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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Liquid–Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl 3 ) Enabled by Machine Learning Interatomic Potentials

Molten salts are promising candidates in numerous clean energy applications, where knowledge of thermophysical properties and vapor pressure across their operating temperature ranges is critical for safe operations. Due to challenges in evaluating these properties using experimental methods, fast and scalable molecular simulations are essential to complement the experimental data. In this study, we developed machine learning interatomic potentials (MLIP) to study the AlCl 3 molten salt across varied thermodynamic conditions (T = 473–613 K and P = 2.7–23.4 bar), which allowed us to predict temperature-surface tension correlations and liquid–vapor phase diagram from direct simulations of two-phase coexistence in this molten salt. Two MLIP architectures, a Kernel-based potential and neural network interatomic potential (NNIP), were considered to benchmark their performance for AlCl 3 molten salt using experimental structure and density values. The NNIP potential employed in two-phase equilibrium simulations yields the critical temperature and critical density of AlCl 3 that are within 10 K (∼3%) and 0.03 g/cm 3 (∼7%) of the reported experimental values. An accurate correlation between temperature and viscosities is obtained as well. In doing so, we report that the inclusion of low-density configurations in their training is critical to more accurately represent the AlCl 3 system across a wide phase-space. The MLIP trained using PBE-D3 functional in the ab initio molecular dynamics (AIMD) simulations (120 atoms) also showed close agreement with experimentally determined molten salt structure comprising Al 2 Cl 6 dimers, as validated using Raman spectra and neutron structure factor. Furthermore, the PBE-D3 as well as its trained MLIP showed better liquid density and temperature correlation for AlCl 3 system when compared to several other density functionals explored in this work. Overall, the demonstrated approach to predict temperature correlations for liquid and vapor densities in this study can be employed to screen nuclear reactors-relevant compositions, helping to mitigate safety concerns.

Ab initio molecular dynamics↗
DOE OSTI2020

Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics

In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system’s specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. In this work, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Coarse-grained molecular dynamics simulation of solvent-dependent cellulose nanofiber interactions

Associations between cellulose are important both in biofuel production and in the use of cellulose for biomaterials. Cellulose nanofibers (CNFs) are sustainable, strong, light-weight alternatives to traditional materials in manufacturing, but are challenging to obtain due to irreversible aggregation in solution during preparative fibrillation. Therefore, it is imperative to understand the underlying factors driving aggregation with a view to designing solvents that can effectively compete with interfiber interactions, hence reducing aggregation. Molecular dynamics (MD) simulation at atomic detail can provide useful information on local interactions. However, the length and timescales accessible are too short to fully capture association processes. Here, we provide a method for accessing the longer length and timescales required using coarse-grained (CG) MD simulations with a MARTINI force field to calculate the interaction behavior of CNFs in three selected solvents: NaOH-urea-water, acetone, and neat water. The CG results are consistent with our prior all-atom MD and with previous experimental results. While acetone is found not to be an effective solvent, urea and ionic moieties in NaOH-urea-water not only solvate the fibrils but also improve the confinement of water molecules around them as shown by the solvent residence times and mean-square displacements. Overall, the presence of urea and ions reduces the likelihood of aggregation in multi-CNF systems relative to neat water irrespective of whether the hydrophobic or hydrophilic CNF surfaces are interacting. In conclusion, the CG method shows clear promise for selecting potential high-performance solvents for experimental prioritization in bioenergy and biomaterials research in a relatively fast manner as well as for understanding the aggregation and rheological behavior of CNF-solvent systems.

aggregation↗
DOE OSTI2024

On the importance of species immiscibility in mixing-layer dynamics at supercritical pressures

