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At least 721 records · Page 40

3D printed lignin/polymer composite with enhanced mechanical and anti-thermal-aging performance

Lignin is the most abundant natural aromatic polymer globally but is still underutilized as a renewable material, even with its versatile properties. One approach to using lignin is to incorporate it in polymer composites, but this application is often limited by the poor mechanical performance of the resultant composite due to the poor interfacial adhesion. Following the structure–property relationship, stronger interactions were designed to be enhanced by alternating the functional groups of lignin. Here, this study applied a demethylation method to hardwood lignin (Ori-Lig) to introduce more phenolic hydroxyl groups. Research studies with rheology behavior and molecular simulations demonstrated that an increased phenolic hydroxyl content could improve the adhesion between the modified lignin (OH-Lig) and the polymer matrix at the interface. The tensile performance of the samples from the fused depositional modeling (FDM) 3D printing technique was also improved due to the improved interfacial adhesion. Specifically, by adding 10 wt% of the modified lignin, the tensile strength of the 3D printed samples could reach 46.1 MPa (40.2 MPa of Polyamide 12, PA12), and Young’s Modulus could be improved to 1.73 GPa (1.48 GPa of PA12). OH-Lig also improved anti-aging performance so that the tensile strength of the OH-Lig composite after thermo-aging (100 h at 140 °C) remained ~48MPa. The enhanced mechanical performance with anti-aging properties indicated that the OH-Lig composite may replace PA12 to reduce the use of petrol-based materials. This work showed the method of purposefully designing and modifying lignin structures to fulfill the interaction requirements between lignin and polymer matrix. The as-prepared lignin could be used to prepare functional composites to achieve improved mechanical performance and targeted functions at the same time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Membrane-based solvent extraction for the recovery of rare earths from phosphate mining process streams

This study reports on the capture of rare earth elements (REEs) from phosphate industry process streams, including phosphoric acid (PA) sludge and phosphogypsum (PG), using a membrane solvent extraction (MSX) process. While MSX has been proven effective for a relatively concentrated feed, its effectiveness for dilute REEs solutions remains unexplored. Investigated PA-sludge and PG particles contain total REEs concentrations of ∼1100 and ∼320 ppm, respectively. Acid leaching, implemented to dissolve the REEs, significantly dilutes the REEs concentration to ∼210 ppm for PA-sludge leachate and ∼60 ppm for PG leachate. These low concentrations, compounded by the higher levels of non-REE ions and radioactive species, uranium (U) and thorium (Th), poses challenges to the MSX process. Here, we demonstrated that N,N,N′,N′-tetraoctyl-diglycolamide (TODGA) selectively binds REEs from a >3 M nitric-acid leachate while effectively rejecting U and Th. Concentrations of light REEs in strip solution were doubled compared to the feed, while heavy REEs were preferentially extracted. Furthermore, >99% purity gypsum, free of U and Th, was precipitated during the acid leaching process, aiding separation by removing significant amounts of non-REEs species (e.g., calcium) prior to the MSX process. Molecular simulations support the experimental data, suggesting preferential separation of heavy over light REEs. Based on these results, a cost-effective integrated process including pretreatment, acid leaching, MSX, and wastewater treatment is proposed for the co-recovery of REEs, phosphoric acid, gypsum, and U. This study shows MSX as a technically and economically feasible process for the recovery of REEs from low-concentration process streams, offering advantages over conventional solvent extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A physics-informed operator regression framework for extracting data-driven continuum models

The application of deep learning toward discovery of data-driven models requires careful application of inductive biases to obtain a description of physics which is both accurate and robust. We present here a framework for discovering continuum models from high fidelity molecular simulation data. Our approach applies a neural network parameterization of governing physics in modal space, allowing a characterization of differential operators while providing structure which may be used to impose biases related to symmetry, isotropy, and conservation form. Here, we demonstrate the effectiveness of our framework for a variety of physics, including local and nonlocal diffusion processes and single and multiphase flows. For the flow physics we demonstrate this approach leads to a learned operator that generalizes to system characteristics not included in the training sets, such as variable particle sizes, densities, and concentration.

