Phebe van Langevelde earned her BSc in molecular science and technology from Leiden University and Delft University of Technology (joint degree) in 2017. She completed a master's degree in chemistry with a specialization in energy and sustainability at Leiden University in 2020, working on the development of catalysts for the oxygen reduction reaction, and was a visiting student at the Institute of Chemical Research of Catalonia (ICIQ). Since 2020, she is a PhD candidate in the Catalysis and Surface Chemistry group of Leiden University. Her current research focuses on electrocatalysis for the sustainable production of hydrogen peroxide. Ioannis Katsounaros is the leader of the Electrosynthesis group at the Helmholtz Institute Erlangen-Nuremberg for renewable energy, an institute of Forschungszentrum Julich GmbH (FZJ). He graduated with a PhD in chemical engineering from the Aristotle University of Thessaloniki in 2009, working on the electrochemical reduction of nitrate. He was a post-doc at the Max-Planck-Institut fur Eisenforschung (2010–2013) and a Marie Curie International Outgoing Fellow, first at the Argonne National Laboratory (outgoing phase, 2013–2015) and then at the University of Leiden (return phase, 2015–2016) before joining FZJ in September 2016. His research interests are on physical electrochemistry and electrocatalysis. Marc Koper is professor of surface chemistry and catalysis at Leiden University. He received his PhD degree (1994) from Utrecht University with a thesis on nonlinear dynamics and oscillations in electrochemistry. He was an EU Marie Curie postdoctoral fellow at the University of Ulm and a Fellow of Royal Netherlands Academy of Arts and Sciences at Eindhoven University of Technology before moving to Leiden in 2005. His research focuses on fundamental aspects of electrocatalysis, theoretical electrochemistry, and electrochemical surface science in relation to renewable energy and chemistry. He has received various national and international awards, including the Netherlands Catalysis and Chemistry Award (2019) and the Faraday Medal (2017).
Captivating cavities Laser technology is a familiar example of how confining light between two mirrors can tune its properties. Quantum mechanics also dictates that even without extraneous light, matter confined in a cavity resonant with its electronic or vibrational transitions can couple with vacuum electromagnetic field fluctuations. Garcia-Vidal et al. review the remarkable and still somewhat mysterious implications of this “strong-coupling” regime, with manifestations ranging from enhanced charge transport to site-selective chemical reactivity across a range of molecular and solid-state materials. Science, abd0336, this issue p. eabd0336 A Review describes chemical and physical manifestations of strong coupling in cavities tuned to electronic or vibrational resonances. BACKGROUND One of the most important phenomena in cavity quantum electrodynamics (cQED) is the so-called strong coupling regime, which appears when the interaction between a photon tightly confined in an optical cavity and a matter excitation creates hybrid light-matter states. When the latter are populated, hybrid particles called polaritons are formed. These particles are very attractive because they combine properties of their constituents, which enables applications ranging from low-threshold lasing in semiconductors to photon quantum information. Since its discovery, most of the investigations on strong coupling have been aimed mainly toward the modification of optical properties. During the past decade, an alternative area of research has emerged that takes advantage of collective strong coupling to take chemistry and materials science into new directions. For this purpose, no external light source is necessary as the hybrid light-matter states are formed even in the dark because the coupling occurs through the zero-point energy of the optical mode (i.e., the vacuum field). The mere presence of the hybrid states has a substantial effect on material properties, as reviewed here. ADVANCES Both experimental and theoretical studies have shown changes to photochemical reaction rates under strong coupling between the electronic excitations of molecules and cavity electromagnetic modes. Strong coupling modifies the shape of the potential energy surfaces associated with the excited states of the molecule, allowing for a manipulation of its photophysical properties. Moreover, ground-state chemical reactivity can also be completely modified when molecular vibrations are strongly coupled