85 Search Results

Water-lean solvents are a promising technology for capturing acid gases like carbon dioxide (CO2). In situ liquid time-of-flight secondary ionization mass spectroscopy (ToF-SIMS) is used to study a representative solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (2-EEMPA) with different CO2 loadings to reveal the complex solvent structure upon CO2 capture. Characteristic peaks of 2-EEMPA, such as m/z- 215 C11H23N2O2- (deprotonated 2-EEMPA) and m/z+ 217 C11H25N2O2+ (protonated 2-EEMPA), are detected due to acid gas uptake. Also, solvent molecules and carboxylate ion pairs, such as m/z– 259 C12H23N2O4– [(deprotonated 2-EEMPA∙∙∙CO2)] and m/z+ 261 C12H25N2O4+ (protonated 2-EEMPA∙∙∙CO2), are observed. Interestingly, more than one CO2 molecule can be capturedmore » per each solvent molecule as evidenced in SIMS mass spectra, for example, m/z– 321 C13H25N2O7– [(deprotonated 2-EEMPA)∙∙∙2CO2∙∙∙H2O], m/z+ 305 C13H25N2O4+ [(protonated 2-EEMPA)∙∙∙2CO2], m/z– 389 C17H29N2O8– [(deprotonated 2-EEMPA)∙∙∙3CO2∙∙∙3CH2], and m/z+ 373 C16H25N2O8+ [(protonated 2-EEMPA)∙∙∙3CO2∙∙∙2C]. However, the monomer of 2-EEMPA and CO2 seems to be most prevalent. Furthermore, solvent clusters are detected in loaded solvents, for instance m/z+ 433 C22H49N4O4+ [(2-EEMPA)2∙∙∙H] and m/z+ 646 [(2-EEMPA)3-2H], while capturing CO2 at different amounts. Relative abundance of cluster ions provides a semi-qualitative venue to assess the free energies of gas capture energetics, indicating the relative stability trend within the same solvent system, previously impossible. These observed ion clusters are verified with molecular modeling, where dimer, trimer, and cluster ions are validated for their presence either due to weak molecular interactions or hydrogen bonds. In situ molecular imaging of ionic liquids and molecular modeling reveals that the acid gas capture mechanism by ionic liquids includes both physical adsorption and chemical bonding with multiple reaction pathways, engaging cluster formation and alteration of solvent structures.« less

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directlymore » or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.« less

Understanding the quantitative interactions among zeolite pore walls, Bro̷nsted acid sites, and molecules with both polar and nonpolar regions is essential for scoping out the potential of zeolites as sorbents and catalysts. Purely siliceous zeolites (MFI and Beta in the present study) are hydrophobic, whereas those containing aluminum are considered hydrophilic, preferentially adsorbing organic molecules even in aqueous environments. To characterize these interactions, we use primary alcohols of increasing molecular weight, quantifying their specific interactions in the confined pore space of the alkyl (CH_x) and OH groups. Three types of interactions were identified: (i) alkyl CH_x groups interacting with themore » zeolite pore walls (approximately 10 kJ mol⁻¹ per carbon), (ii) alcohol OH groups interacting with the pore walls (30−35 kJ mol⁻¹), and (iii) alcohol OH groups interacting with Bro̷nsted acid sites (37 kJ mol⁻¹). All three interactions were well mirrored by computational simulations. The contribution of the alkyl CH_x groups was inferred from the incremental increase in sorption enthalpy with increasing molecular weight; the interaction strength of the OH groups was determined by extrapolating the global adsorption enthalpy of the alcohols to a hypothetical OH group without an alkyl group. This value was identical to the adsorption enthalpy of water. The experiments demonstrated that only water has an adsorption enthalpy on zeolite pore walls lower than its condensation enthalpy (30−35 kJ mol⁻¹ vs 45 kJ mol⁻¹), limiting the concentration of water that can be adsorbed.« less

Molecular-level insights into reactive separations are crucial for the design of new conversion pathways of carbon dioxide (CO₂). This work explores a postulated pathway that directs CO₂ to undergo inverse-electron-demand Diels–Alder reactions to produce heterocycles using the CO₂ chemically fixed on water-lean solvent molecules. Density functional theory calculations are applied to evaluate the lowest unoccupied molecular orbital (LUMO) energies of three types of reactants (1,3-butadiene, 1,3-cyclohexadiene, and 1,2,4,5-tetrazine) with various functional substituents. These calculations also provide a data set (5.8k data) for developing a machine learning model to efficiently predict LUMO energies. A computational screening of LUMO energies for anmore » additional 47k diene and tetrazine candidates is performed, and a list of candidates with lowered LUMO energies by electron-withdrawing substituents is provided. These candidates are further examined by their reaction energy barriers computed from the interatomic potential or density functional theory. Two major energy barriers are identified, one for the proton transfer within the water-lean solvent and the other for the CO₂ transfer from the solvent molecule to the reactant candidate (diene or tetrazine). The functional substituents have a more significant impact on the second barrier but a very slight one on the first barrier. This exploratory work demonstrates a new possibility for guiding experimental efforts toward the chemical conversion of fixated CO₂ to value-added compounds.« less

