals of science, including Nature, Science, Nature Physics, Nature Communications, and Physical Review Letters. These findings have guided future experiments on the laser cooling of radioactive molecules, opening a new platform for precision tests of fundamental symmetries.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Symmetry‐Breaking Strategy Yields Dopant‐Free Small Molecule Hole Transport Materials for Inorganic Perovskite Solar Cells with 20.58% Efficiency and Outstanding Stability

Abstract Inorganic perovskites are known for their excellent photothermal stability; however, the photothermal stability of all‐inorganic n‐i‐p perovskite solar cells (PSCs) is compromised due to ion diffusion and free radical‐induced degradation caused by the use of doped spiro‐OMeTAD hole transport materials (HTMs). In this study, two isomeric donor–acceptor–donor (D–A–D) type small molecules, namely HBT and HiBT, were developed and used as dopant‐free HTMs, using 2,1,3‐benzothiadiazole or benzo[d][1,2,3]thiadiazole as acceptor moieties. The HiBT molecule, with its symmetry‐breaking features, exhibits a large dipole moment, enhanced coordination‐active sites, and a well‐aligned energy level structure, all of which contribute to passivating perovskite surface defects and improving free charge separation. As a result, inorganic CsPbI 3 PSCs with HiBT HTM achieved an impressive power conversion efficiency (PCE) of 20.58%, the highest reported for dopant‐free HTM‐based inorganic PSCs. Moreover, the enhanced hydrophobic properties of HiBT molecules, coupled with their ability to passivate perovskite surface defects, contribute to significantly improved device stability. The unencapsulated devices based on HiBT HTM retained over 83% and 80% of their initial efficiency after being stored at 85 °C for 50 days and undergoing maximum power point (MPP) tracking at 85 °C for 1100 h, respectively. These results highlight that the symmetry‐breaking strategy is an exceptionally effective approach for designing efficient, dopant‐free small molecule HTMs, significantly contributing to both the high efficiency and enhanced stability of all‐inorganic PSCs.

Chemistry↗

Insights from 20 years of the Molecule of the Month

For 20 years, Molecule of the Month articles have highlighted the functional stories of 3D structures found in the Protein Data Bank (PDB). The PDB is the primary archive of atomic structures of biological molecules, currently providing open access to more than 150,000 structures studied by researchers around the world. The wealth of knowledge embodied in this resource is remarkable, with structures that allow exploration of nearly any biomolecular topic, including the basic science of genetic mechanisms, mechanisms of photosynthesis and bioenergetics, and central biomedical topics like cancer therapy and the fight against infectious disease. The central motivation behind the Molecule of the Month is to provide a user-friendly introduction to this rich body of data, charting a path for users to get started with finding and exploring the many available structures. The Molecule of the Month and related materials are updated regularly at the education portal PDB-101 (http://pdb101.rcsb.org/), offering an ongoing resource for molecular biology educators and students around the world.

59 BASIC BIOLOGICAL SCIENCES↗

Traction-separation response of bilayer graphene interfaces: The role of an intercalated single atomic layer of water molecules and hydroxyl groups

Molecular dynamics simulations of the normal and shear traction-separation response of dry and wet bilayer graphene interfaces were performed. The influence of a single, atomic layer of water molecules sandwiched between graphene layers and hydroxyl functionalization on one or both layers were investigated. Hydroxyl groups provided a shielding effect during normal separation while favoring stick-slip friction under sliding conditions. The single, atomic layer of water molecules confined between hydrophilic and asymmetric hydrophobic/hydrophilic surfaces was found to ease sliding friction. The mechanisms arose from the balance between the attractive and repulsive graphene/water interactions through bridges of single water molecules between the two surfaces and the structure of the water monolayer under confinement for which an out-of-plane water/water hydrogen bond network could not be developed. The single, atomic layer of water molecules reduced the sliding friction the most when both surfaces were hydrophilic and lowered the sliding friction of the asymmetric hydrophobic/hydrophilic interfaces to that when both surfaces were hydrophobic. An optimal hydroxyl surface coverage of less than 10% may exist for efficient water lubrication, with diminishing effect with increasing number of hydroxyl groups. Finally, the findings offer a design strategy for assembling bilayer graphene interfaces with tailored friction and sliding contact properties.

