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Proteins can form droplets via liquid–liquid phase separation (LLPS) in cells. Recent experiments demonstrate that LLPS is qualitatively different on two-dimensional (2D) surfaces compared to three-dimensional (3D) solutions. In this paper, we use mathematical modeling to investigate the causes of the discrepancies between LLPS in 2D and 3D. We model the number of proteins and droplets inducing LLPS by continuous-time Markov chains and use chemical reaction network theory to analyze the model. To reflect the influence of space dimension, droplet formation and dissociation rates are determined using the first hitting times of diffusing proteins. We first show that our stochastic model reproduces the appropriate phase diagram and is consistent with the relevant thermodynamic constraints. After further analyzing the model, we find that it predicts that the space dimension induces qualitatively different features of LLPS, which are consistent with recent experiments. While it has been claimed that the differences between 2D and 3D LLPS stem mainly from different diffusion coefficients, our analysis is independent of the diffusion coefficients of the proteins since we use the stationary model behavior. Our results thus give new hypotheses about how space dimension affects LLPS. [ABSTRACT FROM AUTHOR]

Recent experiments indicated that nanoparticles (NPs) might efficiently catalyze multiple chemical reactions, frequently exhibiting new phenomena. One of those surprising observations is intra-particle catalytic cooperativity, when the reactions at one active site can stimulate the reactions at spatially distant sites. Theoretical explanations of these phenomena have been presented, pointing out the important role of charged hole dynamics. However, the crucial feature of nanoparticles that can undergo dynamic structural surface rearrangements, potentially affecting the catalytic properties, has not yet been accounted for. We present a theoretical study of the effect of dynamic restructuring in NPs on intra-particle catalytic cooperativity. It is done by extending the original static discrete-state stochastic framework that quantitatively evaluates the catalytic communications. The dynamic restructuring is modeled as stochastic transitions between states with different dynamic properties of charged holes. Our analysis reveals that the communication times always decrease with increasing rates of dynamic restructuring, while the communication lengths exhibit a dynamic behavior that depends on how dynamic fluctuations affect migration and death rates of charged holes. Computer simulations fully support theoretical predictions. These findings provide important insights into the microscopic mechanisms of catalysis on single NPs, suggesting specific routes to rationally design more efficient catalytic systems. [ABSTRACT FROM AUTHOR]

In a companion paper, we put forth a thermodynamic model for complex formation via a chemical reaction involving multiple macromolecular species, which may subsequently undergo liquid–liquid phase separation and a further transition into a gel-like state. In the present work, we formulate a thermodynamically consistent kinetic framework to study the interplay between phase separation, chemical reaction, and aging in spatially inhomogeneous macromolecular mixtures. A numerical algorithm is also proposed to simulate domain growth from collisions of liquid and gel domains via passive Brownian motion in both two and three spatial dimensions. Our results show that the coarsening behavior is significantly influenced by the degree of gelation and Brownian motion. The presence of a gel phase inside condensates strongly limits the diffusive transport processes, and Brownian motion coalescence controls the coarsening process in systems with high area/volume fractions of gel-like condensates, leading to the formation of interconnected domains with atypical domain growth rates controlled by size-dependent translational and rotational diffusivities. [ABSTRACT FROM AUTHOR]

We investigate the vibrational ultrastrong coupling between molecular vibrations of water molecules and surface lattice resonances (SLRs) sustained by extended arrays of plasmonic microparticles. We design and fabricate an array of gold bowties, which sustain a very high field enhancement, with its SLR resonated with the OH stretching modes of water. We measure a Rabi splitting of 567 cm−1 in the strongly coupled system, whose coupling strength is 8% of the OH vibrational energy, at the onset of the ultrastrong coupling regime (10%). These results introduce metallic microparticle arrays as a platform for the investigation of ultrastrong coupling, which could be used in polaritonic chemistry to modify the dynamics of chemical reactions that require high coupling strengths. [ABSTRACT FROM AUTHOR]

The chemical reactions between certain interstellar molecules are exothermic in nature and barrierless in the entrance channel, allowing these reactions to occur rapidly even at low astronomical temperatures, e.g., C and O2 interaction. Obtaining detailed rovibrational transition parameters for the reaction between C and O2, such as state-selected rate coefficients, is crucial for studying the associated atmospheric and astronomical environments. Hence, this work presents an approach that combines quasi-classical trajectory calculations with machine learning techniques based on Neural Network (NN) and Gaussian Process Regression (GPR) to determine state-selected rate coefficients. Employing this approach, we significantly reduced the computational requirements while simultaneously obtaining the accurate state-selected reaction cross sections and rate coefficients for the collision of C and O2. Both the NN-based and GPR-based models established in this work accurately predict the results calculated from explicit numerical calculations in the explored temperature range of 50–1500 K, achieving a coefficient of determination R2 > 0.96. Most importantly, the current work provides the most comprehensive dataset of rovibrational rate coefficients of v = 0–4, j = 0–70 → v′ = 0–15 for the astrophysical modeling of the C–O2 collision system. [ABSTRACT FROM AUTHOR]

The coupled structural and electronic parameters of intramolecular hydrogen bonding play an important role in ultrafast chemical reactions, such as proton transfer processes. We perform one- and two-dimensional vibrational–electronic (1D and 2D VE) spectroscopy experiments to understand the couplings between vibrational and electronic coordinates in 10-Hydroxybenzo[h]quinoline, an ultrafast proton transfer system. The experiments reveal that the OH stretch (νOH) is strongly coupled to the electronic excitation, and Fourier analysis of the 1D data shows coherent oscillations from the low frequency backbone vibrational modes coupled to the νOH mode, resulting in an electronically detected vibronic signal. In-plane low-frequency vibrations at 242 and 386 cm−1 change the hydrogen bond distance and modulate the observed electronic signal in the polarization-selective 1D VE experiment through orientation-dependent coupling with the νOH mode. Resolution of the excitation frequency axis with 2D VE experiments reveals that excitation frequency, detection frequency, and experimental delay affect the frequency and strength of the vibronic transitions observed. Our results demonstrate evidence of direct coupling of the high frequency νOH mode with the S1 ← S0 electronic transition in 10-Hydroxybenzo[h]quinoline (HBQ), and orientation-dependent couplings of the low-frequency 242 and 386 cm−1 modes to the νOH mode and the electronic transition. This demonstration of multidimensional VE spectroscopy on HBQ reveals the potential of using 1D and 2D VE spectroscopy to develop a quantitative understanding of the role of vibronic coupling in hydrogen bonding and ultrafast proton transfer for complex systems. [ABSTRACT FROM AUTHOR]