to infrared cavity modes. Although a detailed picture of the mechanism is still missing, symmetry seems to play a key role. Material properties can also be changed by strong coupling. Charge and energy transport in organic materials and magneto-conductivity in two-dimensional electron gases have been shown to be altered. Thanks to the intrinsic delocalized character of the polaritonic modes, transport properties can be then tuned at a macroscopic scale. It is also feasible to manipulate phases of matter by means of strong coupling. It has been reported that the critical temperature of a superconductor can be substantially enhanced by judiciously exploiting vibrational strong coupling and that the ferromagnetism of nanoparticles can be boosted by orders of magnitude. These examples illustrate the potential of using vacuum fields instead of intense laser fields to induce modification of material properties. OUTLOOK There are many classes of organic reactions that are currently being explored under strong coupling. As more results are collected, the underlying physical chemistry will be further clarified and should lead to some general principles to guide chemists and physicists in their use of vibrational strong coupling. The recent demonstrations that water, under vibrational strong coupling, modifies enzyme activity illustrates the potential for manipulating biological activity under strong coupling—an avenue that remains unexplored. Regarding solid-state material properties, the influence of strong coupling in phonon-based phase transitions should also be fully explored, aiming at inducing new condensed phases. Moreover, cavity-controlled magneto-transport might reach the quantum Hall regime. In general, two-dimensional materials are very well suited to be integrated in cavity resonators with deeply subwavelength photon confinement, which provides an intriguing platform to modify electronic properties through vacuum fields. Illustration of modified molecular processes under strong coupling in optical cavities. (Left) Charge transfer complexation between mesitylene and iodide (courtesy of K. Nagarajan). (Right) Energy transfer between donor and acceptor molecules (courtesy of J. Galego). Over the past decade, there has been a surge of interest in the ability of hybrid light-matter states to control the properties of matter and chemical reactivity. Such hybrid states can be generated by simply placing a material in the spatially confined electromagnetic field of an optical resonator, such as that provided by two parallel mirrors. This occurs even in the dark because it is electromagnetic fluctuations of the cavity (the vacuum field) that strongly couple with the material. Experimental and theoretical studies have shown that the mere presence of these hybrid states can enhance properties such as transport, magnetism, and superconductivity and modify (bio)chemical reactivity. This emerging field is highly multidisciplinary, and much of its potential has yet to be explored.
Abstracts: To investigate the aging failure mechanism of epoxy Zn-Al composite coatings on steel grid supports in industrial marine environments, the corrosion conditions of “high Cl⁻ + high concentrations of industrial acid gases + alternating wet-dry cycles” in the Caofeidian Port Area of Bohai Bay were taken as the testing background. A salt spray/wet-dry alternating cycle test combined with outdoor exposure testing was adopted. Coating performance and morphological evolution were analyzed via thickness measurements, adhesion tests, electrochemical impedance spectroscopy (EIS), 3D laser confocal microscopy, scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). Results indicate a three-stage failure progression: Initial protective stage (Cycles 0–3): The coating remains dense and smooth with minimal color change, gradual thickness increase, and high adhesion. EIS results show |Z| at 0.01 Hz is approximately 10⁸–10⁹ Ω·cm², demonstrating a significant physical barrier function. Localized failure stage (4 cycles): Localized rust spots appear on the coating surface, thickness growth accelerates, adhesion decreases abruptly, |Z| at 0.01 Hz drops to 10⁷ Ω·cm², and the penetration of corrosive media triggers Zn dissolution. Expanded failure stage (≥5 cycles): Corrosion spots expand, the contents of Zn and Al decrease sharply, Fe and O are enriched, |Z| at 0.01 Hz reaches 10⁶ Ω·cm², the coating blisters and peels off, leading to complete failure. This study provides a theoretical basis for optimizing protection strategies in industrial marine environments.