36 MATERIALS SCIENCE↗

BODIPY based A-D-A molecules: Effect of CF3 group substitution at meso phenyl group

Two pairs of A-D-A molecules have been created with fluorene and benzodithiophene as the central donor subunits and terminal BODIPY units, functionalized with either a 4-methylphenyl or 4-trifluoromethylphenyl group at the meso position. The effect of the para substituent of the meso phenyl group on the photophysical properties of these molecules is studied through steady state absorption and fluorescence spectroscopy as well as femtosecond transient absorption and time resolved fluorescence spectroscopy techniques. Applicability of these molecules as donors in solution processed solar cell active layers was investigated through time resolved microwave conductivity measurements on blends with PC60BM acceptor, which shows a varying yield of charge transfer with choice of substituent. Transient absorption spectroscopy is then employed to investigate the role of the 4-trifluoromethylphenyl group in altering the efficiency of charge transfer from these A-D-A molecules to PC60BM. The results show a consistent picture of picosecond charge transfer and a component of a few hundred ps geminate recombination that results in a small yield of long-lived free charges optimized for the methylphenyl derivatives.

36 MATERIALS SCIENCE↗

Machine learning for the redox potential prediction of molecules in organic redox flow battery

Here, organic redox flow batteries (ORFB) are recognized as an innovative technology for the large-scale storage of renewable energy. The redox potential of organic redox-active molecules plays a vital role in their performance. Advanced screening techniques like high-throughput experiment and machine learning (ML) have significantly enhanced organic material performance and transformed the field of ORFB. However, the scarcity of experimental data poses a considerable challenge for ML model development in this domain. In our study, we developed lightweight graph-based Gaussian process regression (GPR) models with GPU-accelerated marginalized graph kernel and hybrid kernel to predict the redox potentials of organic redox-active molecules for ORFBs, specifically focusing on small datasets. To evaluate model accuracy, we created a new experimental database of organic redox-active molecules by the data from hundreds of published papers and assembled previous computational datasets. We also considered some key parameters, such as pH conditions and solvent type, to assess their impact on redox potential prediction. Our GPR model predicted redox potentials with high accuracy across all datasets using minimal training data. The study provides powerful tools for molecule screening and design and delivers valuable guidance on designing training datasets for costly experiments.

25 ENERGY STORAGE↗

Line coupling and line mixing effects on calculated widths of symmetric-top molecules with the k-degeneracy: A theoretical study of N 2 -, O 2 -, and air-broadened lines of CH 3 I

Calculations of the N 2 -, O 2 -, and air-broadened widths, together with their temperature dependence exponents have been made for transitions of CH 3 I in the ν 5 and ν 6 bands. The calculations are based on a semi-classical line shape formalism developed by the current authors through modifying and refining the Robert-Bonamy formalism. In recent years, we have applied this formalism for linear molecules, symmetric-top molecules with inversion symmetry, and asymmetric-top molecules. For symmetric-top molecules with the k degeneracy such as CH 3 I, the formalism has a new feature. In this case, one should consider each of the CH 3 I transitions labeled by k i or f ≠ 0 as a doublet. Then, one needs to consider the effects of the line mixing process between these two components. Furthermore, comparisons of our theoretical predictions with some data available demonstrate a very reasonable agreement. Finally, we propose new experiments at higher perturber pressures that would enable one to check the theoretically calculated relaxation matrices and to extend the analysis to the inter-doublet mixing effects.

