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At least 1,495 records · Page 83

Cyclic Topology Enhancing Structural Ordering and Stability of Comb-Shaped Polypeptoid Thin Films against Melt-Induced Dewetting

We investigated the effect of cyclic chain topology on the molecular ordering and thermal stability of comb-shaped polypeptoid thin films on silicon (Si) substrates. Cyclic and linear poly(N-decylglycine) (PNDG) bearing long n-decyl side chains were synthesized by ring-opening polymerization of N-decylglycine-derived N-carboxyanhydrides. When the spin-coated thin films were subjected to thermal annealing at temperatures above the melting temperature (T > T m ), the cyclic PNDG films exhibited significantly enhanced stability against melt-induced dewetting than the linear counterparts (l-PNDG). When recrystallized at temperatures below the crystallization temperature (T < T c ), the homogeneous c-PNDG films exhibit enhanced crystalline ordering relative to the macroscopically dewetted l-PNDG films. Both cyclic and linear PNDG molecules adopt cis-amide conformations in the crystalline film, which transition into trans-amide conformations upon melting. A top-down solvent leaching treatment of both l/c-PNDG films revealed the formation of an irreversibly physisorbed monolayer with similar thickness (ca. 3 nm) on the Si substrate. The physisorbed monolayers are more disordered relative to the respective thicker crystalline films for both cyclic and linear PNDGs. Upon heating above T m , the adsorbed c-PNDG chains adopt trans-amide backbone conformation identical with the free c-PNDG molecules in the molten film. By contrast, the backbone conformations of l-PNDG chains in the adsorbed layers are notably different from those of the free chains in the molten film. We postulate that the conformational disparity between the chains in the physically adsorbed layers versus the free chains in the molten film is an important factor to account for the difference in the thermal stability of PNDG thin films. These findings highlight the use of cyclic chain topology to suppress the melt-induced dewetting in polymer thin films.

36 MATERIALS SCIENCE↗

Structure, Dynamics, and Hydrogen Transport in Amorphous Polymers: An Analysis of the Interplay between Free Volume Element Distribution and Local Segmental Dynamics from Molecular Dynamics Simulations

Polymers are attractive membrane materials owing to their mechanical robustness and relatively inexpensive fabrication. An important indicator of membrane performance are free volume elements (FVE): microporous void spaces created by the inefficient packing of bulky groups along the polymer chain. FVEs tend to degrade over time, as polymer chains reorganize irreversibly. While it is widely accepted that polymer flexibility has an impact on membrane transport properties, the molecular nature of this impact is still not well understood. By the establishment of a correlation between local chain dynamics and the distribution of free volume elements (FVEs), penetrant transport can be regulated more efficiently in amorphous polymer membranes. In this work, we implement all-atom molecular dynamics (MD) simulations to explore the relationship between chain dynamics and free volume in three polymers with different levels of backbone flexibility: polymethylpentene (PMP), polystyrene (PS), and HAB-6FDA thermally rearranged polymer (TRP). We construct these polymers at different temperatures and examine how temperature impacts the FVE distribution and segmental mobility. Our analysis shows that chain segments near FVEs have higher mobility compared with the atoms in the bulk; the extent of this difference increases with chain flexibility. Increasing the chain flexibility by increasing the temperature results in a broader FVE distribution. Rigid polymers such as TRP show the most robust FVE distribution and are not significantly affected by the temperature change. To capture penetrant diffusion through the polymer matrix, hydrogen is inserted and the diffusion is measured at different temperatures; hydrogen mobility is influenced by the FVE structure and overall mobility of polymer chains. Lastly, at low temperatures, hydrogen mobility is influenced by void distribution, while at high temperatures, polymer dynamics dictate hydrogen transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallization of Bottlebrush Statistical Copolymers of Polystyrene and Poly(ethylene oxide)

