Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem. The extent of problems in quantum chemistry for which quantum algorithms could provide a speedup is still unclear, as well as the kind of speedup one should expect. Here, the authors look at the problem of ground state energy estimation, and gather theoretical and numerical evidence for the fact that an exponential quantum advantage is unlikely for generic problems of interest.
In the field of medicine, compounds that contain pyrazole and their derivatives are recognized as some of the earliest anti-inflammatory and analgesic agents. Consequently, the development of novel pyrazole-containing synthons represents a promising avenue in the quest for new biologically active substances. The supramolecular aspect plays a crucial role in comprehending the chemistry of pyrazoles. The primary driving force behind the self-assembly of pyrazolyl molecules is attributed to hydrogen bonds. In this context, we propose a quantum theoretical approach to hydrogen bonding in order to elucidate the infrared (IR) spectra of 4-bromo-3,5-dimethylpyrazole (4-Br,3,5-DMPz) crystals. Our ultimate objective is to elucidate the hydrogen-bond dynamics and illustrate the main mechanisms that govern the generation of the IR band contours. The approach addresses the impact of the anharmonic vibrational coupling within the dimeric units, the Davydov coupling and the combined influences of damping mechanisms on theυSX-H IR band contours. The exchange interaction between the two hydrogen bonds of the dimeric units is analyzed through the non-adiabatic coupling framework. The direct damping mechanism is addressed within the theoretical framework established by Rösch and Ratner, while the indirect damping associated with the two hydrogen-bonded bridges is integrated using non-Hermitian Hamiltonians. The contours of the IR bands are obtained through linear response theory by applying a Fourier transform to the dipole moment operator autocorrelation function associated with the high-frequency mode. This theoretical framework reverts to the model proposed by Maréchal and Witkowski regarding Davydov coupling in damping lack, and aligns with the foundational quantum approach of indirect damping when Davydov coupling is not present. The methodology is applied to the study the IR spectra of crystals of 4-Br,3,5-DMPz and their deuterium-bonded analogues at 293 K and 77 K. Numerical simulations demonstrate that the congregated influence of Davydov coupling, the linear interaction within the dimeric units, and the various damping mechanisms can effectively account for the intricate characteristics of the experimental IR band contours. The notable distinctions identified in the fine structure patterns of theυSX-H(D) band contours, along with the temperature effects in these crystals, have been clarified and interpreted from a physical perspective.
Can the laws of physics be unified? One of the most puzzling challenges is to reconcile physics and chemistry, where molecular physics meets condensed-matter physics, resulting from the dynamic fluctuation and scaling effect of glassy matter at the glass transition temperature. The pioneer of condensed-matter physics, Nobel Prize-winning physicist Philip Warren Anderson referred to this gap as the deepest and most interesting unsolved problem in condensed-matter physics in 1995. In 2005, Science, in its 125th anniversary publication, highlighted that the question of ‘what is the nature of glassy state?’ was one of the greatest scientific conundrums for the next quarter century. However, the nature of the glassy state and its connection to the glass transition have not been fully understood owing to the interdisciplinary complexity of physics and chemistry, governed by physical laws at the condensed-matter and molecular scales, respectively. Therefore, the study of glass transition is essential to explore the working principles of the scaling effects and dynamic fluctuations in glassy matter and to further reconcile the interdisciplinary complexity of physics and chemistry. Initially, this paper proposes a thermodynamic order-to-disorder free-energy equation for microphase separation to formulate the dynamic equilibria and fluctuations, which originate from the interplay of the phase and microphase separations during glass transition. Then, the Adam–Gibbs domain model is employed to explore the cooperative dynamics and molecular entanglement in glassy matter. It relies on the concept of transition probability in pairing, where each domain contains e + 1 segments, in which approximately 3.718 segments cooperatively relax in a domain at the glass transition temperature. This model enables the theoretical modeling and validation of a previously unverified statement, suggesting that 50–100 individual monomers would relax synchronously at glass transition temperature. Finally, the constant free-volume fraction of 2.48% is phenomenologically obtained to achieve a condensed constant (C) of C= 0.12(1−γ) = 1.501 × 10−11 J·mol−1·K−1, where γ represents the superposition factor of free volume and is characterised using the cumulative Poisson distribution function, at the condensed-matter scale, analogous to the Boltzmann constant (k B) and gas constant (R).