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO₃)₃ dissolved in acetonitrile with a terpyridine ligand (terpyNO₂), and Nd(NO₃)₃ dissolvedmore » in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO₃)₃(terpyNO₂) and Nd(NO₃)(acetonitrile)₃, with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.« less

Membrane separation for 2,3-butanediol (2,3-BDO) recovery from fermentation broth is highly valued for sustainable and renewable processes, but it requires efficient membrane materials. Here, this work evaluates the sulfonated polybenzimidazole (sPBI) and its graphene oxide (GO) doped composite membrane for separating 2,3-BDO and water via atomistic simulations. Density functional theory calculations are applied to identify various forms of sPBI structures and quantify their binding interactions with 2,3-BDO and water. Classical molecular dynamic simulations are used to evaluate the structural changes, diffusivity, and selectivity of 2,3-BDO and water in different sPBI models, GO surfaces, and GO-doped sPBI composite models. Our resultsmore » suggest that sPBI slightly increases the crystallinity of the membrane structures, enhances the adsorption strength for both 2,3-BDO and water, and improves the water/2,3-BDO selectivity by 2–3 times. The GO surfaces display a maximum selectivity at a surface coverage of 0.1–0.15 for both hydroxyl and epoxy surface groups. The addition of GO flakes to sPBI creates new interaction sites for 2,3-BDO and water at the interface of sPBI and GO, and the water/2,3-BDO selectivity of GO-doped sPBI models is further increased up to 3 times. This work illustrates how the integrated addition of sPBI and GO flakes offers a promising approach to selective separation of 2,3-BDO and water, providing theoretical guidance for polybenzimidazole-based membranes in the potential application of 2,3-BDO recovery.« less

Nitrogen oxides, present in flue gas, can cause negative impacts on amine carbon capture solvents by the formation of heat-stable salts and suspected carcinogens. Thus, to maximize the performance of water-lean solvents, a better understanding of this process in these systems is necessary. Here, a computational study for the fixation of the CO₂ capture solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (EEMPA) to nitramine/nitrosamine was conducted. The first step involves the dissociation of the NH bond of EEMPA, in which the homolytic mechanism is energetically more favorable than the heterolytic mechanism. The second step involves radical recombination to form N–N bonds. While NO₂ directly reactsmore » with EEMPA, NO has almost no effect. However, in the presence of O₂, fixation of EEMPA by NO is enhanced via the formation of N₂O₄ species. Finally, low reaction energies indicate that the formation of nitramine/nitrosamine may be a reversible process, suggesting that EEMPA could be recovered under thermal stripping conditions.« less

Catalysis informatics has received tremendous attention in recent years as a tool to design catalysts and discover unique descriptors that capture the relationships between chemical properties and catalytic performance. One of the stop-gaps in understanding catalytic effects, which is often ignored and limits the deployment of data science tools, relates to the lack of uniform data. The catalytic cleavage of C–X (X= H, C, N, and O) bonds is relevant to many fundamental catalytic processes. In this Perspective, we performed data analytics on four groups of C–X cleavage reactions that are common in production, upcycling, or reactive separation: the C–Cmore » cleavage in cyclopropyl alcohol, the C–H cleavage in hydroacylation reactions, the C–O cleavage in β-O-4 linkages, and the C–N cleavage in amides, using experimental data collected from the literature to understand their underlying correlations. Experimental variables of high impact are identified for each reaction by dimensionality reduction methods. We highlight the urgent need for experimental data sets that include full details on the reaction conditions, such as reagent concentration, reaction temperature, or time in machine-readable forms. We discuss the potential improvement of the data of these reactions and promising approaches such as autonomous experiments to fill the gaps in unbiased experimental data. Finally, we also address the early stage consideration of separation aspects in the experimental design of efficient catalytic systems for these fundamental examples of chemical reactivity.« less

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. Here, we discuss two approaches for this: developing carbon alternatives and improving our ability tomore » reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.« less

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl₃ mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl₃) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determinemore » structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl₃ content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu³⁺ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu³⁺ intermolecular structure is observed within the 36 mol% PuCl₃ mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu³⁺ is significantly lower than that of Na⁺ and Cl^-.« less