42 ENGINEERING↗

Probing degradation at solid-state battery interfaces using machine-learning interatomic potential

Solid-state batteries featuring fast ion-conducting solid electrolytes are promising next-generation energy storage technologies, yet challenges remain for practical deployment due to electro-chemo-mechanical instabilities at solid-solid interfaces. These interfaces, which include homogeneous/internal interfaces such as grain boundaries (GBs) and heterogeneous/external interfaces between solid-electrolyte and electrode materials, can impede Li-ion transport, deteriorate performance, and eventually lead to cell failure. Here, in this study, we leverage large-scale molecular simulations, enabled by validated machine-learning interatomic potentials, to directly probe the onset of interfacial degradation at the garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid-electrolyte/LiCoO 2 (LCO) cathode interface. By surveying different interfacial geometries and compositions, it is found that Li-deficient interfaces can lead to severe interfacial disordering with cation mixing and Co interdiffusion from LCO into LLZO. By contrast, Li-sufficient interfaces are less disordered, although elemental segregation with local ordering is observed. As a consequence of Co interdiffusion, Co-rich regions are formed at the GBs of LLZO due to cation segregation and trapping effects. This behavior is independent of the GB tilting axis, degree of disorder at the GBs, and Co concentration, which implies Co clustering at GBs is a general phenomenon in polycrystalline LLZO and can dictate its overall transport and mechanical properties. Our findings elucidate the underlying fundamental mechanisms that give rise to experimentally observed physicochemical properties and provide guidelines for interface design that can mitigate interfacial degradation and improve cycling performance.

25 ENERGY STORAGE↗

Hydrogen diffusion induced dislocation transformations in a nickel superalloy

The diffusion of hydrogen in metals and alloys induces embrittlement that can adversely affect the structural properties. We examine the adsorption and diffusion of hydrogen in Inconel-718 (IN-718), and scrutinize the ensuing effects on the dislocation behavior in the alloy to elucidate the fundamental mechanisms of hydrogen-microstructure interactions from classical molecular simulations. Hydrogen adsorption increases with time until the surface saturates, while hydrogen diffusion exhibits strong temperature dependence, with diffusion coefficients converging above 1300 K regardless of the initial hydrogen concentration in the alloy. The diffusion in IN-718 is significantly sluggish than in pure Ni, Fe, or Cr, and is strongly impacted by hydrogen concentrations, resulting in an order of magnitude higher diffusion coefficient for hydrogen (10-14 m2/s relative to 10-15 m2/s) at high concentrations, especially below 600 K. Hydrogen diffusion coefficient varies from 10-12 to 10-15 m2/s in IN-718 depending on temperature (500–1400 K). More critically, our results reveal that increasing hydrogen concentration induces microstructural changes in the alloy, transforming perfect dislocations into stair-rods and Shockley partials, with higher temperatures favoring the latter. The results are significant for hydrogen fuel applications to gain insights into the materials chemistry for designing safer and more efficient propulsion systems, particularly in high-performance environments related to controlled hydrogen combustion applications.

Banerjee, Tanumoy↗

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗

Energetics of water expulsion from intervening space between two particles during aggregation

Solvent expulsion away from an intervening region between two approaching particles plays important roles in particle aggregation yet remains poorly understood. Here, in this work, we use metadynamics molecular simulations to study the free energy landscape of removing water molecules from gibbsite and pyrophyllite slit pores representing the confined spaces between two approaching particles. For gibbsite, removing water from the intervening region is both entropically and enthalpically unfavorable. The closer the particles approach each other, the harder it is to expel water molecules. For pyrophyllite, water expulsion is spontaneous, which is different from the gibbsite system. A smaller pore makes the water removal more favorable. When water is being drained from the intervening region, single chains of water molecules are observed in gibbsite pore, while in pyrophyllite pore water cluster is usually observed. Water-gibbsite hydrogen bonds help stabilize water chains, while water forms clusters in pyrophyllite pore to maximize the number of hydrogen bonds among themselves. This work provides the first assessment into the energetics and structure of water being drained from the intervening region between two approaching particles during oriented attachment and aggregation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Environmental application of chlorine-doped graphitic carbon nitride: Continuous solar-driven photocatalytic production of hydrogen peroxide