Industrial electrochemistry, Physical and theoretical chemistry
Fernando Corrêa, Julio Michael Stern, Rafael Bassi Stern
In this article, we present an extension of the Full Bayesian Significance Test (FBST) for nonparametric settings, termed NP-FBST, which is constructed using the limit of finite dimension histograms. The test statistics for NP-FBST are based on a plug-in estimate of the cross-entropy between the null hypothesis and a histogram. This method shares similarities with Kullback–Leibler and entropy-based goodness-of-fit tests, but it can be applied to a broader range of hypotheses and is generally less computationally intensive. We demonstrate that when the number of histogram bins increases slowly with the sample size, the NP-FBST is consistent for Lipschitz continuous data-generating densities. Additionally, we propose an algorithm to optimize the NP-FBST. Through simulations, we compare the performance of the NP-FBST to traditional methods for testing uniformity. Our results indicate that the NP-FBST is competitive in terms of power, even surpassing the most powerful likelihood-ratio-based procedures for very small sample sizes.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
This review provides the fundamental theoretical tools for the development of a complete wave‐function formalism for the study of time‐evolution of chemico‐physical systems at finite temperature. The methodology is based on the non‐equilibrium thermo‐field dynamics (NE‐TFD) representation of quantum mechanics, which is alternative to the commonly used density matrix representation. TFD concepts are extended and integrated with the tensor‐train (TT) numerical tools leading to a novel and powerful theoretical and computational framework for the study of complex quantum dynamical problems. In addition, NE‐TFD techniques are extended to enable the study of dissipative open systems via a new formulation of the hierarchical equations of motion (HEOM) fully integrated with TT methodologies. We demonstrate that the combination of the TFD machinery with computational advantages of TTs results in a powerful theoretical and computational framework for scrutinizing dynamics of complex multidimensional electron‐vibrational systems. We illustrate the validity and the computational advantages of the developed methodologies by applying them to the study of quantum coherence effects in the energy‐transfer processes in antenna systems, to the analysis of fingerprints of vibrational modes in electron‐transfer and charge‐transfer processes in various model and realistic multidimensional molecular systems, as well as to simulation of other fundamental models of physical chemistry.
Quantum mechanical calculations are routinely used as a major support in mid-infrared (MIR) and Raman spectroscopy. In contrast, practical limitations for long time formed a barrier to developing a similar synergy between near-infrared (NIR) spectroscopy and computational chemistry. Recent advances in theoretical methods suitable for calculation of NIR spectra opened the pathway to modeling NIR spectra of various molecules. Accurate theoretical reproduction of NIR spectra of molecules reaching the size of long-chain fatty acids was accomplished so far. In silico NIR spectroscopy, where the spectra are calculated ab initio, provides substantial improvement in our understanding of the overtones and combination bands that overlap in staggering numbers and create complex lineshape typical for NIR spectra. This improves the comprehension of the spectral information enabling access to rich and detail molecular footprint, essential for fundamental research and useful in routine analysis by NIR spectroscopy and chemometrics. This review article summarizes the most recent accomplishments in the emerging field with examples of simulated NIR spectra of molecules reaching long-chain fatty acids and polymers. In addition to detailed NIR band assignments and new physical insights, simulated spectra enable innovative support in applications. Understanding of the difference in the performance observed between miniaturized NIR spectrometers and chemical interpretation of the chemometric models are noteworthy here. These new elements integrated into NIR spectroscopy framework enable a knowledge-based design of the analysis with comprehension of the processed chemical information.
Synthesis of monodispersed, stable halide, and mixed halide perovskite nanocrystals by hot‐injection approach is still challenging due to the fast reaction kinetics and unrevealed ligand chemistry. The atomic scale imaging of perovskite nanocrystals using transmission electron microscopy (TEM) is also challenging because of their structural degradation due to high electron dose and soft nature of perovskites. Here, a novel technique is proposed to synthesize pure cubic phase, monodispersed, stable CsPbX3 (X = I/Br) nanocrystals by simply modifying ligand chemistry using olive oil, which also leads to realization of tuneable composition mixed halide perovskites by simple physical mixing. Here, the atomic scale images and the probable distribution of Cs, Pb, and I/Br atoms in single halide and mixed halide perovskites via high‐resolution TEM microscopy are presented. The estimated atomic distance (PbPb and PbI/Br) is strongly corroborated with the VESTA structure. Interestingly, the lattice constant (d‐value) of the synthesized nanocrystals is smaller (≈3%) than the theoretical predicted one, leading to a higher phase stability in laboratory ambient conditions (45–55% humidity, 300 K). The theoretical analysis using density functional theory enlightens the understanding of higher stability of CsPbI2Br along with the maximum optical absorption in the visible regime, as a preferable material for the photovoltaic applications.