We develop a framework describing the dynamics and thermodynamics of open non-ideal reaction–diffusion systems, which embodies Flory–Huggins theories of mixtures and chemical reaction network theories. Our theory elucidates the mechanisms underpinning the emergence of self-organized dissipative structures in these systems. It evaluates the dissipation needed to sustain and control them, discriminating the contributions from each reaction and diffusion process with spatial resolution. It also reveals the role of the reaction network in powering and shaping these structures. We identify particular classes of networks in which diffusion processes always equilibrate within the structures, while dissipation occurs solely due to chemical reactions. The spatial configurations resulting from these processes can be derived by minimizing a kinetic potential, contrasting with the minimization of the thermodynamic free energy in passive systems. This framework opens the way to investigating the energetic cost of phenomena, such as liquid–liquid phase separation, coacervation, and the formation of biomolecular condensates. [ABSTRACT FROM AUTHOR]

Chemical reactions and vapor–liquid equilibria for molten lithium hydroxide (LiOH) were studied using molecular dynamics simulations and a deep potential (DP) model. The neural network for the model was trained on quantum density functional theory data for a range of conditions. The DP model allows simulations over timescales of hundreds of ns, which provide equilibrium compositions for the systems of interest. Single-phase NPT simulations of the liquid show the decomposition of LiOH into lithium oxide (Li2O) and dissolved water (H2O). These DP results were validated by direct ab initio molecular dynamics simulations that confirmed the accuracy of the model with respect to reaction kinetics and equilibrium properties of the melt. The reactive vapor–liquid behavior of this system was subsequently studied using direct coexistence interfacial DP simulations. Partial pressures of H2O in the vapor are found to be in close agreement with available experimental measurements. By fitting temperature-dependent expressions for the reaction equilibrium and Henry's law constants, the equilibrium composition for any given initial composition and temperature can be quantitatively modeled. For high initial concentrations of Li2O or H2O, mixtures of LiOH + Li2O/H2O are found to undergo phase separation. The present study illustrates how DP-based molecular dynamics simulations can be used for quantitative modeling of multiphase reactive behavior with the accuracy of the underlying ab initio quantum chemical methods. [ABSTRACT FROM AUTHOR]

Shock-induced energy localization is a crucial mechanism for determining shock sensitivity of energetic materials (EMs). Hotspots, i.e., localized areas of elevated temperature, arise when shocks interact with defects (cracks, pores, and interfaces) in the EM microstructure. The ignition and growth of hotspots in a shocked energetic material contribute to rapid chemical reactions that can couple with the passing shock wave, potentially leading to a self-sustained detonation wave. Predictive models for shock-to-detonation transition must correctly capture hotspot dynamics, which demands high-fidelity material models for meso-scale calculations. In this work, we deploy atomistics-guided material models for the energetic crystal RDX (1,3,5-trinitro-1,3,5-triazinane) and perform tandem continuum and all-atom molecular dynamics (MD) simulations. The computational setup for the continuum and MD simulations are nearly identical. The material models used for the calculations are derived from MD data, particularly the equations of state, rate-dependent Johnson–Cook strength model, and pressure-dependent shear modulus and melting temperature. We show that a modified Johnson–Cook model that accounts for shear-induced localization at the pore surface is necessary to represent well—relative to MD as the ground truth—the inelastic response of the crystal under a range of shock conditions. A head-to-head comparison of continuum and atomistic calculations across several metrics of pore collapse and energy deposition demonstrates that the continuum calculations are in good overall agreement with MD. Therefore, this work provides improved RDX material models to perform physically accurate meso-scale simulations, to enhance understanding of hot spot formation, and to use meso-scale hot spot data to inform macro-scale shock simulations. [ABSTRACT FROM AUTHOR]

Surface functionalization of low-dimensional nanomaterials offers a means to tailor their optoelectronic and chemical characteristics. However, functionalization reactions are sensitive to the inherent surface features of nanomaterials, such as defects, grain boundaries, and edges. Conventional optical characterization methods, such as Raman spectroscopy, have limited sensitivity and spatial resolution and, therefore, struggle to visualize reaction sites and chemical species. Here, we demonstrate the capability of spatially and chemically sensitive tip-enhanced Raman spectroscopy imaging to map the distribution of molecules in covalently functionalized graphene. Hyperspectral vertex component analysis and density functional theory are necessary to interpret the nature of binding sites and extract information from the spatially and spectrally heterogeneous datasets. Our results clarify the origin of heterogeneous surface functionalization, resolving preferential binding at edges and defects. This work demonstrates the potential of nanospectroscopic tools combined with unsupervised learning to characterize complex, partially ordered optoelectronic nanomaterials. [ABSTRACT FROM AUTHOR]

Self-propelled synthetic particles have attracted scientific interest due to their potential applications as nanomotors in drug delivery and their insight into bacterial taxis. Research on their dynamics has focused on understanding phoresis and self-phoresis in catalytic Janus particles at both the nano- and microscale. This study explores the combined effects of self-diffusiophoresis and self-thermophoresis induced by exothermic chemical reactions on the surface of active particles moving in non-electrolyte media. We examine how these phoretic phenomena interact, influenced by the coupling between chemical reactions, heat generation, and the concentration and temperature fields at the particle interface. Using a theoretical framework based on the induction of surface tension gradients at the particle interface, we analyze the phoretic dynamics, quantifying parameters such as effective diffusivities, transport coefficients, and, most importantly, phoretic coefficients. Our findings provide insights into the conditions that dictate coupled or independent phoretic behaviors, with implications for drug delivery and nanomotor applications, enabling customized transport processes at the nanoscale. [ABSTRACT FROM AUTHOR]