Solar-driven photocatalytic generation of H 2 O 2 over metal-free catalysts is a sustainable approach for value-added chemical production. Here, we synthesized chlorine-doped graphitic carbon nitride (Cl-doped g-C 3 N 4 ) through a solvothermal method to effectively produce H 2 O 2 with a rate of 1.19 ± 0.06 µM min –1 under visible light irradiation, which was improved by 104 times compared to pristine g-C 3 N 4 . Continuous net production of H 2 O 2 was realized at a rate of 2.78 ± 0.10 µM min –1 up to 54 h with isopropanol as the hole scavenger, whereas H 2 O 2 production was only sustained for ~ 6 h without scavengers. Both molecular simulations and advanced spectroscopic characterizations elucidated that the Cl dopant increased the charge transfer rate, decreased the bandgap, and reduced the activation energy of the rate-limiting step of O 2 reduction, all of which favored H 2 O 2 production. Furthermore, this work implemented a novel metal-free photocatalyst for sustainable H 2 O 2 production and elucidated the mechanism for promoting H 2 O 2 production that can guide future photoreactive nanomaterial design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Critical role of solvation on CC13 porous organic cages for design of porous liquids

Efficient carbon capture requires the design of new materials with high CO 2 selectivity and gas adsorption capacity that can be incorporated into existing industrial processes. Porous liquids (PLs) are promising candidate materials that consist of a nanoporous host and a solvent forming a liquid with permanent porosity based on exclusion of the solvent from the interior of the nanoporous host. Stable PLs are based on solvent-nanoporous host interactions, which can be evaluated through molecular simulations. Here, time- and temperature-dependent density functional theory simulations were performed between four solvents, 2-bromophenol, 4-methylphenol, 2,4-dimethylphenol, and cyclohexanone and the CC13 porous organic cage (POC) as a prototypical PL composition. Overall, minimal reactions occurred in the PL including no changes in the POC structure. Additionally, POC-solvent coordination occurred through interactions of neighboring functional groups such as methyl/bromide and hydroxyl on the solvent molecules with the POC surface. Therefore, the location rather than the number of functional groups on the solvent molecule controls the POC-solvent interactions. Additionally, the POC pore window contracted or expanded up to 8% during solvation, which correlates with the experimental solubility and static solvent-POC binding, where solvents that caused less contraction of the POC pore window increased POC solubility. Finally, these results allow for the design of optimized POC-based PL compositions based on solvent-nanoporous host binding and variation in the pore window during solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultra-efficient polymer binder for silicon anode in high-capacity lithium-ion batteries

As a highly promising anode material for high-capacity lithium-ion batteries (LIBs), the low electronic conductivity and large volume variation of silicon (Si) make the slurry-coating Si based electrode requiring high content of “inert” materials and suffering rapid capacity fading. In this work, a polyimine, synthesized via one-step condensation reaction, has been demonstrated as an ultra-efficient polymer binder that can resolve the above issues. The polyimine binder containing Si electrode delivers superior electrochemical performance: a delithiation specific capacity of 804.4 mAh g –1 with capacity retention of 82.4% after 1000 cycles at the current density of 2 A g –1 . The high efficiency of polyimine binder for Si electrode has also been demonstrated with ultrahigh weight ratio of “active” material to “inert” material (R A/I ). The electrode with 95 wt% of Si (95Si/Polyimine, R A/I = 19) reveals a reversible delithiation capacity of 2114 mAh g –1 (capacity retention ~ 80.4%) over 200 cycles at the current density of 400 mA g –1 . Even at the high current density of 2 A g –1 , a delithiation capacity of 1087.8 mAh g –1 after 500 cycles can be obtained. Molecular simulations and atomic force microscopy (AFM) indentation are utilized to investigate the ultra-efficiency of polyimine binder. With simple manufacturing process and ultra-efficient binder performance, the designed polyimine binder will be definitely meaningful in achieving low-cost and high-capacity LIBs with prolonged cycle life.