Lipid digestion is a bio-interfacial process that is largely governed by the binding of the lipase-colipase-biosurfactant (bile salts) complex onto the surface of emulsified lipid droplets. Therefore, engineering oil-water interfaces that prevent competitive displacement by bile salts and/or delay the transportation of lipase to the lipidoidal substrate can be an effective strategy to modulate lipolysis in human physiology. In this review, we present the mechanistic role of Pickering emulsions i.e. emulsions stabilised by micron-to-nano sized particles in modulating the important fundamental biological process of lipid digestion by virtue of their distinctive stability against coalescence and resilience to desorption by intestinal biosurfactants. We provide a systematic summary of recent experimental investigations and mathematical models that have blossomed in the last decade in this domain. A strategic examination of the behavior and mechanism of lipid digestion of droplets stabilised by particles in simulated biophysical environments (oral, gastric, intestinal regimes) was conducted. Various particle-laden interfaces were considered, where the particles were derived from synthetic or biological sources. This allowed us to categorize these particles into two classes based on their mechanistic role in modifying lipid digestion. These are 'human enzyme-unresponsive particles' (e.g. silica, cellulose, chitin, flavonoids) i.e. the ones that cannot to be digested by human enzymes, such as amylase, protease and 'human enzyme-responsive particles' (e.g. protein microgels, starch granules), which can be readily digested by humans. We focused on the role of particle shape (spherical, anisotropic) on modifying both interfacial and bulk phases during lipolysis. Also, the techniques currently used to alter the kinetics of lipid digestion using intelligent physical or chemical treatments to control interfacial particle spacing were critically reviewed. A comparison of how various mathematical models reported in literature predict free fatty acid release kinetics during lipid digestion highlighted the importance of the clear statement of the underlying assumptions. We provide details of the initial first order kinetic models to the more recent models, which account for the rate of adsorption of lipase at the droplet surface and include the crucial aspect of interfacial dynamics. We provide a unique decision tree on model selection, which is appropriate to minimize the difference between experimental data of free fatty acid generation and model predictions based on precise assumptions of droplet shrinkage, lipase-binding rate, and nature of lipase transport process to the particle-laden interface. Greater insights into the mechanisms of controlling lipolysis using particle-laden interfaces with appropriate mathematical model fitting permit better understanding of the key lipid digestion processes. Future outlook on interfacial design parameters, such as particle shape, size, polydispersity, charge, fusion, material chemistry, loading and development of new mathematical models that provide closed-loop equations from early to later stages of kinetics are proposed. Such future experiments and models hold promise for the tailoring of particle-laden interfaces for delaying lipid digestion and/or site-dependent controlled release of lipidic active molecules in composite soft matter systems, such as food, personal care, pharmaceutical, healthcare and biotechnological applications.
Gomez, Axel, de la Puente, Miguel, David, Rolf
et al.
Recent advances in machine learning offer powerful tools for exploring complex reaction mechanisms in condensed phases via reactive simulations. In this tutorial review, we describe the key challenges associated with simulating reactions in condensed phases, we introduce neural network potentials and detail how they can be trained. We emphasize the importance of active learning to construct the training set, and show how these reactive force fields can be integrated with enhanced sampling techniques, including transition path sampling. We illustrate the capabilities of these new methods with a selection of applications to chemical reaction mechanisms in solution and at interfaces.
Soil is the bearing centre of terrestrial ecosystems. Oil pollution leads to changes in the physical and chemical properties of soil to varying degrees. Polluted soils form a unique microbial species composition, which provides rich materials for the bioremediation of oil-contaminated soil through biological enhancement. Understanding the microbial composition of petroleum-contaminated soil can provide a better biological method for soil remediation. Based on this, 16 S rRNA and ITS genetic markers were used to analyse the bacterial and fungal microbiota in petroleum-contaminated soil, and their physical and chemical properties (total organic carbon, alkaline hydrolysable nitrogen, total phosphorus, total potassium, available potassium, Cu, Zn, and Cd) were measured. It was found that petroleum pollution can significantly reduce the abundance and diversity of bacteria and fungi in the soil and significantly promote the relative abundance of Proteobacteria, Pseudomonas, Pseudoxanthomonas and Pseudoallescheria, which changed the dominant flora of bacteria and fungi and reshaped the co-occurrence network relationship between bacteria and fungi in oil-contaminated soil. The content of total organic carbon in petroleum-contaminated soil was significantly higher than that in uncontaminated soil, while the content of alkaline hydrolysable nitrogen and available potassium was significantly lower than that in uncontaminated soil, and the content of Cu significantly increased after pollution. Total organic carbon is the key driving factor that changes oil-contaminated soil microorganisms and plays a significant role in regulating the remodelling and composition of the microbial community in oil-contaminated soil. This study laid a solid theoretical foundation for the bioremediation of oil-contaminated soil.