Here, bottlebrush statistical copolymers (BSCPs) with poly(ethylene oxide) (PEO) and polystyrene (PS) side chains grafted to a polynorbornene (PNB) backbone were synthesized by ring-opening metathesis polymerization (ROMP). The impact of the glassy PS side chains on the crystallization of the PEO side chains as a function of the backbone length, grafting densities, and fraction of the PS and PEO side chains is described. The bottlebrush architecture, where the side chains are anchored to the backbone, inherently constrains the mobility of PEO. Compared with the bulk crystallization temperature of PEO, the higher glass transition temperature of PS places further constraints on PEO crystallization. The limited mobility of PEO leads to cold crystallization behavior during heating. Reduced grafting densities, in turn, reduce side-chain crowding, leading to less extended pendant structures. The degree of crystallinity of PEO was found to decrease at lower grafting densities to a point where crystallization was not observed. The average distance between bottlebrush backbones increased linearly with the backbone length, suggesting that the backbone forms a distinct mesodomain. For BSCPs with asymmetric volume fractions of PS and PEO side chains, the degree of crystallinity of PEO increases with a change from cold crystallization to normal nucleation and growth during cooling, as a result of reduced constraints on PEO mobility by the glassy PS side chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Short Range Order in Disordered Spinel and the Impact on Cation Vacancy Transport

Spinels are important complex oxides for use in radiation damage environments and resulting from the corrosion of steels. It is known that, in these environments, normal spinels exist with some concentration of antisite cation pairs known as inversion. In this work we show that even in highly disordered states characterized by high levels of inversion, spinel still shows some short range order (SRO) that manifests itself in antisite chains. The propensity to form these antisite chains is confirmed through Monte Carlo simulations which find that the length of chains which can form depend on the spinel chemistry. We also consider the effect of antisite chains on the diffusivity of cation vacancies and find the effect strongly depends on the spinel chemistry. At the extremes, chains in FeCr2O4 significantly increase vacancy transport but in MgAl2O4 chains have the inverse effect of drastically reducing vacancy mobility. The explanation of these dramatically different effects results from the assessment of the thermodynamic stability of the antisite chains and contrasting attractive/repulsive interactions of vacancies with the chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2023 Critical Materials Strategy

The global effort to curb carbon emissions is accelerating demand for clean energy technologies and the materials they rely on. Demand for these materials will only continue to grow, especially as some nations aim to achieve net zero emissions by 2050. While some major materials like steel, copper, and aluminum are already powering the fossil fuel economy, others are more minor materials with potential supply risks. These risks could jeopardize the ability to reduce greenhouse gas emissions within the desirable timeframe to avoid significant climate change. In some cases, it may be necessary to take action to improve the resilience of material supply chains and mitigate supply risks. Understanding the importance of individual materials to clean energy and the supply risks associated with them is necessary to identify which materials may serve as potential roadblocks to a clean energy future. The U.S. Department of Energy (DOE) issued a series of 13 supply chain deep dive assessment reports on various energy technologies in 2022 in response to President Biden’s Executive Order on America’s Supply Chains (E.O. 14017). These reports emphasized that supply chain bottlenecks can occur at any stage of the value chain from mining and refining to component and even sub-system manufacturing. The bottlenecks are a combination of factors such as material availability, equipment availability, work force availability and quality, logistics, regulatory framework, and market conditions. These bottlenecks were worsened during the global Covid-19 pandemic. Its lingering impacts have hindered capacity expansion for material supply chains and prevented product lead-time recovery. One approach to reduce supply chain risks for the United States is to have a strong domestic manufacturing sector with a diverse set of producers. Boosting responsible domestic production would require leveraging the latest science not only in material extraction but also in developing substitutes, recycling, reuse, and remanufacturing. This report is an updated analysis of previous Critical Materials Strategy (CMS) reports published by the DOE in 2010, 2011, and 2019 based on national and global priorities, technology advancement, and technology adoption trends. Like the CMS reports, this analysis presents the results of a formal material criticality assessment to identify which materials are critical to the continued deployment of clean energy technologies globally. The analysis in this report leveraged the DOE supply chain deep dive assessments to develop the initial list of materials to evaluate. This DOE Critical Materials Assessment (CMA) is conducted independently of criticality assessments performed by other U.S. government agencies, such as that conducted by the U.S. Geological Survey (USGS). This analysis complements the USGS critical minerals determination in three aspects. First, the DOE assessment is performed from a global perspective, while the USGS analysis focusses on the importance of minerals to the U.S. economy. Second, this report focuses on the importance of materials to clean energy technologies, rather than to the economy in general. Lastly, this study is forward looking to 2035 based on clean energy deployment scenarios, whereas the USGS assessment is retrospective. Materials evaluated in this report that do not appear in the USGS Critical Minerals List include copper, uranium, electrical steel, and SiC. A draft version of this report received ~80 public comments related to supporting data and methodological improvement. Those comments have been incorporated as much as possible where appropriate. Highlights of findings from this 2023 CMA include: Rare earth materials (neodymium, praseodymium, dysprosium, and terbium) used in magnets in electric vehicle (EV) motors and wind turbine generators continue to be critical. While dysprosium (Dy) and terbium (Tb) are both heavy rare earth elements that serve the same function in magnets, the criticality of Tb is slightly lower than that for Dy in the short term due to the widespread use of Dy in high-grade magnets and Tb’s present role as a substitute. Similarly, praseodymium (Pr) is critical in the medium term but only near critical in the short term because it is more substitutable in magnets than neodymium (Nd); Materials used in batteries for EVs and stationary storage are now considered to be critical. While cobalt (Co) was found to be critical in this and previous reports, lithium (Li) becomes critical in the medium term due to its broader use in various battery chemistries and the rampant growth of the EV industry. Natural graphite is a new addition in this assessment and is also found to be critical; Platinum group metals used in hydrogen electrolyzers, such as platinum (Pr) and iridium (Ir), are critical due to an increased focus on hydrogen technologies to achieve net zero carbon emissions, while those used in catalytic converters, such as rhodium (Rh) and palladium (Pd), were screened out due to the decreased importance of catalytic converters in the medium term; Gallium (Ga) continues to be critical due to its use in light-emitting diodes (LEDs). In addition, the use of Ga has increased in magnet manufacturing and in semiconductor in forms such as gallium arsenide (GaAs) or gallium nitride (GaN); Major materials like Aluminum (Al), copper (Cu), nickel (Ni), and silicon (Si) move from noncritical in the short term to near critical in the medium term due to their importance in electrification; Electrical steel is near critical due to its use in transformers for the grid and electric motors in EVs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Next-Generation Reverse Logistics Networks of Photovoltaic Recycling: Perspectives and Challenges