The mixing dynamics of injected propellants is a key factor in determining the ignition performance and combustion-instability response of rocket engines, internal combustion engines, and gas turbines. A key source of uncertainty in the prediction of phase-exchange dynamics is the immiscibility of the injected propellants at supercritical pressure conditions, which induces liquid/vapor phase separation and surface-tension dynamics. While experimental observations indicate the presence of liquid/vapor interfacial structures, this interfacial dynamics is typically neglected in numerical analyses. To address this issue, the objective of the present study is to systematically evaluate the importance of species immiscibility on the phase-exchange dynamics of cryogenic LOX/GH2 mixing layers at typical rocket engine injection conditions. This is accomplished by comparing simulations of (i) a recently developed interface-capturing Regularized-Interface Method (RIM) formulation, and (ii) the commonly employed Diffuse-Interface Method (DIM) formulation. Analysis shows that the interfacial dynamics significantly impact the atomization and mixing of the propellants in the near-injector region, which is not captured by the DIM formulation. The findings of this study extend to other immiscible injection systems, such as LOX/kerosene and hydrocarbon-fuel/air, thereby highlighting the importance of resolving species immiscibility in simulating high-pressure combustion engines.

diffused-interface method↗
DOE OSTI2020

Building Durable Multimetallic Electrocatalysts from Intermetallic Seeds

When combined with earth-abundant metals, Pt-based alloy nanoparticles (NPs) can be cost-effective electrocatalysts. However, these NPs can experience leaching of non-noble-metal components under harsh electrocatalytic conditions. In this work, the Skrabalak group has demonstrated a novel NP construct in which Pt-based random alloy surfaces are stabilized against non-noble-metal leaching by their deposition onto intermetallic seeds. These core@shell NPs are highly durable electrocatalysts, with the ability to tune catalytic performance by the core@shell architecture, surface alloy composition, and NP shape. This versatility was demonstrated in a model system in which random alloy (ra-) PtM surfaces were deposited onto ordered intermetallic (i-) PdCu seeds using seed-mediated co-reduction (SMCR). In the initial demonstration, ra-PtCu shells were deposited on i-PdCu seeds, with these core@shell NPs exhibiting higher specific and mass activities for the oxygen reduction reaction (ORR) when compared to similarly sized ra-PtCu NPs. These NPs also showed outstanding durability, maintaining ~85% in specific activity after 5000 cycles. Characterization of the NPs after use revealed minimal loss of Cu. The activity enhancement was attributed to the strained surface that arises from the lattice mismatch between the intermetallic core and random alloy surface. The outstanding durability was attributed to the ordered structure of the intermetallic core. The origin of this durability enhancement was investigated by classical molecular dynamics simulations, where Pt atoms were found to have a lower potential energy when deposited on an intermetallic core than when deposited on a random alloy core. Also, ordering of Cu atoms at the core@shell interface appears to enhance the overall binding between the core and the shell materials. Inspired by this initial demonstration, SMCR has been used to achieve shells of different random alloy compositions, PtM (M = Ni, Co, Cu, or Fe). This advance is significant because ligand effects vary as a function of PtM identity and Pt/M ratio. These features also influence the degree of surface strain imparted from the lattice mismatch between the core and shell materials. Like the initial demonstration, standout features of these core@shell NPs were high durability and resistance to non-noble metal leaching. Moving forward, efforts have been directed toward integrating shape-control to this core@shell NP construct. This integration is motivated by the shape-dependent catalytic performance of NPs derived from the selective expression of specific facets. Considering the initial i-PdCu@ra-PtCu system, NPs with a cubic shape have been achieved by judicious selection of capping ligands during SMCR. Evaluation of these NPs as catalysts for the electrooxidation of formic acid found that the nanocubic shape enhances catalytic performance compared to similar core@shell NPs with a spherical morphology. We envision that SMCR can be applied to other NP systems to achieve highly durable catalysts as the syntheses of monodisperse and shape-controlled intermetallic seeds are advanced. This Account highlights the role of intermetallic cores in providing more durable electrocatalysts. More broadly, the versatility of SMCR is highlighted as a route to integrate architecture, alloy surfaces, and shape within one NP system, and how this achievement is inspiring new high-performance and robust catalysts is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Comparative Studies of the Structural and Transport Properties of Molten Salt FLiNaK Using the Machine-Learned Neural Network and Reparametrized Classical Forcefields