74 ATOMIC AND MOLECULAR PHYSICS↗

Impact of dipolar molecules on the reliability of organic photovoltaic cells

Blending two non-fullerene acceptors (NFAs) to form bulk heterojunctions (BHJs) in ternary organic photovoltaics (OPVs) has been shown to lead to an end-capping exchange reaction that results in the generation of several new dipolar species whose impact on OPV operational stability remains uncertain. Here, we investigate the reliability of a ternary OPV system intentionally blended with dipolar NFA molecules. We reveal that an intrinsic contribution to OPV degradation is the reorganization and reorientation of the dipolar molecules during operation, which leads to an increased dielectric constant (ε r ) of the BHJ. Consequently, the electric field across the BHJ with dipolar molecules decreases compared with that of a non-dipolar BHJ under the same applied voltage, leading to a larger reduction in charge collection efficiency over time. This result has implications on the stability of a range of organic electronic devices containing dipolar molecules.

14 SOLAR ENERGY↗

Dirhodium(II,II) Complexes as Panchromatic Single-Molecule Photocatalysts for Hydrogen Evolution

The growing global energy demand and climate change have prompted a shift from carbon-based fuels to sustainable energy sources. Hydrogen production by harnessing solar energy and using abundant proton sources represents an attractive approach to addressing this crisis. Single-molecule single-chromophore photocatalysts, capable of both absorbing the incident photon and catalyzing the chemical transformation, are able to circumvent energy losses present in multicomponent systems that require a photosensitizer and a catalyst, often employing additional redox relay molecules. Here, the series of complexes derived from cis-[Rh 2 (μ-DPhF) 2 (μ-bncn) 2 ] 2+ (1; DPhF = N,N′-diphenylformamidinate, bncn = benzo[c]cinnoline) discussed in this Account presents robust and air-stable single-molecule photocatalysts with panchromatic absorption from the ultraviolet spectral region to the near-infrared (NIR), with high turnover frequencies of ∼20 to 30 h –1 under red light irradiation. For comparison, other single-molecule hydrogen-evolving photocatalysts reported to date exhibit low photocatalytic efficiency, are not operable in the visible or NIR regions, and are unstable under an ambient atmosphere.

Absorption↗

Distributive Nd-to-Yb Energy Transfer within Pure [YbNdYb] Heterometallic Molecules

Facile access to site-selective hetero-lanthanide molecules will open new avenues in the search of novel photophysical phenomena based on Ln-to-Ln' energy transfer (ET). This challenge demands strategies to segregate efficiently different Ln metal ions among different positions in a molecule. We report here the one-step synthesis and structure of a pure [YbNdYb] (1) coordination complex featuring short Yb···Nd distances, ideal to investigate a potential distributive (i.e., from one donor to two acceptors) intramolecular ET from one Nd 3+ ion to two Yb 3+ centers within a well-characterized molecule. The difference in ionic radius is the mechanism allowing to allocate selectively both types of metal ion within the molecular structure, exploited with the simultaneous use of two β-diketone-type ligands. To assist the photophysical investigation of this heterometallic species, the analogues [YbLaYb] (2) and [LuNdLu] (3) have also been prepared. Sensitization of Yb 3+ and Nd 3+ in the last two complexes, respectively, was observed, with remarkably long decay times, facilitating the determination of the Nd-to-Yb ET within the [YbNdYb] composite. This ET was demonstrated by comparing the emission of iso-absorbant solutions of 1, 2, and 3 and through lifetime determinations in solution and solid state. The comparatively high efficiency of this process corroborates the facilitating effect of having two acceptors for the nonradiative decay of Nd 3+ created within the [YbNdYb] molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nature of Hyperfine Interactions in TbPc 2 Single-Molecule Magnets: Multiconfigurational Ab Initio Study

