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At least 73 records · Page 4

C-C Coupling Mechanism on Cu(100) A Molecular Dynamics Study at 298K

The electrochemical reduction of carbon dioxide (CO2) into valuable fuels such as C1 (syngas, methane) and C2 (ethylene, ethanol) products is a key strategy for achieving a carbon-neutral economy. Computational studies of C-C coupling, a critical step in CO2 reduction, are essential for designing more efficient catalysts. However, simulating these processes under realistic electrochemical conditions, including temperature and solvent effects, is computationally demanding. In this work, we develop a machine learning-based atomistic potential to study CO2 reduction on Cu(100) surfaces, accounting for temperature and explicit water solvent effects. We compute thermodynamic free energies of the possible C-C coupling pathways, CO*+CO*→OCCO*, CO*+CHO*→OCCHO*, CO*+COH*→OCCOH*, CHO*+COH*→OHCCOH*, COH*-COH*→HOCCOH*, and CHO*-CHO*→OHCCHO*. Our results quantify the thermodynamic tendencies of these reactions and reveal that, in addition to the well-established CO* + CO* → OCCO* pathway, CHO* is a critical intermediate in the formation of C2 products on Cu(100). Furthermore, we demonstrate that the machine learning approach offers a cost-efficient framework for studying CO2 reduction on diverse catalysts under realistic electrochemical conditions.

machine learning↗

Modeling Phase Equilibrium of Common Sugars Glucose, Fructose, and Sucrose in Mixed Solvents

The industrial processing of sugars and sugar-containing mixtures is gaining widespread use as a form of renewable manufacturing from biomass. To aid in process modeling for design and optimization, a commonly available thermodynamic model is needed that describes the phase equilibrium of these compounds. This work compiles and compares models for solid–liquid and vapor–liquid phase equilibrium from the available data for the representative sugars glucose, fructose, and sucrose in the representative solvents water, methanol, and ethanol, including data for multisugar, multisolvent systems. Additionally, the nonrandom two-liquid (NRTL) model was chosen for these systems because of its widespread use in industry and the availability of parameters for many solvents and cosolutes. The association-NRTL (aNRTL) model was investigated as an improvement for modeling sugars, which may experience a high degree of association because of their many hydroxy groups. Both models accurately capture the data and are able to predict the behavior of multisugar systems with only solute–solvent interaction parameters. The aNRTL model shows an improvement over the baseline NRTL model that is most significant for sucrose, the component with the highest association strength, and least significant for fructose, which has the lowest association strength.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical specificity in polyzwitterion-polyelectrolyte coacervates: polycations vs polyanions

Aqueous solutions containing polyzwitterions and polyelectrolytes were studied to probe the effects of chemical specificity on the complexation among different types of chains and resulting liquid–liquid phase separation (coacervation). Two kinds of blends were studied. A polyzwitterion, poly(sulfobetaine methacrylate) (PSBMA), was blended with either (1) a polycation, poly(diallydimethylammonium chloride) (PDADMAC), or (2) a polyanion, sodium poly(styrene sulphonate) (NaPSS). Coacervation was observed in both blends after equilibration, while the freshly prepared blend solutions exhibited distinct behavior dependent on the mixing protocols. Mixing solutions of the polyzwitterions and the polycations led to coacervation almost instantaneously. In contrast, the blends containing the same polyzwitterions and the polyanions exhibited no such coacervation by following the same mixing protocol. However, blends prepared after dissolving a solid mixture containing the same polyzwitterions and the polyanions in water exhibited coacervation. Based on the small-angle X-ray scattering (SAXS), cryo-electron microscopy, and rheology measurements, complexation and coacervation in the polyzwitterion-polyelectrolyte blends is rationalized in terms of the entropy change associated with reorganization of solvent (water), which appears to be larger in the polyzwitterion-polycation case in comparison with the polyzwitterion-polyanion blends. These results highlight the importance of chemical specificity and mixing protocols leading to metastable structures in designing a new class of materials based on macromolecular complexation of polyzwitterions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetics of the reactions of the acid anhydrides with aromatic amines in aprotic solvents

Work has revealed that diamine derivatives of diphenylmethane (IV), diphenyl ether (V), benzophenone (IV), fluorene (VII), and fluorenone (VIII) polymerizations with pyromellitic dianhydride in DMA were dependent on the basicity of the amine compound. The correlation between the basicity of the amine and its reactivity with phthalic anhydride was determined. Basicity measurements were made by potentiometric titration of each amine in an acetonitrile-water solvent system, from which the pKa of the amine could be determined. Reactivity was defined in terms of the second order rate constant derived form spectrophotometric examination of the reaction between each amine and phthalic anhydride in DMA. This reaction was expected to proceed in either one (for a monoamine) or two (for a diamine) stages.

