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At least 865 records · Page 48

Analysis of soot formation from aviation fuels in laminar counterflow flames

Combustion emissions from aviation contribute to the formation of condensation trail (contrail) that can lead to the formation of anthropogenic cirrus clouds. Ice particles that form contrails are observed to have a linear correlation with soot particle number density. Synthetic aviation fuels (SAFs) offer a promising route to mitigate the production of soot particles while also increasing energy security. Although studies have focused on combustion and spray behavior, the detailed investigation of soot formation processes for different jet fuels and their impact on models for computational fluid dynamics (CFD) applications is not well understood. Moreover, experimental measurements of soot for canonical flames using Synthetic aviation fuels (SAF) for model validation remain scarce. To address this, we use employed the Lawrence Livermore National Laboratory (LLNL) detailed soot model based on the discrete sectional method. Additionally, we develop two reduced chemical mechanisms for Jet-A and Alcohol-to-Jet (C1) that are suitable for turbulent flame simulations and couple them with the Hybrid Method of Moments (HMOM). The detailed and reduced model frameworks are validated against experimental measurements of soot volume fraction (ƒ ν ) from a counterflow burner experiment previously reported in the literature. Given the good agreement between modeling results and experimental measurements for the (1) spatial distribution of ƒ ν and (2) the non-linear variation of peak ƒ ν with strain rate, we further investigate the modeled sub-processes (nucleation, condensation, surface growth, and oxidation) using the LLNL model to analyze the assumptions in the reduced model framework. Furthermore, the results indicate a significant contribution from resonant radicals to the surface growth of soot particles, which are not accounted for in the current implementation of HMOM and could help reconcile soot predictions by the reduced model with observations.

Counterflow↗

Natural organic matter composition and nanomaterial surface coating determine the nature of platinum nanomaterial-natural organic matter corona

Natural organic matter corona (NOM corona) is an interfacial area between nanomaterials (NMs) and the sur- rounding environment, which gives rise to NMs' unique surface identity. While the importance of the formation of natural organic matter (NOM) corona on engineered nanomaterials (NMs) to NM behavior, fate, and toxicity has been well-established, the understanding of how NOM molecular properties affect NOM corona composition remains elusive due to the complexity and heterogeneity of NOM. This is further complicated by the variation of NOMs from different origins. Here we use eight NOM isolates of different molecular composition and ultrahigh resolution Fourier-transform ion cyclotron resonance-mass spectrometry (ESI-FT-ICR-MS) to determine the mol- ecular composition of platinum NM-NOM corona as a function of NOM composition and NM surface coating. We observed that the composition of PtNM-NOM corona varied with the composition of the original NOM. The per- centage of NOM formulas that formed PVP-PtNM-NOM corona was higher than those formed citrate-PtNM-NOM corona, due to increased sorption of NOM formulas, in particular condensed hydrocarbons, to the PVP coating. The relative abundance of heteroatom formulas (CHON, CHOS, and CHOP) was higher in the PVP-PtNM-NOM corona than in citrate-PtNM-corona which was in turn higher than those in the original NOM isolate, indicating preferential partitioning of heteroatom-rich molecules to NM surfaces. The relative abundance of CHO, CHON, CHOS, CHOP and condensed hydrocarbons in PtNM-NOM corona increased with their increase in NOM isolates. Furthermore, PtNM-NOM corona is rich with compounds with high molecular weight. This study demonstrates that the composition and properties of PtNM-NOM corona depend on NOM molecular properties and PtNM sur- face coating. The results here provide evidence of molecular interactions between NOM and NMs, which are crit- ical to understanding NM colloidal properties (e.g., surface charge and stability), interaction forces (e.g., van der Waals and hydrphobic), environmental behaviors (e.g., aggregation, disso.

Baalousha, Mohammed↗

Organic amendments change soil organic C structure and microbial community but not total organic matter on sub-decadal scales