With the growing adoption of solar energy as a key component of the global energy transition and its new industrial policy (the Inflation Reduction Act and others), the United States is witnessing a significant increase in solar investments. This surge in installations and domestic and reshored manufacturing of solar photovoltaic (PV) panels brings with it a pressing issue: the proper management of end-of-life (EoL) PV panels. As these panels are decommissioned, either due to reaching the end of their lifespans or due to breakage across the various stages of the forward supply chain, it becomes crucial to establish efficient reverse supply chain logistics systems to address the challenges associated with their disposal, while also unlocking the value of the inherent materials that are of critical value for other forward supply chains. This perspective article examines the challenges regarding EoL PV panels and relevant reverse supply chain and logistics networks, and proposes future research directions based on the gaps observed among academic research, industry, and policy-making challenges. We identify the main bottlenecks and hurdles including, among others, the lack of supportive regulations and absence of structured, optimized recycling infrastructure. To this end, it is proposed that the key to achieving a sustainable reverse supply chain network for solar PV panels lies in relentless end-to-end supply chain cost optimization efforts supported by enabling policies. Moreover, it is proposed that designing systematic decision-making modeling frameworks is vital for examining different possibilities and scenarios for state, region or nation-wide optimization of solar PV reverse supply chain networks. Indicative to this effect, we discuss the development of a Resource-Task-Network (RTN)-based model and demonstrate its application and benefits through a case study. We wrap up with conclusions and future research directions.

circular economy↗

Genetic and metabolic drivers of membrane remodeling in Clostridium thermocellum under alcohol stress