ReaxFF reactive molecular dynamics has significantly advanced the exploration of chemical reaction mechanisms in complex systems. However, it faces several challenges: (1) the prevalent use of excessively high temperatures (>2000 K), (2) a time scale considerably shorter than the experimental timeframes (nanoseconds vs seconds), and (3) the constraining impact of dimensionality growth due to collective variables on the expansiveness of research systems. To overcome these issues, we introduced Parallel Collective Variable-Driven Adaptive Accelerated Reaction Molecular Dynamics (PCVR), which integrates metadynamics with ReaxFF. This method incorporates bond distortion based on each bond type for customized Collective Variable (CV) parameterization, facilitating independent parallel acceleration. Simultaneously, the sampling was confined to fixed cutoff ranges for distinct bond distortions, effectively overcoming the challenge of the CV dimensionality explosion. This extension enhances the applicability of ReaxFF to non-strongly coupled systems with numerous reaction energy barriers and mitigates the system size limitations. Using accelerated reactive molecular dynamics, the oxidation of ester-based oil was simulated with 31 808 atoms at 500 K for 64 s. This achieved 61% efficiency compared to the original ReaxFF and was ∼37 times faster than previous methods. Unlike ReaxFF's high-temperature constraints, PCVR accurately reveals the pivotal role of oxygen in ester oxidation at industrial temperatures, producing polymers consistent with the sludge formation observed in ester degradation experiments. This method promises to advance reactive molecular dynamics by enabling simulations at lower temperatures, extending to second-level timescales, and accommodating systems with millions of atoms. [ABSTRACT FROM AUTHOR]

Stepwise two-photon absorption processes have received considerable attention, especially in photocatalysis, due to their relatively lower power threshold, characteristic spatial selectivity, amplification of chemical reactions, and so on. Meanwhile, studies on the relaxation dynamics of higher excited states in condensed systems have been limited for several molecular systems due to the short-lived nature of these states. In this study, we synthesized perylene-substituted perylene bisimide (PBI) and its derivate as model compounds and investigated their excited-state dynamics, including higher excited states, using pump–repump–probe spectroscopy. We revealed that these molecules form charge-transfer (CT) states instantaneously after the excitation, regardless of whether it is the perylene moiety or the PBI moiety that is excited. The lifetime of the CT state was shorter when the distance between the donor (perylene) and the acceptor (PBI) was shorter. Moreover, we also revealed that a higher-lying CT state generated by the stepwise excitation of the CT state using a 740-nm pulse induced Stark effect to the neighboring perylene moiety. The Stark effect not only gives more detailed information about the CT state, but also presents the possibility of new photofunctions, such as instantaneous modulation of the electronic state to achieve optimal electronic properties. These insights contribute to understanding advanced photochemical reactions and would be important for exploring photocatalytic reactions involving higher excited states. [ABSTRACT FROM AUTHOR]

Reliable thermodynamic and kinetic properties of free radical polymerization reactions are essential for synthesizing both primary polymeric materials and specialty polymers. The computational generation of these data from quantum chemistry requires a time-efficient method capable of capturing the essential physics. One such method, fixed-node diffusion Monte Carlo (FN-DMC) (using single Slater–Jastrow trial wavefunctions), has demonstrated the capability to recover 90%–95% of missing dynamic correlation energy for typical systems. In this study, methyl radical addition to ethylene serves as a simple model to test FN-DMC's ability to calculate enthalpies of reaction and activation energies with different time steps, antisymmetric trial wavefunctions, basis set sizes, and effective core potentials. The FN-DMC computational protocol thus defined for methyl radical addition to ethylene is subsequently benchmarked against Weizmann-1 and experimental reaction enthalpies from Lin et al.'s test set of 21 radical addition and 28 hydrogen abstraction enthalpies. Our findings reveal that FN-DMC consistently generates reaction enthalpies with chemical accuracy, exhibiting mean absolute deviation of 3.5(7) and 1.4(8) kJ/mol from the Weizmann-1 reference for radical addition and hydrogen abstraction reactions, respectively. Given its favorable computational scaling and high degree of parallelizability, we, therefore, recommend more comprehensive testing of FN-DMC with effective core potentials to address more extensive and intricate polymerization reactions and reactions with other radicals. [ABSTRACT FROM AUTHOR]

We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software application to design custom coarse-grained (CG) models, as well as pre-defined models of polyelectrolytes, peptides, and globular proteins in the Extensible Simulation Package for Research on Soft Matter (ESPResSo). The Python interface of ESPResSo offers a flexible framework, capable of building custom CG models from scratch. As a downside, building CG models from scratch is prone to mistakes, especially for newcomers in the field of CG modeling, or for molecules with complex architectures. The pyMBE module builds CG models in ESPResSo using a hierarchical bottom-up approach, providing a robust tool to automate the setup of CG models and helping new users prevent common mistakes. ESPResSo features the constant pH (cpH) and grand-reaction (G-RxMC) methods, which have been designed to study chemical reaction equilibria in macromolecular systems with many reactive species. However, setting up these methods for systems, which contain several types of reactive groups, is an error-prone task, especially for beginners. The pyMBE module enables the automatic setup of cpH and G-RxMC simulations in ESPResSo, lowering the barrier for newcomers and opening the door to investigate complex systems not studied with these methods yet. To demonstrate some of the applications of pyMBE, we showcase several case studies where we successfully reproduce previously published simulations of charge-regulating peptides and globular proteins in bulk solution and weak polyelectrolytes in dialysis. The pyMBE module is publicly available as a GitHub repository (https://github.com/pyMBE-dev/pyMBE), which includes its source code and various sample and test scripts, including the ones that we used to generate the data presented in this article. [ABSTRACT FROM AUTHOR]

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium. [ABSTRACT FROM AUTHOR]

Multicomponent macromolecular mixtures often form higher-order structures, which may display non-ideal mixing and aging behaviors. In this work, we first propose a minimal model of a quaternary system that takes into account the formation of a complex via a chemical reaction involving two macromolecular species; the complex may then phase separate from the buffer and undergo a further transition into a gel-like state. We subsequently investigate how physical parameters such as molecular size, stoichiometric coefficients, equilibrium constants, and interaction parameters affect the phase behavior of the mixture and its propensity to undergo aging via gelation. In addition, we analyze the thermodynamic stability of the system and identify the spinodal regions and their overlap with gelation boundaries. The approach developed in this work can be readily generalized to study systems with an arbitrary number of components. More broadly, it provides a physically based starting point for the investigation of the kinetics of the coupled complex formation, phase separation, and gelation processes in spatially extended systems. [ABSTRACT FROM AUTHOR]