Organic C has many benefits for soil, but it is depleted by tillage and crop harvest, and especially so for biofuel crops. Accordingly, strategies such as partially retaining stover or planting a cover crop can help ameliorate the negative effect of C removal. We used a long-term field experiment to study the impacts of stover retention and planting cover crop on soil organic matter (SOM), its extractable components and the soil microbial community. SOM chemical composition characterization was determined by electrospray ionization (ESI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) in sequential water, methanol (MeOH), and chloroform (CHCl3) extracts. The characteristics of the soil bacterial community were measured by phospholipid fatty acid (PLFA), real-time quantitative PCR, and 16S rRNA gene sequence. The variations in total SOM content, total microbial biomass, and bacterial population were slight among treatments, but SOM chemical compounds, arbuscular mycorrhizal fungi (AMF) biomass, and bacterial structure changed significantly, and especially so in the coupled application of stover retention and cover crop. Specifically, stover retention enriched more lignin-like compounds in soil, whereas cover crop enriched more condensed hydrocarbons, and had more compounds with an aromaticity index (AI) >0.5. The bacterial community was not altered by the cover crop, but the corn stover retention increased the relative abundances of Myxococcales (Deltaproteobacteria) and decreased that of Actinobacteria. Redundancy analysis (RDA) further unveiled that the bacterial community in the stover treatments had significantly positive association with CHCl3-extracted chemical classes, i.e. unsaturated hydrocarbon and lipid with the coupled application (stover and cover crop), and lignin and protein with the single corn stover treatment. Taken together, our study shows how different C addition practices influence the molecular composition of SOM and the structure of soil microbial communities.

Xu, Jiangbin↗

Computing the shape gradient of stellarator coil complexity with respect to the plasma boundary

Coil complexity is a critical consideration in stellarator design. The traditional two-step optimization approach, in which the plasma boundary is optimized for physics properties and the coils are subsequently optimized to be consistent with this boundary, can result in plasma shapes which cannot be produced with sufficiently simple coils. To address this challenge, we propose a method to incorporate considerations of coil complexity in the optimization of the plasma boundary. Coil complexity metrics are computed from the current potential solution obtained with the REGCOIL code (Landreman, Nucl. Fusion , vol. 57, 2017, 046003). While such metrics have previously been included in derivative-free fixed-boundary optimization (Drevlak et al. , Nucl. Fusion , vol. 59, 2018, 016010), we compute the local sensitivity of these metrics with respect to perturbations of the plasma boundary using the shape gradient (Landreman & Paul, Nucl. Fusion , vol. 58, 2018, 076023). We extend REGCOIL to compute derivatives of these metrics with respect to parameters describing the plasma boundary. In keeping with previous research on winding surface optimization (Paul et al. , Nucl. Fusion , vol. 58, 2018, 076015), the shape derivatives are computed with a discrete adjoint method. In contrast with the previous work, derivatives are computed with respect to the plasma surface parameters rather than the winding surface parameters. To further reduce the resolution required to compute the shape gradient, we present a more efficient representation of the plasma surface which uses a single Fourier series to describe the radial distance from a coordinate axis and a spectrally condensed poloidal angle. This representation is advantageous over the standard cylindrical representation used in the VMEC code (Hirshman & Whitson, Phys. Fluids , vol. 26, 1983, pp. 3553–3568), as it provides a uniquely defined poloidal angle, eliminating a null space in the optimization of the plasma surface. In comparison with previous spectral condensation methods (Hirshman & Breslau, Phys. Plasmas , vol. 5, 1998, p. 2664), the modified poloidal angle is obtained algebraically rather than through the solution of a nonlinear optimization problem. The resulting shape gradient highlights features of the plasma boundary that are consistent with simple coils and can be used to couple coil and fixed-boundary optimization.

Physics↗

Aerosol Optical Tweezers Elucidate the Chemistry, Acidity, Phase Separations, and Morphology of Atmospheric Microdroplets

Aerosol particles represent unique chemical environments because of their high surface area-to-volume ratio that promotes the effects of interfacial chemistry in confined environments. Properties such as viscosity, diffusivity, water content, pH, and morphology—following liquid–liquid phase separation—can strongly alter how a particle interacts with condensable vapors and reactive trace gases, thus modifying its continual evolution and environmental effects. Our understanding of this chemical evolution of atmospheric particulate matter and its environmental impacts is largely limited by our ability to directly observe how these critical particle properties respond to the addition or reactive uptake of new chemical components. Aerosol optical tweezers (AOT) stably trap particles in focused laser beams, providing positional control and the retrieval of many of these critical properties required to understand and predict the chemistry of aerosolized microdroplets. The analytical power of the AOT stems from the retrieval of the cavity-enhanced Raman spectrum induced by the trapping laser. Analysis of the whispering gallery modes (WGMs) that resonate as a standing wave around the droplet’s interface, provide high accuracy measurements of the droplet’s size, refractive index (and thus a measurement of composition), and can distinguish between core–shell, partially engulfed, and homogeneous morphologies. In this study, we have advanced the ability to determine the properties of the core and shell phases in biphasic droplets, including obtaining high-accuracy pH measurements. These capabilities were applied to perform AOT physical chemistry experiments on authentic secondary organic aerosol (SOA) produced directly in the AOT chamber by ozonolysis of terpene vapors. The propensity of the SOA to phase separate as a shell from a wide range of nonpolar to polar core phases was observed, along with the discovery of a stable emulsified state of SOA particles in an aqueous salt droplet. Micron-thick SOA shells did not impede the gain or loss of water or squalane from the core to the surrounding air, indicating no significant diffusional limitations to condensational growth or partitioning even under dry conditions. These experiments formed the foundation of a new framework that predicts how the phase-separated morphology of complex aerosols containing organic carbon evolves during continual atmospheric oxidation processes. Increases in oxidation state will quickly drive conversion from a partially engulfed to core–shell morphology that has dramatically different chemical reactivity since the core phase is completely concealed by the shell. The recent advances in the experimental capabilities of the AOT technique such as presented here enable novel experimental methodologies that provide insights into the chemistry and multidimensional properties of aerosol microdroplets, and how these coevolve and respond to continual chemical reactions.