25 ENERGY STORAGE↗

Tuning Enzyme Thermostability via Computationally Guided Covalent Stapling and Structural Basis of Enhanced Stabilization

Enhancing the thermostability of enzymes without impacting their catalytic function represents an important yet challenging goal in protein engineering and biocatalysis. We recently introduced a novel method for enzyme thermostabilization that relies on the computationally guided installation of genetically encoded thioether “staples” into a protein via cysteine alkylation with the noncanonical amino acid O-2-bromoethyl tyrosine (O2beY). Here, we demonstrate the functionality of an expanded set of electrophilic amino acids featuring chloroacetamido, acrylamido, and vinylsulfonamido side-chain groups for protein stapling using this strategy. Using a myoglobin-based cyclopropanase as a model enzyme, our studies show that covalent stapling with pchloroacetamido-phenylalanine (pCaaF) provides higher stapling efficiency and enhanced stability (thermodynamic and kinetic) compared to the other stapled variants and the parent protein. Interestingly, molecular simulations of conformational flexibility of the cross-links show that the pCaaF staple allows fewer energetically feasible conformers than the other staples, and this property may be a broader indicator of stability enhancement. Using this strategy, pCaaF-stapled variants with significantly enhanced stability against thermal denaturation (ΔT m ' = +27 °C) and temperature-induced heme loss (ΔT 50 = +30 °C) were obtained while maintaining high levels of catalytic activity and stereoselectivity. Crystallographic analyses of singly and doubly stapled variants provide key insights into the structural basis for stabilization, which includes both direct interactions of the staples with protein residues and indirect interactions through adjacent residues involved in heme binding. This work expands the toolbox of protein stapling strategies available for protein stabilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multistage Condensation Pathway Minimizes Hysteresis in Water Harvesting with Large-Pore Metal–Organic Frameworks

Metal-organic frameworks (MOFs) have emerged as promising materials for atmospheric water harvesting (AWH). Large-pore MOFs provide high water capacity, but their significant hysteresis between sorption and desorption makes them unsuitable for AWH. Co2Cl2(BTDD) is a noteworthy exception. This MOF has large, 2.2 nm diameter one-dimensional pores, and combines both record-high water capacity and minimal hysteresis, making it an excellent material for water capture in arid areas. Sorption reversibility in Co2Cl2(BTDD) has been attributed to continuous water uptake. However, the sharp adsorption/desorption in the isotherms supports a discontinuous first-order transition. Here we use molecular simulations to compute the water adsorption and desorption pathways and isotherms in a Co2Cl2(BTDD) model, to elucidate how does this MOF achieve reversibility despite its large pore size. The simulations reveal a multi-stage mechanism of discontinuous water uptake facilitated by spatial segregation of rows of hydrophilic metal sites bridged by ~1 nm hydrophobic ligands. The multi-stage mechanism breaks the barrier of capillary condensation into smaller, easier to surmount ones, resulting in a facile process despite the sharp density discontinuity between confined liquid and vapor. Our results explain why exchanging Co2+ for Ni2+ or Clfor F- in the MOF have minimal impact on the condensation and desorption pressures. On the other hand, we predict that a decrease in hydrophilicity of the MOF vertices would strongly increase the hysteresis. We expect that the relationships between spatial distribution of hydrophilic sites and hysteresis unraveled in this study assist the design of water harvesting materials with maximal capacity and reversibility.