Sugg, E.↗

Nuclear quantum effects on the quasiparticle properties of the chloride anion aqueous solution within the GW approximation

Photoelectron spectroscopy experiments in ionic solutions reveal important electronic structure information, in which the interaction between hydrated ions and water solvent can be inferred. Based on many-body perturbation theory with GW approximation, we theoretically compute the quasiparticle electronic structure of chloride anion solution, which is modeled by path-integral abinitio molecular dynamics simulation by taking account the nuclear quantum effects (NQEs). The electronic levels of hydrated anion as well as water are determined and compared with the recent experimental photoelectron spectra. It is found that NQEs improve the agreement between theoretical prediction and experiment because NQEs effectively weaken the hybridization of the between the Cl – anion and water. Furthermore, our study indicates that NQEs plays a small but non-negligible role in predicting the electronic structure of the aqueous solvation of ions of the Hofmeister series.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Diffusion in mixed solvents. III - The heat of mixing parameter and the Soret coefficient

New evidence is presented that for aqueous glycerol solutions, the Soret coefficient of glycerol, sigma sub 1 = D sub 1 T/D sub 1 (where D sub 1 T and D sub 1 are the thermal and self-diffusion coefficients, respectively, of glycerol in aqueous solutions), is an integral part of the heat of mixing parameter. Expressions are presented indicating the importance of the Soret coefficients to correlations for diffusion processes in glycerol water solvents.

Carapellucci, P. A.↗

Understanding Metal–Organic Framework Nucleation from a Solution with Evolving Graphs

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+ and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Furthermore, descriptors such as the average coordination number between half-SBUs and fractal dimension are of particular interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CO 2 utilization in built environment via the P CO 2 swing carbonation of alkaline solid wastes with different mineralogy

Carbon mineralization to solid carbonates is one of the reaction pathways that can not only utilize captured CO 2 but also potentially store it in the long term. In this study, the dissolution and carbonation behaviors of alkaline solid wastes (i.e., waste concrete) was investigated. Concrete is one of the main contributors to a large carbon emission in the built environment. Thus, the upcycling of waste concrete via CO 2 utilization has multifaceted environmental benefits including CO 2 emission reduction, waste management and reduced mining. Unlike natural silicate minerals such as olivine and serpentine, alkaline solid wastes including waste concrete are highly reactive, and thus, their dissolution and carbonation behaviors vary significantly. Here, both conventional acid (e.g., hydrochloric acid) and less studied carbonic acid (i.e., CO 2 saturated water) solvent systems were explored to extract Ca from concrete. Non-stoichiometric dissolution behaviors between Ca and Si were confirmed under far-from-equilibrium conditions (0.1 wt% slurry density), and the re-precipitation of the extracted Si was observed at near-equilibrium conditions (5 wt% slurry density), when the Ca extraction was performed at a controlled pH of 3. These experiments, with a wide range of slurry densities, provided valuable insight into Si re-precipitation phenomena and its effect on the mass transfer limitation during concrete dissolution. Next, the use of the partial pressure of CO 2 for the pH swing carbon mineralization process was investigated for concrete, and the results were compared to those of Mg-bearing silicate minerals. In the P CO 2 swing process, the extraction of Ca was significantly limited by the precipitation of the carbonate phase (i.e., calcite), since CO 2 bubbling could not provide a low enough pH condition for concrete–water–CO 2 systems. Furthermore, this study showed that the two-step carbon mineralization via P CO 2 swing, that has been developed for Mg-bearing silicate minerals, may not be viable for highly reactive Ca-bearing silicate materials (e.g., concrete). The precipitated calcium carbonate (PCC) derived from waste concrete via a pH swing process showed very promising results with a high CO 2 utilization potential as an upcycled construction material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree–Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. Here, the accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, R cut . R cut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small R cut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Rare-Earth Mineral Separation with Insights from Molecular Recognition: Functionalized Hydroxamic Acid Adsorption onto Bastnäsite and Calcite

Enhancing the separation of rare-earth elements (REEs) from gangue materials in mined ores requires an understanding of the fundamental interactions driving the adsorption of collector ligands onto mineral interfaces. In this work, we examine five functionalized hydroxamic acid ligands as potential collectors for the REE-containing bastnäsite mineral in froth flotation using density functional theory calculations and a suite of surface-sensitive analytical spectroscopies. These include vibrational sum frequency generation, attenuated total reflectance Fourier transform infrared, Raman, and X-ray photoelectron spectroscopies. Differences in the chemical makeup of these ligands on well-defined bastnäsite and calcite surfaces allow for a systematic relationship connecting the structure to adsorption activity to be framed in the context of interfacial molecular recognition. Here we show how the intramolecular hydrogen bonding of adsorbed ligands requires the inclusion of explicit water solvent molecules to correctly map energetic and structural trends measured by experiments. We anticipate that the results and insights from this work will motivate and inform the design of improved flotation collectors for REE ores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen-Bonding Interactions in Hybrid Aqueous/Nonaqueous Electrolytes Enable Low-Cost and Long-Lifespan Sodium-Ion Storage