Lanthanide-based single-ion magnetic molecules can have large magnetic hyperfine interactions as well as large magnetic anisotropy. Recent experimental studies reported tunability of these properties by changes of chemical environments or by application of external stimuli for device applications. In order to provide insight onto the origin and mechanism of such tunability, here we investigate the magnetic hyperfine and nuclear quadrupole interactions for a 159 Tb nucleus in TbPc 2 (Pc = phthalocyanine) single-molecule magnets using multiconfigurational ab initio methods including spin–orbit interaction. Since the electronic ground and first-excited (quasi)doublets are well separated in energy, the microscopic Hamiltonian can be mapped onto an effective Hamiltonian with an electronic pseudospin S = 1/2. From the ab initio calculated parameters, we find that the magnetic hyperfine coupling is dominated by the interaction of the Tb nuclear spin with electronic orbital angular momentum. The asymmetric 4f-like electronic charge distribution leads to a strong nuclear quadrupole interaction with significant transverse terms for the molecule with low symmetry. The ab initio calculated electronic–nuclear spectrum including the magnetic hyperfine and quadrupole interactions is in excellent agreement with the experiment. We further find that the transverse quadrupole interactions significantly influence the avoided level crossings in magnetization dynamics and that the molecular distortions affect mostly the Fermi contact terms as well as the transverse quadrupole interactions. Synopsis Hyperfine interactions for 159 Tb nucleus in TbPc 2 single-molecule magnets are investigated from first-principles using multiconfigurational calculations. Strong nuclear quadrupole and magnetic hyperfine coupling are found, with the latter being dominated by the paramagnetic spin-orbital mechanism. Furthermore, we construct an ab initio pseudospin Hamiltonian and obtain the electronic-nuclear spectrum that is in excellent agreement with experiment. The Zeeman diagram is calculated, and the magnetization dynamics is discussed. The effects of molecular distortions are researched.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Theoretical Investigations on the Plasmon-Mediated Dissociation of Small Molecules in the Presence of Silver Atomic Wires

Plasmonic nanoparticles can promote bond activation in adsorbed molecules under relatively benign conditions via excitation of the nanoparticle’s plasmon resonance. As the plasmon resonance often falls within the visible light region, plasmonic nanomaterials are a promising class of catalysts. However, the exact mechanisms through which plasmonic nanoparticles activate the bonds of nearby molecules are still unclear. Herein, we evaluate Ag 8 –X 2 (X = N, H) model systems via real-time time-dependent density functional theory (RT-TDDFT), linear response time-dependent density functional theory (LR-TDDFT), and Ehrenfest dynamics in order to better understand the bond activation processes of N 2 and H 2 facilitated by the presence of the atomic silver wire under excitation at the plasmon resonance energies. We find that dissociation is possible for both small molecules at high electric field strength. Activation of each adsorbate is symmetry- and electric field-dependent, and H 2 activates at lower electric field strengths than N 2 . Furthermore, this work serves as a step toward understanding the complex time-dependent electron and electron–nuclear dynamics between plasmonic nanowires and adsorbed small molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Comparison of Electronic Structure Methods for Predicting the Hydrogenation Energies of Candidate Molecules for Hydrogen Storage

The development of novel energy materials and fuels is required to expand current available energy sources. Aiming to reach this goal, there is growing interest in using molecular hydrogen as an energy carrier due to its abundance and high energy density. Liquid organic hydrogen carriers (LOHCs) are a promising route to the large-scale storage and transport of hydrogen for use in the energy economy. The search for thermodynamically viable LOHC molecules for real world use has led to a set of constraints on the dehydrogenation enthalpy and the minimum gravimetric hydrogen capacity. These constraints allow one to formulate the search for an ideal LOHC candidate molecule as an optimization problem well suited to the strengths of machine learning and artificial intelligence computational approaches. A critical barrier to a large-scale, high-throughput screening of LOHC candidate molecules is the lack of reliable training data. Computational electronic structure methods including density functional theory, coupled cluster approximations, and diffusion Monte Carlo can be used to provide training data where experimental data are either unreliable or do not exist. In this work, we use these methods to calculate the dehydrogenation energies and enthalpies of candidate LOHC molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