Charged molecules play essential roles in many natural and artificial functional processes, ranging from photosynthesis to photovoltaics to chemical reactions and more. It is often difficult to identify the optical dynamic properties of relevant redox species because they cannot be easily prepared, their spectra overlap, or they evolve on a femtosecond timescale. Here, we address these challenges by combining spectroelectrochemistry, ultrafast transient absorption spectroscopy, and suitable data analysis. We illustrate the method with the various redox species of a cyclophane composed of two perylene bisimide subunits. While singular-value decomposition is a well-established tool in the analysis of time-dependent spectra of a single molecular species, we here use it additionally to separate transient maps of individual redox species. This is relevant because at any specific applied electrochemical potential, several redox species coexist in the ensemble, and our procedure allows disentangling their spectroscopic response. In the second step, global analysis is then employed to retrieve the excited-state lifetimes and decay-associated difference spectra. Our approach is generally suitable for unraveling ultrafast dynamics in materials featuring charge-transfer processes. [ABSTRACT FROM AUTHOR]

Droplets are essential for spatially controlling biomolecules in cells. To work properly, cells need to control the emergence and morphology of droplets. On the one hand, driven chemical reactions can affect droplets profoundly. For instance, reactions can control how droplets nucleate and how large they grow. On the other hand, droplets coexist with various organelles and other structures inside cells, which could affect their nucleation and morphology. To understand the interplay of these two aspects, we study a continuous field theory of active phase separation. Our numerical simulations reveal that reactions suppress nucleation while attractive walls enhance it. Intriguingly, these two effects are coupled, leading to shapes that deviate substantially from the spherical caps predicted for passive systems. These distortions result from anisotropic fluxes responding to the boundary conditions dictated by the Young–Dupré equation. Interestingly, an electrostatic analogy of chemical reactions confirms these effects. We thus demonstrate how driven chemical reactions affect the emergence and morphology of droplets, which could be crucial for understanding biological cells and improving technical applications, e.g., in chemical engineering. [ABSTRACT FROM AUTHOR]

In this work, we systematically investigate the mechanisms underlying the rate modification of ground-state chemical reactions in an optical cavity under vibrational strong-coupling conditions. We employ a symmetric double-well description of the molecular potential energy surface and a numerically exact open quantum system approach—the hierarchical equations of motion in twin space with a matrix product state solver. Our results predict the existence of multiple peaks in the photon frequency-dependent rate profile for a strongly anharmonic molecular system with multiple vibrational transition energies. The emergence of a new peak in the rate profile is attributed to the opening of an intramolecular reaction pathway, energetically fueled by the cavity photon bath through a resonant cavity mode. The peak intensity is determined jointly by kinetic factors. Going beyond the single-molecule limit, we examine the effects of the collective coupling of two molecules to the cavity. We find that when two identical molecules are simultaneously coupled to the same resonant cavity mode, the reaction rate is further increased. This additional increase is associated with the activation of a cavity-induced intermolecular reaction channel. Furthermore, the rate modification due to these cavity-promoted reaction pathways remains unaffected, regardless of whether the molecular dipole moments are aligned in the same or opposite direction as the light polarization. [ABSTRACT FROM AUTHOR]

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with standard chemical potentials, we derive and compare the free energy dissipation and the entropy production rates. We express the relation between entropy production and the chemical master equation for modeling metabolism, which unifies chemical kinetics and chemical thermodynamics. Because prediction uncertainty with respect to parameter variability is frequently a concern with mass action models utilizing rate constants, we compare and contrast the maximum entropy model, which has its own set of rate parameters, to a population of standard mass action models in which the rate constants are randomly chosen. We show that a maximum entropy model is characterized by a high probability of free energy dissipation rate and likewise entropy production rate, relative to other models. We then characterize the variability of the maximum entropy model predictions with respect to uncertainties in parameters (standard free energies of formation) and with respect to ionic strengths typically found in a cell. [ABSTRACT FROM AUTHOR]

The spur reaction, a spatially nonhomogeneous chemical reaction following ionization, is crucial in radiolysis or photolysis in liquids, but the spur expansion process has yet to be elucidated. One reason is the need to understand the role of the dielectric response of the solvating molecules surrounding the charged species generated by ionization. The dielectric response corresponds to the time evolution of the permittivity and might affect the chemical reaction–diffusion of the species in a spur expansion process. This study examined the competitive relationship between reaction–diffusion kinetics and the dielectric response by solving the Debye–Smoluchowski equation while considering the dielectric response. The Coulomb force between the charged species gradually decreases with the dielectric response. Our calculation results found a condition where fast recombination occurs before the dielectric response is complete. Although it has been reported that the primary G-values of free electrons depend on the static dielectric constant under low-linear-energy transfer radiation-induced ionization, we propose that considering the dielectric response can provide a deeper insight into fast recombination reactions under high-linear-energy transfer radiation- or photo-induced ionization. Our simulation method enables the understanding of fast radiation-induced phenomena in liquids. [ABSTRACT FROM AUTHOR]

Experimental studies of the products of elementary gas-phase chemical reactions occurring at low temperatures (<50 K) are very scarce, but of importance for fundamental studies of reaction dynamics, comparisons with high-level quantum dynamical calculations, and, in particular, for providing data for the modeling of cold astrophysical environments, such as dense interstellar clouds, the atmospheres of the outer planets, and cometary comae. This study describes the construction and testing of a new apparatus designed to measure product branching fractions of elementary bimolecular gas-phase reactions at low temperatures. It combines chirped-pulse Fourier transform millimeter wave spectroscopy with continuous uniform supersonic flows and high repetition rate laser photolysis. After a comprehensive description of the apparatus, the experimental procedures and data processing protocols used for signal recovery, the capabilities of the instrument are explored by the study of the photodissociation of acrylonitrile and the detection of two of its photoproducts, HC3N and HCN. A description is then given of a study of the reactions of the CN radical with C2H2 at 30 K, detecting the HC3N product, and with C2H6 at 10 K, detecting the HCN product. A calibration of these two products is finally attempted using the photodissociation of acrylonitrile as a reference process. The limitations and possible improvements in the instrument are discussed in conclusion. [ABSTRACT FROM AUTHOR]