Clostridium thermocellum is a leading candidate for consolidated bioprocessing of lignocellulosic biomass into biofuels due to its native cellulolytic capabilities. Beyond ethanol, C. thermocellum is being developed as a platform for producing higher-chain alcohols such as isobutanol and n-butanol. However, its physiological adaptations to alcohol stress remain poorly understood. Here, we investigate how C. thermocellum remodels its membrane lipid composition in response to exogenous ethanol, n-butanol, isobutanol, and butyrate. Exposure to linear alcohols such as n-butanol or to organic acids like butyrate increased the proportion of straight-chain fatty acids in the membrane at the expense of branched-chain species, whereas exposure to the branched alcohol isobutanol produced the opposite effect. Isotope tracer experiments demonstrated that C. thermocellum directly incorporates the carbon backbones of exogenous alcohols and acids into fatty acids, providing a mechanistic basis for these contrasting shifts. We show that the bifunctional aldehyde/alcohol dehydrogenase AdhE is essential for the assimilation of exogenous alcohols into fatty acids, acting through its oxidative activity by first oxidizing alcohols to aldehydes and then converting them to acyl-CoA intermediates. Deletion of the pyruvate:ferredoxin oxidoreductase isozyme pfor4 abolished branched-chain fatty acid synthesis, but supplementation with isobutanol restored production, indicating that Pfor4 substitutes for the canonical branched-chain α-keto acid dehydrogenase complex. These findings reveal two distinct routes for branched-chain fatty acid production in C. thermocellum: a Pfor4-dependent pathway from α-keto acid intermediates derived from amino acid synthesis, and an AdhE-dependent salvage pathway that assimilates exogenous branched-chain alcohols.

Acetivibrio thermocellus↗

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗

A structural explanation for the mechanism and specificity of plant branching enzymes I and IIb

Branching enzymes (BEs) are essential in the biosynthesis of starch and glycogen and play critical roles in determining the fine structure of these polymers. The substrates of these BEs are long carbohydrate chains that interact with these enzymes via multiple binding sites on the enzyme’s surface. By controlling the branched-chain length distribution, BEs can mediate the physiological properties of starch and glycogen moieties; however, the mechanism and structural determinants of this specificity remain mysterious. In this study, we identify a large dodecaose binding surface on rice BE I (BEI) that reaches from the outside of the active site to the active site of the enzyme. Mutagenesis activity assays confirm the importance of this binding site in enzyme catalysis, from which we conclude that it is likely the acceptor chain binding site. Comparison of the structures of BE from Cyanothece and BE1 from rice allowed us to model the location of the donor-binding site. We also identified two loops that likely interact with the donor chain and whose sequences diverge between plant BE1, which tends to transfer longer chains, and BEIIb, which transfers exclusively much shorter chains. When the sequences of these loops were swapped with the BEIIb sequence, rice BE1 also became a short-chain transferring enzyme, demonstrating the key role these loops play in specificity. Taken together, these results provide a more complete picture of the structure, selectivity, and activity of BEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN

Physics-informed neural network (PINN) has been successfully applied in solving a variety of nonlinear non-convex forward and inverse problems. However, the training is challenging because of the non-convex loss functions and the multiple optima in the Bayesian inverse problem. In this work, we propose a multi-variance replica exchange stochastic gradient Langevin dynamics method to tackle the challenge of the multiple local optima in the optimization and the challenge of the multiple modal posterior distribution in the inverse problem. Replica exchange methods are capable of escaping from the local traps and accelerating the convergence; two chains with different temperatures are designed where the low temperature chain aims for the local convergence, and the target of the high temperature chain is to travel globally and explore the whole loss function entropy landscape. However, it may not be efficient to solve mathematical inversion problems by using the vanilla replica method directly since the method doubles the computational cost in evaluating the forward solvers (likelihood functions) in the two chains. To address this issue, we propose to make different assumptions on the energy function estimation and this facilities one to use solvers of different fidelities in the likelihood function evaluation. More precisely, one can use a solver with low fidelity in the high temperature chain while using a solver with high fidelity in the low temperature chain. Our proposed method significantly lowers the computational cost in the high temperature chain, meanwhile preserving the accuracy and converging very fast. Here we give an unbiased estimate of the swapping rate and give an estimation of the discretization error of the scheme. To verify our idea, we design and solve four inverse problems which have multiple modes. The proposed method is also employed to train the Bayesian PINN to solve the forward and inverse problems; faster and more accurate convergence has been observed when compared to the stochastic gradient Langevin dynamics (SGLD) method and vanilla replica exchange methods.