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Implementation and Validation of Constrained Density Functional Theory Forces in the CP2K Package

Constrained density functional theory (CDFT) is a powerful tool for the prediction of electron transfer parameters in condensed phase simulations at a reasonable computational cost. In this work we present an extension to CDFT in the popular mixed Gaussian/plane wave electronic structure package CP2K, implementing the additional force terms arising from a constraint based on Hirshfeld charge partitioning. This improves upon the existing Becke partitioning scheme, which is prone to give unphysical atomic charges. We verify this implementation for a variety of systems: electron transfer in (H 2 O) 2 + in vacuum, electron tunnelling between oxygen vacancy centers in solid MgO, and electron self-exchange in aqueous Ru 2+ -Ru 3+ . We find good agreement with previous plane-wave CDFT results for the same systems, but at a significantly lower computational cost, and we discuss the general reliability of condensed phase CDFT calculations.

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Extracting Inelastic Scattering Cross Sections for Finite and Aperiodic Materials from Electronic Dynamics Simulations

Explicit time-dependent electronic structure theory methods are increasingly prevalent in the areas of condensed matter physics and quantum chemistry, with the broad-band optical absorptivity of molecular and small condensed-phase systems nowadays routinely studied with such approaches. Here, in this paper, it is demonstrated that electronic dynamics simulations can similarly be employed to study cross sections for the scattering-induced electronic excitations probed in nonresonant inelastic X-ray scattering and momentum-resolved electron energy loss spectroscopies. A method is put forth for evaluating the electronic dynamic structure factor, which involves the application of a momentum boost-type perturbation and transformation of the resulting reciprocal space density fluctuations into the frequency domain. Good agreement is first demonstrated between the dynamic structure factor extracted from these electronic dynamics simulations and the corresponding transition matrix elements from linear response theory. The method is then applied to some extended (quasi)one-dimensional systems, for which the wave vector becomes a good quantum number in the thermodynamic limit. Finally, the dispersion of many-body excitations in a series of hydrogen-terminated graphene flakes (and twisted bilayers thereof) is investigated to highlight the utility of the presented approach for capturing morphology-dependent effects in the inelastic scattering cross sections of nanostructured and/or noncrystalline materials.

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Charge Transport in Solvated Donor–Acceptor Functionalized Peptoids: Molecular Dynamics and Rate Theory

Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.

Charge transfer↗

The CP-PAW Code Package for First-Principles Calculations from a User’s Perspective

CP-PAW is a combined electronic structure and ab initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as solids, liquids, and molecular systems. As the name suggests, the CP-PAW code unifies the all-electron projector augmented-wave (PAW) method with the Car–Parrinello (CP) approach to determine not only the electronic and nuclear ground states of condensed matter but also to study their properties and dynamics. In addition to briefly outlining the underlying theory, the focus will be on the unique aspects of CP-PAW and how to correctly employ them as a user. How to install CP-PAW using the new build system will also be briefly mentioned.

Blöchl, Peter E [Institute for Theoretical Physic↗

Axial H-Bonding Solvent Controls Inhomogeneous Spectral Broadening, While Peripheral H-Bonding Solvent Controls Vibronic Broadening: Cresyl Violet in Methanol

The dynamics of the nuclei of both a chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore–solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore–solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both force field and ab initio molecular dynamics trajectories along with the inclusion of only certain solvent molecules in the excited-state calculations, we determine that the methanol molecules axial to the chromophore are responsible for the majority of inhomogeneous broadening, with a single methanol molecule that forms an axial hydrogen bond dominating the response. Furthermore, the strong peripheral hydrogen bonds do not contribute to spectral broadening, as they are very stable throughout the dynamics and do not lead to increased energy-gap fluctuations. We also find that treating the strong peripheral hydrogen bonds as molecular mechanical point charges during the molecular dynamics simulation underestimates the vibronic coupling. Including these peripheral hydrogen bonding methanol molecules in the quantum-mechanical region in a geometry optimization increases the vibronic coupling, suggesting that a more advanced treatment of these strongly interacting solvent molecules during the molecular dynamics trajectory may be necessary to capture the full vibronic spectral broadening.