In our recent publication, we have proposed a revised base excision repair pathway in which DNA polymerase β (Polβ) catalyzes Schiff base formation prior to the gap-filling DNA synthesis followed by β-elimination. In addition, the polymerase activity of Polβ employs the "three-metal ion mechanism" instead of the long-standing "two-metal ion mechanism" to catalyze phosphodiester bond formation based on the fact derived from time-resolved x-ray crystallography that a third Mg2+ was captured in the polymerase active site after the chemical reaction was initiated. In this study, we develop the models of the uncross-linked and cross-linked Polβ complexes and investigate the "three-metal ion mechanism" vs the "two-metal ion mechanism" by using the quantum mechanics/molecular mechanics molecular dynamics simulations. Our results suggest that the presence of the third Mg2+ ion stabilizes the reaction-state structures, strengthens correct nucleotide binding, and accelerates phosphodiester bond formation. The improved understanding of Polβ's catalytic mechanism provides valuable insights into DNA replication and damage repair. [ABSTRACT FROM AUTHOR]

Chemical shakers are active particles with zero propulsion velocity whose activity derives from chemical reactions on portions of their surfaces. Although they do not move, except through Brownian motion, the nonequilibrium concentration and velocity fields that they generate endow them with properties that differ from their equilibrium counterparts. In particular, collections of such shakers can actively move, reorient, and self-assemble into various cluster states, which are the subject of this paper. Elongated chemical shakers constructed from linked catalytic and noncatalytic spheres are considered, and it is shown how hydrodynamic, chemotactic, and shape-dependent interactions give rise to various self-assembled shaker structures. The chemical forces responsible for cluster formation are described in terms of a model based on pair-wise additive contributions. The forms of the self-assembled structures can be varied by changing the chemostat concentrations that control the nonequilibrium state. The resulting structures and their manipulation through chemical means suggest ways to construct a class of active materials for applications. [ABSTRACT FROM AUTHOR]

Chemical reaction networks can undergo nonequilibrium phase transitions upon variation in external control parameters, such as the chemical potential of a species. We investigate the flux in the associated chemostats that is proportional to the entropy production and its critical fluctuations within the Schlögl model. Numerical simulations show that the corresponding diffusion coefficient diverges at the critical point as a function of system size. In the vicinity of the critical point, the diffusion coefficient follows a scaling form. We develop an analytical approach based on the chemical Langevin equation and van Kampen's system size expansion that yields the corresponding exponents in the monostable regime. In the bistable regime, we rely on a two-state approximation in order to analytically describe the critical behavior. [ABSTRACT FROM AUTHOR]

Incorporating self-interaction corrections (SIC) significantly improves chemical reaction barrier height predictions made using density functional theory methods. We present a detailed orbital-by-orbital analysis of these corrections for three semi-local density functional approximations (DFAs) situated on the three lowest rungs of Jacob's ladder of approximations. The analysis is based on Fermi–Löwdin Orbital Self-Interaction Correction (FLOSIC) calculations performed at several steps along the reaction pathway from the reactants (R) to the transition state (TS) to the products (P) for four representative reactions selected from the BH76 benchmark set. For all three functionals, the major contribution to self-interaction corrections of the barrier heights can be traced to stretched bond orbitals that develop near the TS configuration. The magnitude of the ratio of the self-exchange–correlation energy to the self-Hartree energy (XC/H) for a given orbital is introduced as an indicator of one-electron self-interaction error. XC/H = 1.0 implies that an orbital's self-exchange–correlation energy exactly cancels its self-Hartree energy and that the orbital, therefore, makes no contribution to the SIC in the FLOSIC scheme. For the practical DFAs studied here, XC/H spans a range of values. The largest values are obtained for stretched or strongly lobed orbitals. We show that significant differences in XC/H for corresponding orbitals in the R, TS, and P configurations can be used to identify the major contributors to the SIC of barrier heights and reaction energies. Based on such comparisons, we suggest that barrier height predictions made using the strongly constrained and appropriately normed meta-generalized gradient approximation may have attained the best accuracy possible for a semi-local functional using the Perdew–Zunger SIC approach. [ABSTRACT FROM AUTHOR]

The electronic energies of molecules have been successfully evaluated on quantum computers. However, more attention is paid to the dynamics simulation of molecules in practical applications. Based on the variational quantum eigensolver (VQE) algorithm, Fedorov et al. proposed a correlated sampling (CS) method and demonstrated the vibrational dynamics of H2 molecules [J. Chem. Phys. 154, 164103 (2021)]. In this study, we have developed a quantum approach by extending the CS method based on the VQE algorithm (labeled eCS-VQE) for simulating chemical reaction dynamics. First, the CS method is extended to the three-dimensional cases for calculation of first-order energy gradients, and then, it is further generalized to calculate the second-order gradients of energies. By calculating atomic forces and vibrational frequencies for H2, LiH, H+ + H2, and Cl− + CH3Cl systems, we have seen that the approach has achieved the CCSD level of accuracy. Thus, we have simulated dynamics processes for two typical chemical reactions, hydrogen exchange and chlorine substitution, and obtained high-precision reaction dynamics trajectories consistent with the classical methods. Our eCS-VQE approach, as measurement expectations and ground-state wave functions can be reused, is less demanding in quantum computing resources and is, therefore, a feasible means for the dynamics simulation of chemical reactions on the current noisy intermediate-scale quantum-era quantum devices. [ABSTRACT FROM AUTHOR]

Chemical reactions can induce Marangoni flows by changing the surface tension of a solution open to the air, either by changing the composition and/or by modifying the temperature. We consider the case of a simple A + B → C reaction front propagating in a thin horizontal system open to air. The effect of the three chemical species on the surface tension of the aqueous solution is quantified by three solutal Marangoni numbers, while the effect of temperature changes is determined by the thermal Marangoni number. By integrating numerically the incompressible Navier–Stokes equations coupled to reaction-diffusion-convection equations for the chemical concentrations and temperature taking into account the Lewis number (ratio between heat and mass diffusivities), we emphasize the importance of thermal changes occurring due to the heat of reaction on the dynamics of chemically induced Marangoni convection. Based on the reaction-diffusion profiles of concentrations and temperature, asymptotic analytical solutions for the surface tension profiles are obtained and classified as a function of the Marangoni numbers and the Lewis number. This new classification allows for the prediction of the convective patterns in thermo-solutal Marangoni flows. The analytical predictions are further confirmed by numerical results and additional extrema in surface tension profiles induced by the thermal effects are found to affect the nonlinear dynamics. [ABSTRACT FROM AUTHOR]