Despite surging interest in molten salt reactors and thermal storage systems, knowledge of the physicochemical properties of molten salts are still inadequate due to demanding experiments that require high temperature, impurity control, and corrosion mitigation. Therefore, the ability to predict these properties for molten salts from first-principles computations is urgently needed. Herein, we developed and compared a machine-learned neural network force field (NNFF) and a reparametrized rigid ion model (RIM) for a prototypical molten salt LiF–NaF–KF (FLiNaK). We found that NNFF was able to reproduce both the structural and transport properties of the molten salt with first-principles accuracy and classical-MD computational efficiency. Furthermore, the correlation between the local atomic structures and the dynamics was identified by comparing with RIMs, suggesting the significance of polarization of anions implicitly embedded in the NNFF. Furthermore, this work demonstrated a computational framework that can facilitate the screening of molten salts with different chemical compositions, impurities, and additives, and at different thermodynamic conditions suitable for the next-generation nuclear reactors and thermal energy storage facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Adatom-Driven Oxygen Intermixing during the Deposition of Oxide Thin Films by Molecular Beam Epitaxy

Thin film deposition from the vapor phase is a complex process involving adatom adsorption, movement, and incorporation into the growing film. While simulations have been able to capture key aspects of these processes to reproduce film morphology, these models typically ignore any subsurface diffusion that occurs. The results of these diffusion and intermixing processes are often observed experimentally, but cannot be explained by invoking bulk lattice diffusion at the deposition temperature. In this work, we present quantitative experimental data that reveals anion and cation intermixing over long length scales during the deposition of epitaxial Fe 2 O 3 and Cr 2 O 3 films and heterostructures by oxygen-plasma-assisted molecular beam epitaxy. We track this diffusion by incorporating well-defined tracer layers containing 18 O and/or 57 Fe, and measure their redistribution on the nanometer scale with atom probe tomography. Molecular dynamics simulations suggest potential intermixing events, which are then examined via nudged elastic band calculations. These reveal that adatoms on the film surface act to “pull up” subsurface O and Fe. Subsequent ring-like rotation mechanisms involving both adatom and subsurface anions then facilitate their mixing. A simple model incorporating these events qualitatively agrees with the experimental intermixing results. In addition to film deposition, these intermixing mechanisms may to be operant during other surface-mediated processes such as heterogeneous catalysis and corrosion.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Origin, nature, and the dynamic behavior of nanoscale vacancy clusters in Ni-rich layered oxide cathodes

Oxygen and transition metal (TM) vacancies in transition metal oxides (TMOs) play an important role in materials functionalities. For TMO cathodes of Li-ion batteries, vacancies can be introduced, either deliberately or inevitably, during materials synthesis or upon electrochemical cycling. Effects of vacancies on the electrochemical properties of cathodes critically depend on the dynamic characteristics of vacancies during the battery cycling. However, a fundamental understanding of such characteristics in the layer structured cathode remains elusive. Here, using scanning transmission electron microscopy (STEM), we reveal a cycling-induced aggregation behavior of oxygen and TM vacancies in a Ni-rich layer structured cathode of secondary particles. We discover that during the initial charging, vacancies aggregate to form visible vacancy-rich nanoregions (vacancy clusters) firstly at the outer layer of the secondary particle, and then the vacancy-cluster populated region extends to the inner part of particle upon fully charged. The spatial distinction of preferential nucleation of vacancy clusters at the outer layer indicates that the vacancy migration and clustering is associated with Li migration flux, which is larger at the outer layer, as all the Li from the inner part has to go through the outer layer. With extended cycling (> 50), these vacancy clusters become immobilized. We further reveal that the generation of these vacancy clusters is correlated to the material-synthesis conditions. Our findings solve a long-standing puzzle on the origin, nature, and behavior of the commonly visible vacancy clusters in the NMC cathode, providing insights on correlation between properties and dynamic behaviors of atomic-scale defects in layered oxide cathodes.

Li-ion batteries, layered oxide cathodes, NMC, cat↗
DOE OSTI2020

Enhanced Binding of SARS-CoV-2 Spike Protein to Receptor by Distal Polybasic Cleavage Sites