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Influence of Electronic Polarization on the Spectral Density

Accurate spectral densities are necessary for computing realistic exciton dynamics and nonlinear optical spectra of chromophores in condensed-phase environments, including multichromophore pigment–protein systems. However, due to the significant computational cost of computing spectral densities from first principles, requiring many thousands of excited-state calculations, most simulations of realistic systems rely on treating the environment as fixed-point charges. In this work, using a number of representative systems ranging from solvated chromophores to the photoactive yellow protein (PYP), we demonstrate that the quantum mechanical (QM) electronic polarization of the environment is key to obtaining accurate spectral densities and line shapes within the cumulant framework. We show that the QM environment can enhance or depress the coupling of fast chromophore degrees of freedom to the energy gap, altering the electronic–vibrational coupling and the resulting vibronic progressions in the absorption spectrum. In analyzing the physical origin of peaks in the spectral density, we identify vibrational modes that couple the electron and the hole as being particularly sensitive to the QM screening of the environment. For PYP, we reveal the need for careful determination of the appropriate QM region to obtain reliable spectral densities. Our findings suggest that the QM polarization of the environment can be crucial not just for excitation energies but also for electronic–vibrational coupling in complex systems with implications for the correct modeling of linear and nonlinear optical spectroscopy in the condensed phase as well as energy transfer in pigment–protein complexes.

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Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations

Intermetallic nanoparticles are promising catalysts in hydrogenation and fuel cell technologies. Much is known about the ability of intermetallic nanoparticles to selectively reduce nitro vs alkene, alcohol, or halide functional groups; less is known about their selectivity toward aniline vs azo or azoxy condensation products that result from the reduction of a nitro group alone. Because azo(xy)arenes bear promise as dyes, chemical stabilizers, and building blocks to functional materials but can be difficult to isolate, developing high surface area nanoparticle catalysts that display azo(xy) selectivity is desirable. To address this question, we studied a family of nanocrystalline group 10 metal (Pd, Pt)- and group 14 metal (Ge, Sn, Pb)-containing intermetallics-Pd 2 Ge, Pd 2 Sn, Pd 3 Sn 2 , Pd 3 Pb, and PtSn-in the catalytic reduction of nitroarenes. In contrast to monometallic Au, Pt, and Pd nanoparticles and "random" PdxSn1 – x nanoalloys, which are selective for aniline, nanoparticles of atomically precise intermetallic Pd 2 Ge, Pd 2 Sn, Pd 3 Sn 2 , and PtSn prefer an indirect condensation pathway and have a high selectivity for the azo(xy) products. The only exception is Pd 3 Pb, the most active among the intermetallic nanoparticles studied here, which is instead selective for aniline. Employing a novel application of molecular dynamics-based on machine learned potentials within a DeePMD framework-to heterogeneous catalysis, we are able to identify key reaction species on the different types of catalysts employed, furthering our understanding of the unique selectivity of these materials. By demonstrating how intermetallic nanoparticles can be as active yet more selective than other more traditional catalysts, this work provides new physical insights and opens new opportunities in the use of these materials in other important chemical transformations and applications.

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Ex Machina Determination of Structural Correlation Functions

Determining the structural properties of condensed-phase systems is a fundamental problem in theoretical statistical mechanics. In this study, we present a machine learning method that is able to predict structural correlation functions with significantly improved accuracy in comparison with traditional approaches. The usefulness of this ex machina (from the machine) approach is illustrated by predicting the radial distribution functions of two paradigmatic condensed-phase systems, a Lennard-Jones fluid and a hard-sphere fluid, and then comparing those results to the results obtained using both integral equation methods and empirically motivated analytical functions. We find that application of the developed ex machina method typically decreases the predictive error by more than an order of magnitude in comparison with traditional theoretical methods.