The activation volume, which quantifies the response of the chemical reactions to the applied stress, plays a central role in controlling the mechanochemical reactions for applications including lubricity, wear, and the topographic fabrication of the surfaces under stress. However, the physical interpretations of the activation volume remain scientifically intriguing and largely unexplored. Here, density functional theory calculations are used to investigate the general rules of charge transfer underlying activation volume in controlling the typically mechanochemical reaction process. It is found that the activation volume could be decoupled into the electronic contributions from interface chemistry and bulk physical deformation, which are commonly linear dependent on the contact pressure. Therefore, the activation volume may, indeed, be derived from the stress-driven charge transfer underlying cooperative competition between interfacial chemistry and the bulk region. This competition is related to the stiffness change from the bulk to slab. The magnitude of the stiffness change represents the degree to which the interface atoms modify the bulk properties, which is directly related to the contribution of different regions to the activation volume. This work may open up the understanding of the activation volume from dynamic electron transfer to engineer mechanochemical reactions, different from the existing insights into the geometric dimensionality of the contact configuration. [ABSTRACT FROM AUTHOR]

We have investigated, using molecular dynamics, the surface chemistry of hydrogen incident on the amorphous and crystalline lithium oxide and lithium hydroxide surfaces upon being slowed down by a collision cascade and retained in the amorphous surface of either Li2O or LiOH. We looked for the bonding of H to the resident structures in the surface to understand a possible chain of chemical reactions that can lead to surface transformation upon H atom impact. Our findings, using Density-Functional Theory (DFT) trained ReaxFF force field/electronegativity equalization method potentials, stress the importance of inclusion of polarization in the dynamics of a Li–O–H system, which is also illustrated by DFT energy minimization and quantum–classical molecular dynamics using tight binding DFT. The resulting polar-covalent chemistry of the studied systems is complex and very sensitive to the instantaneous positions of all atoms as well as the ratio of concentrations of various resident atoms in the surface. [ABSTRACT FROM AUTHOR]

We study an autonomous model of a Maxwell demon that works by rectifying thermal fluctuations of chemical reactions. It constitutes the chemical analog of a recently studied electronic demon. We characterize its scaling behavior in the macroscopic limit, its performances, and the impact of potential internal delays. We obtain analytical expressions for all quantities of interest: the generated reverse chemical current, the output power, the transduction efficiency, and correlation between the number of molecules. Due to a bound on the nonequilibrium response of its chemical reaction network, we find that, contrary to the electronic case, there is no way for the Maxwell demon to generate a finite output in the macroscopic limit. Finally, we analyze the information thermodynamics of the Maxwell demon from a bipartite perspective. In the limit of a fast demon, the information flow is obtained, its pattern in the state space is discussed, and the behavior of partial efficiencies related to the measurement and feedback processes is examined. [ABSTRACT FROM AUTHOR]

For an electronic system, given a mean field method and a distribution of orbital occupation numbers that are close to the natural occupations of the correlated system, we provide formal evidence and computational support to the hypothesis that the entropy (or more precisely −σS, where σ is a parameter and S is the entropy) of such a distribution is a good approximation to the correlation energy. Underpinning the formal evidence are mild assumptions: the correlation energy is strictly a functional of the occupation numbers, and the occupation numbers derive from an invertible distribution. Computational support centers around employing different mean field methods and occupation number distributions (Fermi–Dirac, Gaussian, and linear), for which our claims are verified for a series of pilot calculations involving bond breaking and chemical reactions. This work establishes a formal footing for those methods employing entropy as a measure of electronic correlation energy (e.g., i-DMFT [Wang and Baerends, Phys. Rev. Lett. 128, 013001 (2022)] and TAO-DFT [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)]) and sets the stage for the widespread use of entropy functionals for approximating the (static) electronic correlation. [ABSTRACT FROM AUTHOR]

Designing and predicting self-organized pattern formation in out-of-equilibrium chemical and biochemical reactions holds fundamental significance. External perturbations like light and electric fields exert a crucial influence on reaction-diffusion systems involving ionic species. While the separate impacts of light and electric fields have been extensively studied, comprehending their combined effects on spatiotemporal dynamics is paramount for designing versatile spatial orders. Here, we theoretically investigate the spatiotemporal dynamics of chlorine dioxide-iodine-malonic acid reaction-diffusion system under photo-illumination and circularly polarized electric field (CPEF). By applying CPEF at varying intensities and frequencies, we observe the predominant emergence of oscillating hexagonal spot-like patterns from homogeneous stable steady states. Furthermore, our study unveils a spectrum of intriguing spatiotemporal instabilities, encompassing stripe-like patterns, oscillating dumbbell-shaped patterns, spot-like instabilities with square-based symmetry, and irregular chaotic patterns. However, when we introduce periodic photo-illumination to the hexagonal spot-like instabilities induced by CPEF in homogeneous steady states, we observe periodic size fluctuations. Additionally, the stripe-like instabilities undergo alternating transitions between hexagonal spots and stripes. Notably, within the Turing region, the interplay between these two external influences leads to the emergence of distinct superlattice patterns characterized by hexagonal-and square-based symmetry. These patterns include parallel lines of spots, target-like formations, black-eye patterns, and other captivating structures. Remarkably, the simple perturbation of the system through the application of these two external fields offers a versatile tool for generating a wide range of pattern-forming instabilities, thereby opening up exciting possibilities for future experimental validation. [ABSTRACT FROM AUTHOR]

In the catalytic layer of proton exchange membrane fuel cells, water molecules in ionomers tend to be accumulated at the ionomer/Pt interface, preventing oxygen from reaching the Pt surface to participate in chemical reactions. It is necessary to take measures to improve the water molecules distribution and proton transport performance in the ionomer on the Pt surface. In this work, the effect of "acid–base pair" functionalized graphene oxide (AB‐GO) as the additive on the distribution of water molecules and transport property in the ionomer is evaluated. The results demonstrate that with the addition of AB‐GO, the distribution uniformity of water molecules and hydronium ions in the ionomer on the Pt surface is improved. The connectivity of water cluster is also increased. When the doping ratio of BAF‐GO and TF‐GO is 1:3, the connectivity coefficient of water cluster is about 1.37 times that of Nafion ionomer without the doping. [ABSTRACT FROM AUTHOR]