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein plays a crucial role in binding the human cell receptor ACE2 that is required for viral entry. Many studies have been conducted to target the structures of RBD–ACE2 binding and to design RBD-targeting vaccines and drugs. Nevertheless, mutations distal from the SARS-CoV-2 RBD also impact its transmissibility and antibody can target non-RBD regions, suggesting the incomplete role of the RBD region in the spike protein–ACE2 binding. Here, in order to elucidate distant binding mechanisms, we analyze complexes of ACE2 with the wild-type spike protein and with key mutants via large-scale all-atom explicit solvent molecular dynamics simulations. We find that though distributed approximately 10 nm away from the RBD, the SARS-CoV-2 polybasic cleavage sites enhance, via electrostatic interactions and hydration, the RBD–ACE2 binding affinity. A negatively charged tetrapeptide (GluGluLeuGlu) is then designed to neutralize the positively charged arginine on the polybasic cleavage sites. We find that the tetrapeptide GluGluLeuGlu binds to one of the three polybasic cleavage sites of the SARS-CoV-2 spike protein lessening by 34% the RBD–ACE2 binding strength. This significant binding energy reduction demonstrates the feasibility to neutralize RBD–ACE2 binding by targeting this specific polybasic cleavage site. Our work enhances understanding of the binding mechanism of SARS-CoV-2 to ACE2, which may aid the design of therapeutics for COVID-19 infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Influence of the Dielectric Constant on the Ionic Current Rectification of Bipolar Nanopores

In this paper, we investigate how the dielectric constant, ϵ, of an electrolyte solvent influences the current rectification characteristics of bipolar nanopores. It is well recognized that bipolar nanopores with two oppositely charged regions rectify current when exposed to an alternating electric potential difference. Here, we consider dilute electrolytes with NaCl only and with a mixture of NaCl and charged nanoparticles. These systems are studied using two levels of description, all-atom explicit water molecular dynamics (MD) simulations and coarse-grained implicit solvent MD simulations. The charge density and electric potential profiles and current-voltage relationship predicted by the implicit solvent simulations with ϵ = 11.3 show good agreement with the predictions from the explicit water simulations. Under nonequilibrium conditions, the predictions of the implicit solvent simulations with a dielectric constant closer to the one of bulk water are significantly different from the predictions obtained with the explicit water model. Further, these findings are closely aligned with experimental data on the dielectric constant of water when confined to nanometric spaces, which suggests that ϵ decreases significantly compared to its value in the bulk. Moreover, the largest electric current rectification is observed in systems containing nanoparticles when ϵ = 78.8. Using enhanced sampling, we have shown that this larger rectification arises from the presence of a significantly deeper minimum in the free energy of the system with a larger ϵ, and when a negative voltage bias is applied. Since implicit solvent models and mean-field continuum theories are often used to design Janus membranes based on bipolar nanopores, this work highlights the importance of properly accounting for the effects of confinement on the dielectric constant of the electrolyte solvent. The results presented here indicate that the dielectric constant in implicit solvent simulations may be used as an adjustable parameter to approximately account for the effects of nanometric confinement on aqueous electrolyte solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

EELS Studies of Cerium Electrolyte Reveal Substantial Solute Concentration Effects in Graphene Liquid Cells

Graphene liquid cell transmission electron microscopy is a powerful technique to visualize nanoscale dynamics and transformations at atomic resolution. However, the solution in liquid cells is known to be affected by radiolysis, and the stochastic formation of graphene liquid cells raises questions about the solution chemistry in individual pockets. In this study, electron energy loss spectroscopy (EELS) was used to evaluate a model encapsulated solution, aqueous CeCl 3 . First, the ratio between the O K-edge and Ce M-edge was used to approximate the concentration of cerium salt in the graphene liquid cell. It was determined that the ratio between oxygen and cerium was orders of magnitude lower than what is expected for a dilute solution, indicating that the encapsulated solution is highly concentrated. To probe how this affects the chemistry within graphene liquid cells, the oxidation of Ce 3+ was measured using time-resolved parallel EELS. Here, it was determined that Ce 3+ oxidizes faster under high electron fluxes, but reaches the same steady-state Ce 4+ concentration regardless of flux. The time-resolved concentration profiles enabled direct comparison to radiolysis models, which indicate rate constants and g-values of certain molecular species are substantially different in the highly concentrated environment. Finally, electron flux-dependent gold nanocrystal etching trajectories showed that gold nanocrystals etch faster at higher electron fluxes, correlating well with the Ce 3+ oxidation kinetics. Understanding the effects of the highly concentrated solution in graphene liquid cells will provide new insight on previous studies and may open up opportunities to systematically study systems in highly concentrated solutions at high resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Visualizing the Three-Dimensional Arrangement of Hydrogen Atoms in Organic Molecules by Coulomb Explosion Imaging