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Nuclear–Electronic Orbital Quantum Mechanical/Molecular Mechanical Real-Time Dynamics

Simulating the nuclear–electronic quantum dynamics of large-scale molecular systems in the condensed phase is key for studying biologically and chemically important processes such as proton transfer and proton-coupled electron transfer reactions. Herein, the real-time nuclear–electronic orbital time-dependent density functional theory (RT-NEO-TDDFT) approach is combined with a hybrid quantum mechanical/molecular mechanical (QM/MM) strategy to enable the accurate description of coupled nuclear–electronic quantum dynamics in the presence of heterogeneous environments such as solvent or proteins. The densities of the electrons and quantum protons are propagated in real time, while the other nuclei are propagated classically on the instantaneous electron–proton vibronic surface. This approach is applied to phenol bound to lysozyme, intramolecular proton transfer in malonaldehyde, and nonequilibrium excited-state intramolecular proton transfer in o-hydroxybenzaldehyde. Furthermore, these examples illustrate that the RT-NEO-TDDFT framework, coupled with an atomistic representation of the environment, allows the simulation of condensed-phase systems that exhibit significant nuclear quantum effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accelerated Zymonic Acid Formation from Pyruvic Acid at the Interface of Aqueous Nanodroplets

To explore the role of the liquid interface in mediating reactivity in small compartments, the formation kinetics of zymonic acid (ZA) is measured in submicron aerosols (average radius = 240 nm) using mass spectrometry. The formation of ZA, from a condensation reaction of two pyruvic acid (PA) molecules, proceeds over days in bulk solutions, while in submicron aerosols, it occurs in minutes. The experimental results are replicated in a kinetic model using an apparent interfacial reaction rate coefficient of krxn = (0.9 ± 0.2) × 10-3 M-1 s-1. The simulation reveals that surface activity of PA coupled with an enhanced interfacial reaction rate drives accelerated ZA formation in aerosols. Experimental and simulated results provide compelling evidence that the condensation reaction of PA occurs exclusively at the aerosol interface with a reaction rate coefficient that is enhanced by 4 orders of magnitude (∼104) relative to what is estimated for macroscale solutions.

Kim, Pyeongeun↗

Counterions under a Surface-Adsorbed Cationic Surfactant Monolayer: Structure and Thermodynamics

The surface adsorption of ionic surfactants is fundamental for many widespread phenomena in life sciences and for a wide range of technological applications. However, direct atomic-resolution structural experimental studies of noncrystalline surface-adsorbed films are scarce. Thus, even the most central physical aspects of these films, such as their charge density, remain uncertain. Consequently, theoretical models based on contradicting assumptions as for the surface films' ionization are widely used for the description and prediction of surface thermodynamics. We employ X-ray reflectivity to obtain the angstrom Ångström-scale surface-normal structure of surface-adsorbed films of the cationic surfactant cetyltrimethylammonium bromide (CTAB) in aqueous solutions at several different temperatures and concentrations. In conjunction with published neutron reflectivity data, we determine the surface-normal charge distribution due to the dissociated surfactants' headgroups. The distribution appears to be inconsistent with the Gouy-Chapman model yet consistent with a compact Stern layer model of condensed counterions. Here, the experimental surfactant adsorption thermodynamics conforms well to classical, Langmuir and Kralchevsky, adsorption models. Furthermore, the Kralchevsky model correctly reproduces the observed condensation of counterions, allowing the values of the adsorption parameters to be resolved, based on the combination of the present data and the published surface tension measurements.

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Toward Efficient Entropic Recycling by Mastering Ring–Chain Kinetics

Traditional chemical recycling approaches for condensation polymers suffer compounding energy losses and CO 2 emissions across multiple polymerization and depolymerization cycles. Entropic recycling can address these energy losses by entrapping free energy within the deconstruction products. Entropic recycling involves depolymerization to macrocyclic monomers, but such processes have not been feasible due to the high dilutions typically required to generate macrocyclic compounds. Here, we leverage selective catalysis to allow entropic recycling at concentrations 20–2000× higher than typical for macrocyclization reactions. We find that Ru-based olefin metathesis catalysts containing bulky iodine ligands significantly bias the ring–chain kinetic product distribution during ring-closing metathesis (RCM) toward the formation of oligomeric cycloalkenes. Further improvements in reaction concentration and macrocycle yield are obtained by using high catalyst loadings and by predisposing the alkene substrates to undergo favorable macrocyclization. These RCM optimizations translate effectively to cyclodepolymerization (CDP) of an olefin-containing polymer, with RCM and CDP affording similar macrocycle product distributions under identical reaction conditions. Macrocycle polymerization by entropy-driven ring-opening metathesis provides much higher molecular weight polymers than condensation polymerization of linear analogues, reducing the time to achieve high molecular weight from hours to minutes and enabling polymerization at room temperature. Finally, our findings re-emphasize the importance of energy consumption during a polymer’s lifecycle and provide a framework for the design of efficient entropic recycling systems.

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