Although “water-in-salt” electrolytes have opened a new pathway to expand the electrochemical stability window of aqueous electrolytes, the electrode instability and irreversible proton co-insertion caused by aqueous media still hinder the practical application, even when using exotic fluorinated salts. In this study, an accessible hybrid electrolyte class based on common sodium salts is proposed, and crucially an ethanol-rich media is introduced to achieve highly stable Na-ion electrochemistry. Here, ethanol exerts a strong hydrogen-bonding effect on water, simultaneously expanding the electrochemical stability window of the hybridized electrolyte to 2.5 V, restricting degradation activities, reducing transition metal dissolution from the cathode material, and improving electrolyte–electrode wettability. The binary ethanol–water solvent enables the impressive cycling of sodium-ion batteries based on perchlorate, chloride, and acetate electrolyte salts. Notably, a Na 0.44 MnO 2 electrode exhibits both high capacity (81 mAh g –1 ) and a remarkably long cycle life >1000 cycles at 100 mA g –1 (a capacity decay rate per cycle of 0.024%) in a 1 M sodium acetate system. The Na 0.44 MnO 2 /Zn full cells also show excellent cycling stability and rate capability in a wide temperature range. The gained understanding of the hydrogen-bonding interactions in the hybridized electrolyte can provide new battery chemistry guidelines in designing promising candidates for developing low-cost and long-lifespan batteries based on other (Li + , K + , Zn 2+ , Mg 2+ , and Al 3+ ) systems.

25 ENERGY STORAGE↗

Double-Atom Catalysts Featuring Inverse Sandwich Structure for CO 2 Reduction Reaction: A Synergetic First-Principles and Machine Learning Investigation

Electrocatalytic CO 2 reduction reactions (CO 2 RR) based on scalable and highly efficient catalysis provide an attractive strategy for reducing CO 2 emissions. Here in this work, we combined first-principles density functional theory (DFT) and machine learning (ML) to comprehensively explore the potential of double-atom catalysts (DACs) featuring an inverse sandwich structure anchored on defective graphene (gra) to catalyze CO 2 RR to generate C 1 products. We started with five homonuclear M 2 ⊥gra (M = Co, Ni, Rh, Ir, and Pt), followed by 127 heteronuclear MM'⊥gra (M = Co, Ni, Rh, Ir, and Pt, M' = Sc–Au). Stable DACs were screened by evaluating their binding energy, formation energy, and dissolution potential of metal atoms, as well as conducting first-principles molecular dynamics simulations with and without solvent water molecules. Based on DFT calculations, Rh 2 ⊥gra DAC was found to outperform the other four homonuclear DACs and the Rh-based single- and double-atom catalysts of noninverse sandwich structures. Out of the 127 heteronuclear DACs, 14 were found to be stable and have good catalytic performance. An ML approach was adopted to correlate key factors with the activity and stability of the DACs, including the sum of radii of metal and ligand atoms (d M–M' , d M–C , and d M'–C ), the sum and difference of electronegativity of two metal atoms (P M + P M' , P M – P M '), the sum and difference of first ionization energy of two metal atoms (I M + I M' , I M – I M '), the sum and difference of electron affinity of two metal atoms (A M + A M' , A M – A M '), and the number of d-electrons of the two metal atoms (Nd). The obtained ML models were further used to predict 154 potential electrocatalysts out of 784 possible DACs featuring the same inverse sandwich configuration. Overall, this work not only identified promising CO 2 RR DACs featuring the reported inverse sandwich structure but also provided insights into key atomic characteristics associated with high CO 2 RR activity.

30 DIRECT ENERGY CONVERSION↗

Electric Field’s Dueling Effects through Dehydration and Ion Separation in Driving NaCl Nucleation at Charged Nanoconfined Interfaces

Investigating nucleation in charged nanoconfined environments under electric fields is crucial for many scientific and engineering applications. Here we study the nucleation of NaCl from aqueous solution near charged surfaces using machine-learning-augmented enhanced sampling molecular dynamics simulations. Our simulations successfully drive phase transitions between the liquid and solid phases of NaCl. The solid phase is stabilized under electric fields, particularly at an intermediate surface charge density. We examine which physical characteristics drive the nucleation of NaCl from aqueous solutions and find that the removal of solvent water from Cl– at the solid precursor surface plays a more critical role than the accumulation of ions. Our simulations reveal the competing effects of electric fields on nucleation processes: they facilitate the removal of water, promoting nucleation, but also promote the separation of ion pairs, thereby hindering nucleation. Here, this work provides a framework for studying nucleation processes in nanoconfined environments under electric fields and provides physical insights for the design of electrochemistry materials.