To meet the booming demand of high‐energy‐density battery systems for modern power applications, various prototypes of rechargeable batteries, especially lithium metal batteries with ultrahigh theoretical capacity, have been intensively explored, which are intimated with new chemistries, novel materials and rationally designed configurations. What happens inside the batteries is associated with the interaction of multi‐physical field, rather than the result of the evolution of a single physical field, such as concentration field, electric field, stress field, morphological evolution, etc. In this review, multi‐physical field simulation with a relatively wide length and timescale is focused as formidable tool to deepen the insight of electrodeposition mechanism of Li metal and the electro‐chemo‐mechanical failure of solid‐state electrolytes based on Butler‐Volmer electrochemical kinetics and solid mechanics, which can promote the future development of state‐of‐the‐art Li metal batteries with satisfied energy density as well as lifespan.
Abstract To select suitable surfactant as water-spray additive to improve dust suppression efficiency, six types of coal sample (lignite, long flame coal, non-caking coal, gas coal, coking coal, and anthracite) were selected from some typical mining areas in China, the influence of the physical chemistry characteristics of coal samples on the wetting ability of surfactants to the coals dust was investigated. Their proximate composition, ultimate content, chemical structure, surface morphology, pore structure parameters, and contact angle were determined. Three kinds of anionic surfactants – Sodium Alcohol Ether Sulphate (AES), Sodium Alpha-Olefin Sulfonate (AOS), Fatty Acid Methyl Esters Ethoxylate Sulfonate (FMES) – and one kind of nonionic surfactant – Coco Diethanolamide (CDEA) – were selected to carry out sedimentation experiments on the coal samples dust, to explore the main factors influencing the wettability of the coal samples dust. Among these factors, pore size is the main factor determining the wettability of coal dust, the contact angle decreases linearly (R2 = 0.96) with pore size increase. The experimental results demonstrate that the following factors produce correspondingly increased wettability: higher moisture content, lower carbon content, higher oxygen content, more oxygen-containing functional groups, and increased pore size. In addition, the wettability of the six types of the coal samples dust shows a high-low-high trend with metamorphic degree increase, lignite has the strongest wettability, and the coking coal with the highest degree of metamorphism in the selected bituminous coal sample has the weakest wettability. Moreover, compared with nonionic surfactants, anionic surfactants have stronger wetting ability, but the same anionic surfactants have different wetting abilities to coal dust with different metamorphic degrees. AOS has stronger wetting ability to the dust of long flame coal, non-caking coal, and anthracite; AES has stronger wetting ability to the dust of lignite and coking coal; and FMES has stronger wetting ability to the dust of gas coal. The research results provide a theoretical basis for different coal mines to select suitable surfactants as water-spray additives to improve dust suppression efficiency.
Cells are heterogeneous on every length and time scale; cytosol contains thousands of proteins, lipids, nucleic acids, and small molecules, and molecular interactions within this crowded environment determine the structure, dynamics, and stability of biomolecules. For decades, the effects of crowding at the atomistic scale have been overlooked in favor of more tractable models largely based on thermodynamics. Crowding can affect the conformations and stability of biomolecules by modulating water structure and dynamics within the cell, and these effects are nonlocal and environment dependent. Thus, characterizing water's hydrogen-bond (H-bond) networks is a critical step toward a complete microscopic crowding model. This perspective provides an overview of molecular crowding and describes recent time-resolved spectroscopy approaches investigating H-bond networks and dynamics in crowded or otherwise complex aqueous environments. Ultrafast spectroscopy combined with atomistic simulations has emerged as a powerful combination for studying H-bond structure and dynamics in heterogeneous multicomponent systems. We discuss the ongoing challenges toward developing a complete atomistic description of macromolecular crowding from an experimental as well as a theoretical perspective.
Xiao Xia Dong, Yan Rong Liu, Victor Kimberg
et al.
The carrier-envelope-phase of sub-cycle UV pulses strongly influences the dynamics of quantum systems, but its characterization is not accessible experimentally. Here, an asymmetry in the of angular photofragment distributions of diatomic molecules is identified as a way to imprint carrier-envelope-phase on a measurable quantity.