Fe ions, as one of the unavoidable metal ions, are present in flotation pulp as ferric and ferrous species, and the effect of ferric species on the flotation behavior of sulfide minerals has been widely discussed in the above literatures. However, the effect of ferrous species has rarely been noticed. In this paper, the effect of ferrous species on the flotation behavior and surface characteristics of galena was investigated by using microflotation, zeta potential measurements, X-ray photoelectron spectrometer (XPS) analysis, and density functional theory (DFT) calculations. Microflotation tests indicated that the flotation recovery of galena with potassium butyl xanthate (KBX) as collector was significantly decreased with the addition of Fe2+ in the pulp, and the recovery was further decreased with increasing dosage of Fe2+. In addition, the finer the galena particles, the greater the decrease in flotation recovery. Zeta potential analysis illustrated that the isoelectric point (IEP) was shifted from 4.4 to 5.8 due to the adsorption of ferrous hydroxyl complexes on the galena surface and the zeta potential. XPS surface analysis suggested that the surface oxidation of galena was alleviated by the consumption of O2 in the pulp, which reduced the adsorption of the collector KBX on and the oxidation of xanthates to dixanthogens. Density functional theory (DFT) calculations confirmed that the ferrous hydroxyl complex FeOH+ could be adsorbed on the galena surface by interactions between Fe and S atoms.
S.V. Molchanov, S.A. Tretyakov, I.A. Kaplunov
et al.
This paper presents studies of the influence of growth conditions of paratellurite single crystals on the side surface of grown boules and the possibility of assessing the quality of crystals based on the values and dynamics of the roughness parameters and fractal parameters of juvenile surfaces. Two single crystals were grown under similar technological conditions and differing from each other in structural quality. Their lateral surfaces were studied using the optical interference profilometer NanoMap 1000WLI employing SPIP and Gwyddion softwares. As a result, roughness parameters of profiles, and fractal parameters of crystal surfaces along the growth direction were obtained,. It was concluded that under conditions corresponding to the formation of stable flows in the melt, the values of the surface roughness over the entire length of the crystal is less than 5 μm, and the fractal energy parameter can be used as a marker of the quality and homogeneity of crystals.
ConspectusAtomic simulations based on quantum mechanics (QM) calculations have entered into the tool box of chemists over the past few decades, facilitating an understanding of a wide range of chemistry problems, from structure characterization to reactivity determination. Due to the poor scaling and high computational cost intrinsic to QM calculations, one has to either sacrifice accuracy or time when performing large-scale atomic simulations. The battle to find a better compromise between accuracy and speed has been central to the development of new theoretical methods.The recent advances of machine-learning (ML)-based large-scale atomic simulations has shown great promise to the benefit of many branches of chemistry. Instead of solving the Schrödinger equation directly, ML-based simulations rely on a large data set of accurate potential energy surfaces (PESs) and complex numerical models to predict the total energy. These simulations feature both a high speed and a high accuracy for computing large systems. Due to the lack of a physical foundation in numerical models, ML models are often frustrated in their predictivity and robustness, which are key to applications. Focusing on these concerns, here we overview the recent advances in ML methodologies for atomic simulations on three key aspects. Namely, the generation of a representative data set, the extensity of ML models, and the continuity of data representation. While global optimization methods are the natural choice for building a representative data set, the stochastic surface walking method is shown to provide the desired PES sampling for both minima and transition regions on the PES. The current ML models generally utilize local geometrical descriptors as an input and consider the total energy as the sum of atomic energies. There are many flavors of data descriptors and ML models, but the applications for material and reaction predictions are still limited, not least because of the difficulty to train the associated vast global data sets. We show that our recently designed power-type structure descriptors together with a feed-forward neural network (NN) model are compatible with highly complex global PES data, which has led to a large family of global NN (G-NN) potentials.Two recent applications of G-NN potentials in material and reaction simulations are selected to illustrate how ML-based atomic simulations can help the discovery of new materials and reactions.