Electric fields↗

First principles modeling of polymer encapsulant degradation in Si photovoltaic modules

An outstanding issue in the longevity of photovoltaic (PV) modules is the accelerated degradation caused by the presence of moisture. Moisture leads to interfacial instability, de-adhesion, encapsulant decomposition, and contact corrosion. However, experimental characterization of moisture in PV modules is not trivial and its impacts can take years or decades to establish in the field, presenting a major obstacle to designing high-reliability modules. First principles calculations provide an alternative way to study the ingress of water and its detrimental effect on the structure and decomposition of the polymer encapsulant and interfaces between the encapsulant and the semiconductor, the metal contacts, or the dielectric layer. Here, we use density functional theory (DFT) computations to model single chain, crystalline and cross-linked structures, infrared (IR) signatures, and degradation mechanisms of ethylene vinyl acetate (EVA), the most common polymer encapsulant used in Si PV modules. IR-active modes computed for low energy EVA structures and possible decomposition products match well with reported experiments. The EVA decomposition energy barriers computed using the Nudged Elastic Band (NEB) method show a preference for acetic acid formation as compared to acetaldehyde, are lowered in the presence of a water solvent or hydroxyl ion catalyst, and match well with reported experimental activation energies. This systematic study leads to a clear picture of the hydrolysis-driven decomposition of EVA in terms of energetically favorable mechanisms, possible intermediate structures, and IR signatures of reactants and products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catalytic conversion of high S-lignin to a sustainable tri-epoxide polymer precursor

More than 40 million tons of thermosetting plastics are produced annually and 70% of those are epoxy polymers. The synthesis of bio-based epoxide provides a pathway for making renewable thermoset plastics. We describe in this study the use of a genetically modified high-S poplar lignin to produce 4-propyl-2,6-dimethoxyphenol (DMPP), which is converted to the tri-functional compound propylpyrogallol (DMPPO) by a reaction catalysed by N 2 O 5 in the green solvent water. The resulting DMPPO can be converted to a novel tri-epoxide by reaction with epichlorohydrin. Native high-S lignin as well as several organosolv lignins extracted from this poplar biomass were investigated as feedstocks. Notably, direct reductive catalytic fractionation (RCF) of the high-S poplar wood over Pd–Zn/C catalyst with Pd : Zn ratio 1 : 10 at 225 °C under 35 bar H 2 in methanol gave the highest yield of biophenol monomers from the lignin present, the major product being DMPP. Under optimized conditions, conversion of DMPP to DMPPO over the Nb 2 O 5 was nearly quantitative (96% yield), and this conversion could be made without extensive prior purification of the DMPP. The Nb 2 O 5 catalyst could be recycled several times before significant deactivation. This sequence of two catalytic reactions demonstrates that the production of epoxides from lignin-derived DMPPO is a realistic strategy for making renewable polymer building blocks from biomass.

09 BIOMASS FUELS↗

Survey of application of radiation to preparative chemistry

The use of radiation for preparative chemistry in liquid solutions is investigated. General principles are presented and preparations involving reduction, oxidation, polymerization, and decomposition are given. The use of various solvents, water, other inorganic liquids and organic liquids for this purpose is discussed. Finally, a commentary is made on some specific applications where radiation chemistry as a preparative technique may be useful.

Philipp, W. H.↗

Optimization of spacecraft high temperature outgassing duration

Spacecraft systems are baked-out under vacuum to remove occluded and adsorbed gases, solvents, water, plasticizer, and other materials acquired during their manufacture. Two bakeouts of solar panels were carried out. Quartz crystal microbalances installed in the vacuum chamber during the tests and held at 273 K (0 C) provided an ongoing measure of the panels' outgassing. From these data, the panels' material weight losses versus time were obtained. A comparison of the total weight loss expected during a relatively long bakeout with that accomplished during a reasonable period of time was used as a criteria for an acceptable duration of the bakeout in order to optimize cost effectiveness.

Scialdone, J. J.↗

Brushless Cleaning of Solar Panels and Windows

Machine proposed for cleaning solar panels and reflectors uses multiple vortexes of air, solvent, and water to remove dust and dirt. Uses no brushes that might abrade solar surfaces and thereby reduce efficiency. Machine can be readily automated and can be used on curved surfaces such as aparbolic reflectors as well as on flat ones. Cleaning fluids are recycled, so that large quantities of water and solvent are not needed.

Schneider, H. W.↗