Structure-sensitive methods based on femtosecond light or electron pulses are now making it possible to measure how molecular structures change during light-induced processes. Despite significant progress, high-fidelity imaging of nuclear positions remains a challenge even for relatively small molecular systems and, notably, regarding the positions of hydrogen atoms. As demonstrated in recent work, X-ray-induced Coulomb explosion imaging (CEI) may overcome this obstacle, as its sensitivity does not depend on the mass of the imaged atoms. The photoinduced ring opening of the heterocyclic molecule 2(5 H )-thiophenone has attracted recent interest. Here, in this work, we show that CEI offers a powerful route to imaging the peripheral H atoms in this molecule and thus, more generally, to tracking detailed nuclear motions (e.g., isomerizations) in organic molecules on ultrafast time scales. Specifically, we record momentum-space Coulomb explosion images that report on the three-dimensional positioning of all nuclei within the molecule, for instance, distinguishing H atoms in C–H bonds that lie within or are directed out of the plane defined by the heavy atoms. The prospect of imaging peripheral H atoms to probe photochemical dynamics is explored by coupling ab initio molecular dynamics with classical Coulomb explosion simulations, thereby differentiating potential photoproduct isomers, including those whose structures primarily differ in the position of the hydrogens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Deuteration removes quantum dipolar defects from KDP crystals

Abstract Dielectric properties of the hydrogen-bonded ferroelectric crystal KH 2 PO 4 (KDP) differ significantly from those of KD 2 PO 4 (DKDP). It is well established that deuteration affects the interplay of hydrogen-bond switches and heavy ion displacements that underlie the emergence of macroscopic polarization, but a detailed microscopic model is missing. We show that all-atom path integral molecular dynamics simulations can predict the isotope effects, revealing the microscopic mechanism that differentiates KDP and DKDP. Proton tunneling generates phosphate configurations that do not contribute to the polarization. At low temperatures, these quantum dipolar defects are substantial in KDP but negligible in DKDP. These intrinsic defects explain why KDP has lower spontaneous polarization and transition entropy than DKDP. The prominent role of quantum fluctuations in KDP is related to the unusual strength of the hydrogen bonds and should be equally important in other crystals of the KDP family, which exhibit similar isotope effects.

Yang, Bingjia (ORCID:0000000340749553)↗
DOE OSTI2024

Measurement of coherent vibrational dynamics with X-ray Transient Absorption Spectroscopy simultaneously at the Carbon K- and Chlorine L 2,3 - edges

X-ray Transient Absorption Spectroscopy (XTAS) is a powerful probe for ultrafast molecular dynamics. The evolution of XTAS signal is controlled by the shapes of potential energy surfaces of the associated core-excited states, which are difficult to directly measure. Here, we study the vibrational dynamics of Raman activated CCl 4 with XTAS targeting the C 1s and Cl 2p electrons. The totally symmetric stretching mode leads to concerted elongation or contraction in bond lengths, which in turn induce an experimentally measurable red or blue shift in the X-ray absorption energies associated with inner-shell electron excitations to the valence antibonding levels. The ratios between slopes of different core-excited potential energy surfaces (CEPESs) thereby extracted agree very well with Restricted Open-Shell Kohn-Sham calculations. The other, asymmetric, modes do not measurably contribute to the XTAS signal. The results highlight the ability of XTAS to reveal coherent nuclear dynamics involving < 0.01 Å atomic displacements and also provide direct measurement of forces on CEPESs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

In situ synchrotron pair distribution function analysis to monitor synthetic pathways under electromagnetic excitation