97 MATHEMATICS AND COMPUTING↗

Confocal Raman Microscopy Investigation of Phospholipid Monolayers Deposited on Nitrile-Modified Surfaces in Porous Silica Particles

Phospholipid bilayers deposited on a variety of surfaces offer models for investigation of the lipid membrane structure and supports for biocompatible sensors. Hybrid-supported phospholipid bilayers (HSLBs) are stable membrane models for these investigations, typically prepared by self-assembly of a lipid monolayer over an n-alkane-modified surface. HSLBs have been prepared on n-alkyl chain-modified silica and used for lipophilicity-based chromatographic separations. The structure of these hybrid bilayers differs from vesicle membranes where the lipid head group spacing is greater due to interdigitation of the lipid acyl chains with the underlying n-alkyl chains bound to the silica surface. This interdigitated structure exhibits a broader melting transition at a higher temperature due to strong interactions between the lipid acyl chains and the immobile n-alkyl chains bound to silica. In the present work, we seek to reduce the interactions between a lipid monolayer and its supporting substrate by self-assembly of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) on porous silica functionalized with nitrile-terminated surface ligands. The frequency of Raman scattering of the surface -C≡N stretching mode at the lipid–nitrile interface is consistent with an n-alkane-like environment and insensitive to lipid head group charge, indicating that the lipid acyl chains are in contact with the surface nitrile groups. The head group area of this lipid monolayer was determined from the within-particle phospholipid concentration and silica specific surface area and found to be 54 ± 2 Å 2 , equivalent to the head group area of a DMPC vesicle bilayer. The structure of these nitrile-supported phospholipid monolayers was characterized below and above their melting transition by confocal Raman microscopy and found to be nearly identical to DMPC vesicle bilayers. Their narrow gel-to-fluid-phase melting transition is equivalent to dispersed DMPC vesicles, indicating that the acyl chain structure on the nitrile support mimics the outer leaflet structure of a vesicle membrane.

36 MATERIALS SCIENCE↗

High-Resolution Comonomer Sequencing of Blocky Brominated Syndiotactic Polystyrene Copolymers Using 13C NMR Spectroscopy and Computer Simulations

This work demonstrates the first high-resolution comonomer sequencing of Blocky brominated syndiotactic polystyrene (sPS-co-sPS-Br) copolymers based on pentad assign- ments of the quaternary carbon region of the nuclear magnetic resonance spectrum. Copolymers containing p-bromostyrene (Br-Sty) units were prepared in matched sets using postpolymerization bromination methods carried out in the heterogeneous gel state (Blocky) and homogeneous solution state (Random). Quantitative information from the quaternary carbon spectra, heteronuclear multiple bond correlation spectroscopy, electronic structure calculations, and simulated statistically random copolymers was correlated to confirm the carbon resonance assignments for all 20 possible pentad comonomer sequences. Using the experimental pentad sequence prevalences, a computer code was developed to simulate chains with microstructures typical of each sample as a means to visually represent the copolymer blockiness with quantitative precision. Based on the microstructure and distribution of run lengths in these chains, the simulations revealed that the Blocky copolymers contain a high degree of blockiness. By comparing the run lengths in the simulated chains to the average number of styrene units in a crystalline segment of sPS (found by small-angle X-ray scattering), copolymer crystallizability was predicted. For the simulated Blocky B-21% (21 mol % Br-Sty) chain, the probability of randomly selecting a styrene unit in a crystallizable block was 25.8%, while that in the simulated Random R-18% was zero, in excellent agreement with the experimental crystallization behavior measured by differential scanning calorimetry. Additionally, these predictions confirmed that the simulated chains accurately represent the ensemble of chains in their respective copolymer samples. Furthermore, each simulated Blocky chain contained one or more long sPS blocks that paralleled the measured 38-40 styrene units spanning a crystalline segment within the sPS/CCl4 gel. This finding affirmed that the long sPS segments originated from the precise lamellar structure within the heterogeneous gel morphology (i.e., block length is correlated with lamellar thickness). Overall, the ability to tailor the copolymer microstructure through control of the semicrystalline gel morphology opens the door to synthesizing ordered copolymers by postpolymerization functionalization processes with unprecedented levels of compositional control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Backbone Dynamics of Bottlebrush Polymers Studied by Neutron Scattering