Acyl migration of fatty acid at sn-2 is often observed alongside enzymatic interesterification (EIE), causing the loss of lipase selectivity toward the acyl group at sn-1,3. In this study, an oil blend consisting of palm stearin (PST) and palm olein (POL) was interesterified via a chemical interesterification (CIE) and enzymatic method using a packed bed reactor. Characterization in terms of the triacylglycerol (TAG) compositions, sn-2 fatty acid distributions, and solid fat content profiles was performed. In comparison to that of CIE fats, EIE fats showed different modification effects on the solid fat content. Under similar reaction conditions, different interesterification degrees (IDs) were obtained according to the various blend ratios. Using the same mass ratio of substrates (POL/PST of 9:1), the EIE reaction time and temperature affected the ID and the change in the fatty acyl group at the sn-2 position. Under the reaction time of 46 min, an ID of 94.41% was acquired, while at 80 °C, the degree of acyl migration at sn-2 was 92.87%. EIE with high acyl migration exhibited a lower crystallization rate than that of EIE with low acyl migration. However, the effect of acyl migration on crystal polymorphism and oxidative stability was insignificant. Outcomes from this study are meaningful for the establishment of a theoretical basis for a controlled positional-specific EIE that is catalyzed by sn-1,3-specific lipase.
Mehdi Honarvar Nazari, M. S. Shihab, E. Havens
et al.
Abstract Preservation of metals in infrastructures and other assets requires cost-effective and sustainable solutions such as green corrosion inhibitors. This study assesses an apple pomace-derived green inhibitor synthesized by an innovative zero-waste method. Electrochemical measurements revealed the high performance of this liquid extract in reducing the corrosion of carbon steel in NaCl brine. The chemical composition of this inhibitor was characterized by liquid chromatography mass spectroscopy (LC-MS) to shed light on the corrosion inhibition mechanism. Based on LC-MS analysis, the results of surface analysis were interpreted. Specifically, the major corrosion inhibitor agent in the apple pomace extract was determined as C 26 H 50 NO 7 P (1-Linoleoyl-sn-glycero-3-phosphocholine), which can adsorb onto the steel surface to form a barrier layer and serve as a blocker of active anodic sites. Further study showed that the apple extract adsorption follows the Langmuir isotherm, and physical adsorption is dominant (vs. chemical adsorption). Theoretical calculations using quantum chemistry proposed a physisorption mechanism for the protection of steel by C 26 H 50 NO 7 P molecules. Graphical abstract
A.A. Kravtsov, I.S. Chikulina, D.S. Vakalov
et al.
This work was the first to study the effect of silver nanoparticles on the luminescence of cerium doped yttrium-aluminum garnet. A sol with the size of silver nanoparticles of ≈100 nm was synthesized using the method of chemical reduction. Phosphor ceramic powder of the yttrium-aluminum garnet doped with cerium was obtained by the two-stage precipitation method. The silver nanoparticles sol was introduced into the precursor powder before calcination in concentrations from 0,125 to 0,1 ml. It was shown that the photoluminescence intensity increased in comparison with the reference when we used this method of introducing silver nanoparticles. The optimal concentration within the study was 0,25 ml. At this concentration, the increase in the photoluminescence intensity at a wavelength of 540 nm was about 10%. Studies have shown that silver nanoparticles can be successfully used to increase the brightness of the phosphor of the yttrium-aluminum garnet doped with cerium without distortion and deterioration of spectral characteristics.
Within the framework of this work, the results are presented of a study of the effect of the concentrations of the stabilizer and precursor on the synthesis of silver nanoparticles. Silver nitrate was used as a precursor, and polyethylene glycol with a molecular weight from 200 to 600 Da was used as a stabilizer. The synthesis was carried out by the method of chemical reduction in an aqueous medium. The obtained samples were investigated by photon correlation spectroscopy and spectrophotometry. The presence of a characteristic absorption band at 400 nm in the absorption spectra of all samples of nanosized silver stabilized with polyethylene glycol was established, which is due to the appearance of surface plasmon resonance in metallic silver nanoparticles. It was also found that at the highest and lowest concentration of the stabilizer, equal, respectively, 0,005 and 0,1 mass. %, the formation of large silver particles with an average hydrodynamic radius from 132 to 1900 nm is observed in the reaction system. As a result, the optimal parameters for the synthesis of aggregatively stable silver nanoparticles were determined: the concentration of silver nitrate CM(AgNO3)=0,05 M and the concentration of polyethylene glycol equal to 0,01 – 0,05 %. Computer quantum-chemical modeling is carried out. It is found that the interaction of the silver atom with the terminal hydroxogroup in the polyethylene glycol molecule in the elementary act of interaction during the stabilization of silver nanoparticles by this polymer is energetically advantageous. This type of interaction is characterized by an absolute chemical hardness equal to η=0,146, and an internal energy of E=–2048,34 kcal / mol.