Electromagnetic (EM) fields, specifically microwave radiation (MWR), can significantly influence the synthesis of ceramic oxide materials and promote rapid, low-temperature growth. However, the mechanisms by which EM fields affect the phase formation process are not well understood. A major limitation to increasing this understanding has been the lack of information regarding dynamic changes in local atomic structure during MWR exposure compared to conventional hydrothermal synthesis routes. Here, we utilize in situ synchrotron X-ray pair distribution function (PDF) analysis to monitor MWR-assisted SnO 2 nanoparticle synthesis. A clear impact of the EM field is demonstrated, with MWR inducing changes in nearest neighbor distances and peaks in oxygen atomic displacement that do not occur during synthesis without MWR exposure. The observed local structural disorder serves as a precursor to rapid rutile SnO 2 nanoparticle crystallization, suggesting that EM field-assisted growth is mediated by changes to the oxygen sublattice. These findings further our understanding of the mechanisms underlying MWR-assisted synthesis and represent a step towards utilizing EM fields to engineer tailored atomic structures for a broad range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Defect-free-induced Na + disordering in electrode materials

For reaching high-performance of electrode materials, it is generally believed that understanding the structure evolution and heterogeneous alignment effect is the key. Presently, a very simple and universally applicable self-healing method is investigated to prepare defect-free Prussian blue analogs (PBAs) that reach their theoretical capacity as cathode materials for sodium-ion batteries (SIBs). For direct imaging of the local structure and the dynamic process at the atomic scale, we deliver a fast ion-conductive nickel-based PBA that enables rapid Na + extraction/insertion within 3 minutes and a capacity retention of nearly 100% over 4000 cycles. This guest-ion disordered and quasi-zero-strain nonequilibrium solid–solution reaction mechanism provides an effective guarantee for realizing long-cycle life and high-rate capability electrode materials that operate via reversible two-phase transition reaction. Unconventional materials and mechanisms that enable reversible insertion/extraction of ions in low-cost metal–organic frameworks (MOFs) within minutes have implications for fast-charging devices, grid-scale energy storage applications, material discovery, and tailored modification.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The effect of low temperature on poly(3-methyl- N -vinylcaprolactam)- b -poly( N -vinylpyrrolidone) diblock copolymer nanovesicles assembled from all-aqueous media

Nanosized polymeric vesicles (polymersomes) self-assembled from double hydrophilic copolymers of poly(3-methyl-N-vinylcaprolactam) n -b-poly(N-vinylpyrrolidone) m (PMVC n -b-PVPON m ) using all aqueous media are a promising platform for biomedical applications, because of their superior stability over liposomes in vivo and high loading capacity. Herein, we explored the temperature-sensitive behavior of PMVC 58 -b-PVPON 65 vesicles using transmission electron microscopy (TEM), dynamic light scattering (DLS), atomic force microscopy (AFM), and small-angle neutron scattering (SANS) in response to lowering the solution temperature from 37 to 25, 20, 14 and 4 °C. The copolymer vesicles with an average size of 350 nm at 37 °C were assembled from the diblock copolymer dissolved in aqueous solution at 4 °C. We show that while the polymersome's size gradually decreases upon the temperature decrease from 37 to 4 °C, the average shell thickness increases from 17 nm to 25 nm, respectively. SANS study revealed that the PMVC 58 -b-PVPON 65 vesicle undergoes a gradual structure evolution from a dense-shell vesicle at 37–25 °C to a highly-hydrated shell vesicle at 20–14 °C to molecular chain aggregates at 4 °C. From SANS contrast matching study, this vesicle behavior is found to be driven by the gradual rehydration of PMVC block at 37–14 °C. The shell hydration at 20–14 °C also correlated with the 4.4-fold decrease in the relative fluorescence intensity from vesicle-encapsulated fluorescent dye, indicating ~80% of the dye release within 12 hours after the vesicle exposure to 14 °C. No significant (<5%) dye release was observed for the vesicle solutions at 37–20 °C, indicating excellent cargo retention inside the vesicles. Our study provides new fundamental insights on temperature-sensitive polymer vesicles and demonstrates that the copolymer assembly into polymersomes can be achieved by decreasing a copolymer aqueous solution temperature below 14 °C followed by solution exposure to ≥20 °C. This type of all-aqueous assembly, instead of nanoprecipitation from organic solvents or solvent exchange, can be highly desirable for encapsulating a wide range of biological molecules, including proteins, peptides, and nucleic acids, into stable polymer vesicles without a need for organic solvents for dissolution of the copolymers that are amphiphilic at physiologically relevant temperatures of 20–37 °C.

36 MATERIALS SCIENCE↗