Bottlebrush polymers have a versatile architecture that is highly customizable due to the combination of a linear backbone and side chains. As a result of the chemical tethering of the side chains, both parts cannot be easily be separated. Huge effort is seen regarding the dynamical behavior of the side chains or the entire bottlebrush polymer, whereas few studies are available considering the backbone. Here, isotopic labeling in combination with quasi-elastic neutron scattering was used to compare the dynamical behavior of the bottlebrush’s backbone with the side chain dynamics. Keeping the side chains deuterated, (h-PNB)- g -(d-PPO), leads to the scattering signal dominated by backbone dynamics, while the fully protonated sample, (h-PNB)- g -(h-PPO), gives side chain dynamics. Both results reveal slower dynamics associated with the backbone with less heterogeneity, as seen for the side chains. Additionally, a plasticizer effect for the backbone dynamics is confirmed by extracting the glass transition temperature and comparing it with pure linear PNB.

neutron scattering↗

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T g ) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T g predictions of various polymers with different chemistries, polymer side chain lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of tacticity and chiral center-to-dipole distance on mesogen-free liquid crystalline self-assembly of sulfonyl-containing comb-like polymers

In this report, new approaches were implemented to achieve novel ferroelectric liquid crystalline self-assembly in mesogen-free comb-like isotactic polyoxypropylenes (iPOPs) bearing mono- or di-sulfonyl groups, which have potential to exhibit high spontaneous polarization for applications in advanced electronic devices. iPOPs with n-alkylsulfonylpentylthioether side chains (iPOP-SC 5 SO 2 C n , where C n is the alkyl tail with n being either 12 or 8) were prepared via a post-polymerization substitution reaction from isotactic poly[(R)-(–)-epichlorohydrin]. Here, the effects of main-chain tacticity, chiral center-to-dipole distance, number of sulfonyl dipoles per side chain, and n-alkyl tail length on the liquid crystalline self-assembly behavior were investigated by comparing iPOPs with their atactic counterparts. First, when the sulfonyl dipole was placed far away from the chiral center in iPOP-SC 5 SO 2 C n compared with our previously reported isotactic polyethers with n-alkylsulfonyl side chains (iPOP-SO 2 C n ), the dipole–dipole interactions among the side chains decreased, which led to more liquid crystalline phases. Smectic E (SmE) and A (SmA) phases were observed after crystal melting; however, the main-chain chiral center was found to have an insignificant effect on the liquid crystalline assembly when compared to the atactic samples. Second, the longer C n tails increased the transition temperatures as a result of stronger van der Waals interactions. Third, after the thioether linkage in the side chain was oxidized into the sulfonyl group, the chiral center–dipole and dipole–dipole interactions in the resultant polymers (i.e., iPOP-SO 2 C 5 SO 2 C n ) enhanced. As a result, the liquid crystalline phase transitions (i.e., crystal → SmE → SmA → I) were pushed to higher temperatures. The knowledge gained in this study will help us further design and achieve the ferroelectric smectic C* phase in mesogen-free comb-like sulfonylated liquid crystalline polymers.

36 MATERIALS SCIENCE↗

Molecular engineering of fluoroether electrolytes for lithium metal batteries

Fluoroether solvents are promising electrolyte candidates for high-energy-density lithium metal batteries, where high ionic conductivity and oxidative stability are important metrics for design of new systems. Recent experiments have shown that these performance metrics, particularly stability, can be tuned by changing the fraction of ether and fluorine content. However, little is known about how different molecular architectures influence the underlying ion transport mechanisms and conductivity. Here, we use all-atom molecular dynamics simulations to elucidate the ion transport and solvation characteristics of fluoroether chains of varying length, and having different ether segment and fluorine terminal group contents. The design rules that emerge from this effort are that solvent size determines lithium-ion transport kinetics, solvation structure, and solvation energy. In particular, the mechanism for lithium-ion transport is found to shift from ion hopping between solvation sites located in different fluoroether chains in short-chain solvents, to ion–solvent co-diffusion in long-chain solvents, indicating that an optimum exists for molecules of intermediate length, where hopping is possible but solvent diffusion is fast. Consistent with these findings, our experimental measurements reveal a non-monotonic behavior of the effects of solvent size on lithium-ion conductivity, with a maximum occurring for medium-length solvent chains. Finally, a key design principle for achieving high ionic conductivity is that a trade-off is required between relying on shorter fluoroether chains having high self-diffusivity, and relying on longer chains that increase the stability of local solvation shells.