Zaragoza, Alberto↗

Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important class of porous crystalline materials for applications ranging from gas adsorption and separation to catalysis. There are thousands of potential MOFs available for separation applications. Here, we developed a computational approach to screen MOFs for the separation of oxygen–helium mixtures at low temperatures (100–200 K), conditions that were motivated by issues associated with propulsion in space-based settings. We used detailed molecular simulations for a small number of MOFs to develop screening methods that were then used to estimate the optimum temperatures for separations using pressure swing adsorption for 2932 MOFs from the CoRE MOF database and the swing capacity and oxygen–helium selectivity at these temperatures. We used the stability of the best-performing structures in the presence of moisture as a means to provide a short list of high-performance materials. In addition to identifying specific materials for oxygen–helium separations, this approach could prove useful for selecting adsorbents for other gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗

Distinguishing Surface and Bulk Reactivity: Concentration-Dependent Kinetics of Iodide Oxidation by Ozone in Microdroplets

Iodine oxidation reactions play an important role in environmental, biological, and industrial contexts. The multiphase reaction between aqueous iodide and ozone is of particular interest due to its prevalence in the marine atmosphere and unique reactivity at the air–water interface. Here, we explore the concentration dependence of the I – + O 3 reaction in levitated microdroplets under both acidic and basic conditions. To interpret the experimental kinetics, molecular simulations are used to benchmark a kinetic model, which enables insight into the reactivity of the interface, the nanometer-scale subsurface region, and the bulk interior of the droplet. For all experiments, a kinetic description of gas- and liquid-phase diffusion is critical to interpreting the results. We find that the surface dominates the iodide oxidation kinetics under concentrated and acidic conditions, with the reactive uptake coefficient approaching an upper limit of 10 –2 at pH 3. In contrast, reactions in the subsurface dominate under more dilute and alkaline conditions, with inhibition of the surface reaction at pH 12 and an uptake coefficient that is 10× smaller. In conclusion, the origin of a changing surface mechanism with pH is explored and compared to previous ozone-dependent measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Properties and Chemical Transformations Near Interfaces

The properties of bulk water and aqueous solutions are known to change in the vicinity of an interface and/or in a confined environment, including the thermodynamics of ion selectivity at interfaces, transition states and pathways of chemical reactions, and nucleation events and phase growth. Here we describe joint progress in identifying unifying concepts about how air, liquid, and solid interfaces can alter molecular properties and chemical reactivity compared to bulk water and multicomponent solutions. Furthermore, we also discuss progress made in interfacial chemistry through advancements in new theory, molecular simulation, and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature Effects in Flexible Adsorption Processes for Amorphous Microporous Polymers

A collection of atomistic molecular simulations is reported that illustrate the impact of adsorption temperature on species uptake and adsorbate-induced structural rearrangement for amorphous polymers of intrinsic microporosity. Temperature-sensitive structural rearrangement is evaluated by contrasting two methods: standard grand canonical Monte Carlo simulations using a rigid framework approximation and a combined Monte Carlo/molecular dynamics approach that fully incorporates framework flexibility. We report single-component gas phase adsorption isotherms for CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , C 3 H 8 , and CO 2 across a temperature range of 250–400 K for models of an archetypal polymer of intrinsic microporosity, PIM-1. A quadratic model is presented that captures two main mechanisms of temperature-dependent adsorption-induced deformation of PIM-1 up to a relative swelling of 1.15: thermal expansion and an increased propensity to swell as a function of species uptake. Two case studies are reported that highlight the critical role of operating temperature in industrial storage and separation applications. The first study focuses on methane storage and delivery applications using a pressure–temperature swing adsorption application (PTSA). We demonstrate that larger working capacities are accompanied by increased volumetric strain between adsorption–desorption steps. The second case study considers PIM-1 as an adsorbent to separate an exemplar ternary syngas mixture at operating temperatures ranging 300–550 K. Here, a temperature threshold of ~400 K is identified, beyond which adsorption-induced PIM-1 swelling is negligible and the solubility selectivity-loading curve transitions to exhibiting a nearly linear relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