Many quantum algorithms, including recently proposed hybrid classical/quantum algorithms, make use of restricted tomography of the quantum state that measures the reduced density matrices, or marginals, of the full state. The most straightforward approach to this algorithmic step estimates each component of the marginal independently without making use of the algebraic and geometric structure of the marginals. Within the field of quantum chemistry, this structure is termed the fermionic n-representability conditions, and is supported by a vast amount of literature on both theoretical and practical results related to their approximations. In this work, we introduce these conditions in the language of quantum computation, and utilize them to develop several techniques to accelerate and improve practical applications for quantum chemistry on quantum computers. As a general result, we demonstrate how these marginals concentrate to diagonal quantities when measured on random quantum states. We also show that one can use fermionic n-representability conditions to reduce the total number of measurements required by more than an order of magnitude for medium sized systems in chemistry. As a practical demonstration, we simulate an efficient restoration of the physicality of energy curves for the dilation of a four qubit diatomic hydrogen system in the presence of three distinct one qubit error channels, providing evidence these techniques are useful for pre-fault tolerant quantum chemistry experiments.
In this work, we comprehensively explore the spectral and photophysical properties of a coumarin-based dye (1) in neat solvents. The modulation of stokes shifts, emission quantum yields (?F) and excited-state lifetimes of 1 by local environment (polarity, polarizability, viscosity and hydrogen bonding) signifies the formation of intramolecular charge state (ICT) from the amino group to the coumarin moiety. Collectively, in the more viscous polar solvents the rotation of the amino group is restricted, exponentially decreasing the non-radiative rate constants (knr).
Crystallography, Physical and theoretical chemistry
The electrochemical conversion of CO2 into valuable fuels is a promising technique to store intermittent energy, such as wind, solar and nuclear, and facilitate a closed carbon cycle. Here we report the formation of formic acid from the electrochemical reduction of CO2 catalyzed by rhodium-protoporphyrin in aqueous solution. The formation of formic acid is highly dependent on pH with the highest faradaic efficiency of 50% at pH=3 while it is negligible at pH=1. The theoretical predication indicates that CO should be the main product from the electrochemical reduction of CO2 catalyzed by rhodium-protoporphyrin as cobalt-protoporphyrin. However, the strong affinity of axial ligands hinders the formation of metal-bonded carboxylate or metal-hydride intermediates leading to the difficulty of the formation of CO or formic acid through the intermediate respectively. The most likely intermediate for the formation of formic acid catalyzed by rhodium-protoporphyrin is phlorin-hydride which is an intermediate protonated the meso carbon of the macrocycle.
Industrial electrochemistry, Physical and theoretical chemistry
The hydrogen bond represents a fundamental interaction widely existing in nature, which plays a key role in chemical, physical and biochemical processes. However, hydrogen bond dynamics at the molecular level are extremely difficult to directly investigate. Here, in this work we address direct electrical measurements of hydrogen bond dynamics at the single-molecule and single-event level on the basis of the platform of molecular nanocircuits, where a quadrupolar hydrogen bonding system is covalently incorporated into graphene point contacts to build stable supramolecule-assembled single-molecule junctions. The dynamics of individual hydrogen bonds in different solvents at different temperatures are studied in combination with density functional theory. Both experimental and theoretical results consistently show a multimodal distribution, stemming from the stochastic rearrangement of the hydrogen bond structure mainly through intermolecular proton transfer and lactam–lactim tautomerism. This work demonstrates an approach of probing hydrogen bond dynamics with single-bond resolution, making an important contribution to broad fields beyond supramolecular chemistry. Hydrogen-bonds are widely found in many systems, such as DNAs and supramolecular assemblies, but it remains challenging to detect their dynamics at a molecular level. Here, Zhou et al. study the stochastic arrangement of hydrogen bonds using single-molecule junctions connected to graphene electrodes.