Natural gas supported co-combustion of gaseous and solid fuels (biomass, coal, and polyethylene) was carried out in a reciprocal porous media reactor (RFR) to evaluate the suitability of the concept for hydrogen (H 2) and syngas production. The reactor was designed and built to operate in semi-continuous mode, where equivalence ratio (φ), the gasifying agent, and different particle sizes of solid fuels were assessed. Rich (φ > 1) and lean (φ < 1) combustion regime were evaluated, while steam and air/steam were used as gasifying agents. The first configuration (C1) has a solid fuel volume space with a width of 25 mm and a diameter of 40 mm, and the second configuration (C2), has a diameter of 17 mm and a height of 40 mm, both in the center of the reactor. The temperature, the reaction wave propagation rate, and the resulting concentration of the main species (H 2 and CO) were measured. The maximum H 2 produced was 19.63 vol%, obtained in C2 with biomass, using only air as gasifying agent. The highest efficiency (87%) was also obtained in this case. In the case of C2, the particle matter emission concentration in the case of biomass was 1.4 g/m3, mainly of PM 4 and PM 2.5. Chemical reactions, such as water-gas-shift, methanation, Boudouard, and others, were recognized in each experimental case. This experimental work shows promising results in the search for solutions to gasify solid fuel in continuous mode. • A reciprocal flow porous media burner was used for solid fuels gasification. • Several gasifying agents were used for coal, biomass, and polyethylene. • Gasification achieved a maximum hydrogen and carbon monoxide ratio of 2.5. • Predominant gasification reactions were recognized for each experimental case. [ABSTRACT FROM AUTHOR]

[Display omitted] We have developed innovative core–shell hydrogel capsules with a dual-network shell structure designed for precise control of molecular transport in response to external stimuli such as pH and temperature. The capsules were fabricated using a combination of microfluidic electrospray techniques and water-in-water (w/w) core–shell droplets templating. The primary network of the shell, calcium alginate (Ca-Alg), with a p K a around 3.4, exhibits sensitivity to pH. The secondary network of the shell, poly(ethylene glycol) methyl ether methacrylate (PEGMA), undergoes a volume phase transition near 60 °C. These properties enable precise molecular transport control in/out of the capsules by modulating the surface charges through varying pH and modifying pore size through temperature changes. Moreover, the dual-network shell structure not only significantly enhances the mechanical strength of the capsules but also improves their stability under external stimulus, ensuring structural integrity during the transport of molecules. This research lays the groundwork for further investigations into the multimodal stimuli-responsive hydrogel systems to control molecular transport, important in applications such as sensors and reactors for chemical cascade reactions. [ABSTRACT FROM AUTHOR]

[Display omitted] Microemulsion (ME) has been investigated as a chemical polishing (CP) fluid for effective polishing of single crystal potassium dihydrogen phosphate (KDP), perfectly avoiding the generation of mechanical stress. In this work, a water-in-deep eutectic solvent ME was proposed as the polishing fluid for CP of single crystal KDP. Deep eutectic solvent (DES) is formulated using n -octanol as hydrogen bond donor and methyltrioctylammonium chloride (MTOAC) as hydrogen bond acceptor, with a mass ratio of 2:1. The ME was prepared by mixing DES as the oil phase (12.5 %, wt.), a hydrochloric acid solution as the water phase (12.5 %, wt.), and isopropanol as the cosolvent (75 %, wt.), without adding any other surfactants. The properties of the ME were characterized by conductivity measurements and ultraviolet (UV) spectroscopy. The reactivity of ME with KDP was measured by the conductivity method, and it was higher at low pH values. A hydrochloric acid solution with a pH of 3 was selected as aqueous phase, considering its effects on particle size, salt loading, and static etching rate. The water content affects the polarity of ME and the final water content was determined to be 12.5 % to ensure high polarity of ME. The surface quality of the KDP crystals before and after polishing was examined using grazing incidence X-ray diffraction (GIXRD) analysis. The average roughness of the KDP crystal surface was decreased from 1.96 nm to 1.43 nm, and the root-mean-square (RMS) roughness was reduced from 2.81 nm to 1.86 nm, demonstrating a significant polishing effect. Finally, the polishing mechanism was elucidated in terms of the irreversible chemical reaction between the active components in the microemulsion and the KDP crystals. [ABSTRACT FROM AUTHOR]

[Display omitted] Perfluorocarbon is commonly used as a coolant, chemical reaction carrier solvent, medical anti-hypoxic agents and blood substitutes. The realization of non-contact complex manipulation of perfluorocarbon liquids is urgently needed in human life and industrial production. However, most liquid-repellent interfaces are ineffective for the transport of ultra-low surface tension perfluorocarbon liquids, and struggle to maintain good durability due to unstable air or oil cushions in the surface. Therefore, preparing surfaces for stable non-contact complex manipulation of ultra-low surface tension droplets remains a challenge. In this paper, a novel solution, a photothermal responsive droplet manipulation surface based on polydimethylsiloxane brushes, has been reported. On this surface, droplets with different surface tensions (as low as 10 mN/m) can be efficiently manipulated through induced near-infrared light. Notably, this surface maintains its effectiveness after exposure to extreme anthropogenic conditions. The interface effect between perfluorocarbon droplets and polydimethylsiloxane brushes by near-infrared light-induced was investigated in detail. In addition, ultra-low surface tension droplets demonstrate the ability to transport solid particles. The conductive droplets exhibit sophisticated manipulation realizing the controlled switching of smart circuits. This research opens up new possibilities for advancing the capabilities and adaptability of ultralow surface tension droplets in a range of applications. [ABSTRACT FROM AUTHOR]