25 ENERGY STORAGE↗

Surfactant Facilitated Spreading of Aqueous Drops on Hydrophobic Surfaces

Microgravity technologies often require aqueous phases to spread over nonwetting hydrophobic solid surfaces. Surfactants facilitate the wetting of water on hydrophobic surfaces by adsorbing on the water/air and hydrophobic solid/water interfaces and lowering the surface tensions of these interfaces. The tension reductions decrease the contact angle, which increases the equilibrium wetted area. Hydrocarbon surfactants; (i.e., amphiphiles with a hydrophobic moiety consisting of an extended chain of (aliphatic) methylene -CH2- groups attached to a large polar group to give aqueous solubility) are capable of reducing the contact angles on surfaces which are not very hydrophobic, but do not reduce significantly the contact angles of the very hydrophobic surfaces such as parafilm, polyethylene or self assembled monolayers. Trisiloxane surfactants (amphiphiles with a hydrophobe consisting of methyl groups linked to a trisiloxane backbone in the form of a disk ((CH3)3-Si-O-Si-O-Si(CH3)3) and an extended ethoxylate (-(OCH2CH2)a-) polar group in the form of a chain with four or eight units) can significantly reduce the contact angle of water on a very hydrophobic surface and cause rapid and complete (or nearly complete) spreading (termed superspreading). The overall goal of the research described in this proposal is to establish and verify a theory for how trisiloxanes cause superspreading, and then use this knowledge as a guide to developing more general hydrocarbon based surfactant systems which superspread. We propose that the trisiloxane surfactants superspread because their structure allows them to strongly lower the high hydrophobic solid/aqueous tension when they adsorb to the solid surface. When the siloxane adsorbs, the hydrophobic disk parts of the molecule adsorb onto the surface removing the surface water. Since the cross-sectional area of the disk is larger than that of the extended ethoxylate chain, the disks can form a space-filling mat on the surface which removes a significant amount of the surface water. In this presentation, we report the results of measurements of the molecular packing and rates of kinetic exchange of the trisiloxane surfactants at the air/water interface in order to confirm our picture of trisiloxane packing, and provide additional insight into the superspreading process. We used the pendant bubble technique as a Langmuir trough to measure the trisiloxane equation of state which relates the tension to the surface concentration. From these measurements we obtain accurate values for the maximum packing density. We find that trisiloxanes with 4 and 8 ethoxylate groups have the same maximum packing concentration, indicating that the maximum packing is controlled by the cross section of the head group. For trisiloxanes with larger than eight ethoxylates, the maximum packing increases with ethoxylate number, indicating that the disposition of the ethoxylate chain (i.e., its effective size) is controlling. This supports our picture of superspreading: The superspreading ability of trisiloxanes decreases considerably for trisiloxanes with larger than eight ethoxylates; the packing measurements indicate that for the higher ethoxylate number trisiloxanes, the compact nonpolar head groups are pushed apart by the ethoxylate chain. They leave spaces of surface water on adsorption and do not lower the solid tension as much as their lower chain analogues. Finally the report measurements of the dynamic tension reduction accompanying the adsorption of trisiloxanes onto an initially clean interface using the pendant bubble technique, and we obtain from these relaxations, the equation of state and a mass transfer model, the rate constants for kinetic exchange. We find that the rate constants for desorption of trisiloxanes are generally much slower than for analogous aliphatic polyethoxylate surfactants with identical ethoxylate chain lengths. When an aqueous drop of a superspreader solution is placed on a hydrophobic surface and begins to spread, the lower desorption rates allows the tension at the drop center to remain reduced relative to the tension of the expanding periphery, thus strengthening Marangoni forces which can assist the spreading. Marangoni forces can be especially significant in the case of superspreaders because their maximum equilibrium reduction in tension is several dynes/cm lower than for aliphatic surfactants.

Kumar, Nitin↗