Wettability of mold flux on stainless steel is a very important index to reflect the possibility of slag entrapment during the continuous casting process. In this study, the wetting behavior of mold flux droplet with different size on stainless steel is investigated using sessile drop method. Results show that the contact angle at 1573 K increases from 64.62 ± 0.25°, 62.56 ± 0.2° to 61.46 ± 0.2° and 60.56 ± 0.2°, with the size of the original flux sample increasing from 3, 4 to 5 and 6 mm. No chemical reaction occurs at the interface between mold flux and steel substrate via the thermodynamic calculation and microstructure analyses. Furthermore, the line tension of flux droplet/stainless steel/Ar‐5%H2 system ranges from 160.55 to 125.19 mN m−1 at the temperature range of 1473–1573 K. It is due to the positive line tension (line energy) which decreases the wettability of flux droplet on steel substrate and results in an increase of contact angle when the droplet size reduces. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose here is to explore the unsteadiness characteristics in magnetized flow of Reiner–Rivlin nanofluid. Energy and concentration expressions are modeled by utilizing Buongiorno model for nanoscale particles. Additionally, Joule heating and activation energy are also deliberated. Design/methodology/approach: The bvp4c solver in MATLAB is employed for graphical and numerical outcomes. Findings: A similar trend of temperature field is seen against thermophoresis and Brownian movement parameters. Thermal transport rate decreases via Prandtl number. Augmentation in mass transport rate is noted through unsteadiness parameter. Originality/value: To the best of author's knowledge, no such consideration has been given in the literature yet. [ABSTRACT FROM AUTHOR]

This study comprehensively examines magnetohydrodynamic heat transport characteristics within a thin nanofluid film on a stretchable sheet embedded in a composite medium. By considering factors such as the unsteady nature of sheet velocity, Brownian motion, thermophoresis, thermally radiative heat, irregular heat generation/sink, chemical reactions, and dissipation due to viscous fluid, the research provides valuable insights into the variations in fluid velocity, temperature, and nanoparticles concentration. The computational solution utilizes the efficient numerical method that enables accurate predictions of system behavior under varying conditions. Notable findings include the influence of Schmidt numbers on nanoparticle concentration distribution, the opposing impact of thermophoresis parameter values, and the influence of Brownian motion and heat source/sink on temperature profiles in thin nanofluid film. Also, nanoliquid film thickness is reduced by enhancing the porous parameter values and Hartmann number values. The nanoliquid film becomes thinner when the space‐dependent heat source/sink parameter is considered compared to the temperature‐dependent heat source/sink coefficient. In space‐dependent and temperature‐dependent cases, the increase in these parameters leads to a decrease in the temperature gradient. Furthermore, it is observed that higher thermophoresis values correspond to reduced nanoparticle concentration gradient profiles. Also, enhancement in the chemical reaction values leads to an expansion in the solutal boundary region surrounding nanoparticles, and as a consequence, the concentration gradient of nanoparticles is enhanced. This research has significant potential for optimizing heat performance and advancing innovation in industrial and engineering processes. [ABSTRACT FROM AUTHOR]

Convection, that is, mixed magnetohydrodynamics stream of Williamson nanofluid in excess of a nonlinearly stretchable permeable sheet, has been studied using a mathematical model that includes thermal radiation, viscous dissipation, heat source/sink, chemical reaction, and suction are all examples of thermal radiation are all examples of how heat is dissipated. By availing the controlling similarity transformations, suitable similarity transformations partial differential equations are reduced into the solution of a set of ordinary differential equations that are nonlinear using the homotopy analysis method. There is also a clear approach to get series solutions to converge. There was a strong correlation between the current and past outcomes. Graphs and tables are used to illustrate the nature of the flow field beneath various conditions. [ABSTRACT FROM AUTHOR]

The present review article discusses the various sensors for biomarker detection available for multiple diseases with the scope of helping and encouraging researchers to design devices for the effective and early detection of diseases. In general, these sensors are classified into various types based on bio-recognition by detection systems or transducers. However, based on optical transducers, these are further divided into chromogenic, luminogenic, chemiluminescence, and optical fiber. Here in this article, attempts have been made for the analysis of various analytes or biomarkers of various diseases using different polymeric systems under the classification of optical chromogenic transducers. Optical detection of biomarkers in the sample solution is obtained via a biochemical reaction that causes changes in optical properties. Herein, results can be easily analyzed by a color change produced via ligand-analyte interaction, which can be measured to help in the diagnosis of various diseases. There are various types of renal biomarkers, which can be used as an indication of the functioning of the kidney like glucose (GL), uric acid (UA), urea, creatinine (CRN), and albumin (AL). GL is also an important biomarker for diabetes mellitus. For urinary tract infections (UTIs), nitrite is an important biomarker in urine samples. Bilirubin is used as a biomarker for liver damage. Increased chloride concentration in the sweat samples can be used as a biomarker for the disease cystic fibrosis. An elevated cholesterol level inside the body acts as a biomarker for cardiac arrest. Lactate appears to be a powerful predictor of sepsis. This review mainly deals with biochemical reactions for the detection of various biomarkers of diseases. Chemical aspects of the reactions are briefly discussed for their colorimetric evaluation to determine the biomarkers. This article also discusses various polymeric supports available for developing point-of-care testing (POCT) strips. • Sensors for the biomarker detection available for the various diseases. • Optical detection of biomarkers in sample solution is based on changes in optical properties. • Renal biomarkers of kidney are glucose (GL), uric acid (UA), urea, creatinine (CRN), and albumin (AL). • For urinary tract infections (UTIs), nitrite is an important biomarker in urine samples. • Various polymeric supports are available for developing point-of-care testing (POCT) strips. [ABSTRACT FROM AUTHOR]

This paper presents a study on the removal of CO2 gas from gas mixture (CO2/N2) of 14% CO2 using adsorption onto zeolite 13X in a fluidized bed at 298 K and 1 atm pressure. The effects of static bed height (5–25 cm) and rate of flow of the gas mixture (6–14 L/min) on the breakthrough time were studied. The desorption of CO2 was performed by absorbing the adsorbed CO2 molecules using NaOH solution (0.1 M). The absorption process which was accompanied with chemical reaction achieved two objectives. The first was converting CO2 gas into a valuable substance (Na2CO3) which could be used in many industries. The second was the storage of CO2 gas in what was called a chemical carrier which could emit the gas when it was needed. The effect of static bed height (5–25 cm) on the absorption process in the fluidized bed was also studied. For the adsorption process, the results showed that the breakthrough time increased with decreasing the flow rate but with increasing the static bed height. In the desorption process, the total amount of absorbed CO2 molecules was 396 mg, achieving a recovery of 90.8% at 5 cm static bed height. HIGHLIGHTS: Studying the adsorption in a fluidized bed. Using breakthrough curve to estimate the adsorbed amount of CO2. Studying the effects of operational parameters on the breakthrough time. Performing the desorption by absorption process. Recovering the adsorbed CO2 molecules. [ABSTRACT FROM AUTHOR]