Energy Sciences

Cryogenic transmission electron microscopy (cryo-TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA-reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo-TEM 3D reconstructions of self-assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. These findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

Nanoparticle-mediated mRNA delivery has emerged as a promising therapeutic modality, but its growth is still limited by the discovery and optimization of effective and well-tolerated delivery strategies. Lipid nanoparticles containing charged or ionizable lipids are an emerging standard for in vivo mRNA delivery, so creating facile, tunable strategies to synthesize these key lipid-like molecules is essential to advance the field. Here, we generate a library of N-substituted glycine oligomers, peptoids, and undertake a multistage down-selection process to identify lead candidate peptoids as the ionizable component in our Nutshell nanoparticle platform. First, we identify a promising peptoid structural motif by clustering a library of >200 molecules based on predicted physical properties and evaluate members of each cluster for reporter gene expression in vivo. Then, the lead peptoid motif is optimized using design of experiments methodology to explore variations on the charged and lipophilic portions of the peptoid, facilitating the discovery of trends between structural elements and nanoparticle properties. We further demonstrate that peptoid-based Nutshells leads to expression of therapeutically relevant levels of an anti-respiratory syncytial virus antibody in mice with minimal tolerability concerns or induced immune responses compared to benchmark ionizable lipid, DLin-MC3-DMA. Through this work, we present peptoid-based nanoparticles as a tunable delivery platform that can be optimized toward a range of therapeutic programs.

α-Phenylthioaldehydes are readily prepared using a simple multi-step procedure and herein are introduced as a new precursor for the NHC-catalysed generation of acyl azolium and azolium enolate intermediates that are of widespread synthetic interest and utility. Treatment of α-phenylthioaldehydes with an NHC precatalyst and base produces an efficient redox rearrangement via a Breslow intermediate, elimination of thiophenolate, and subsequent rebound addition to the generated acyl azolium to give the corresponding thiol ester. In the presence of an external alcohol, competition between redox rearrangement and redox esterification can be controlled through judicious choice of the N-aryl substituent within the NHC precatalyst and the base used in the reaction. With NEt₃ as base, NHCs bearing electron-withdrawing (N-C₆F₅ or N-C₆H₂Cl₃) substituents favour redox rearrangement, while triazolium precatalysts with electron-rich N-aryl substituents (N-Ph, N-Mes) result in preferential redox esterification. Using DBU, redox esterification is preferred due to transesterification of the initially formed thiol ester product. Additionally, α-phenylthioaldehyde-derived azolium enolates have been used in enantioselective formal [4 + 2]-cycloaddition reactions to access dihydropyridinone heterocycles with high enantioselectivity (up to >95 : 5 dr, 98 : 2 er).

Disordered rocksalt oxide (DRX) cathodes are promising candidates for next-generation Co- and Ni-free Li-ion batteries. While fluorine substitution for oxygen has been explored as an avenue to enhance their performance, the amount of fluorine incorporated into the DRX structure is particularly challenging to quantify and impedes our ability to relate fluorination to electrochemical performance. Herein, an experimental-computational method combining ⁷Li and ¹⁹F solid-state nuclear magnetic resonance, and ab initio cluster expansion Monte Carlo simulations, is developed to determine the composition of DRX oxyfluorides. Using this method, the synthesis of Mn- and Ti-containing DRX via standard high temperature sintering and microwave heating is optimized. Further, the upper fluorination limit attainable using each of these two synthesis routes is established for various Mn-rich DRX compounds. A comparison of their electrochemical performance reveals that the capacity and capacity retention mostly depend on the Mn content, while fluorination plays a secondary role.

During Li-ion battery operation, (electro)chemical side reactions occur within the cell that can promote or degrade performance. These complex reactions produce byproducts in the solid, liquid, and gas phases. Studying byproducts in these three phases can help optimize battery lifetimes. To relate the measured gas-phase byproducts to species dissolved in the liquid-phase, equilibrium proprieties such as the Henry's law constants are required. The present work implements a pressure decay experiment to determine the thermodynamic equilibrium concentrations between the gas and liquid phases for ethylene (C₂H₄) and carbon dioxide (CO₂), which are two gases commonly produced in Li-ion batteries, with an electrolyte of 1.2 M LiPF₆ in 3:7 wt/wt ethylene carbonate/ethyl methyl carbonate and 3 wt % fluoroethylene carbonate (15:25:57:3 wt % total composition). The experimentally measured pressure decay curve is fit to an analytical dissolution model and extrapolated to predict the final pressure at equilibrium. The relationship between the partial pressures and concentration of dissolved gas in electrolyte at equilibrium is then used to determine Henry's law constants of 2.0 × 10⁴ kPa for C₂H₄ and k _CO2 = 1.1 × 10⁴ kPa for CO₂. These values are compared to Henry's law constants predicted from density functional theory and show good agreement within a factor of 3.

The aqueous uranyl dication has long been known to facilitate the UV light-induced decomposition of aqueous VOCs (volatile organic compounds), via the long-lived highly efficient, uranyl excited state. The lower-energy visible light excited uranyl ion is also able to cleave unactivated hydrocarbon C-H bonds, yet the development of this reactivity into controlled and catalytic C-H bond functionalization is still in its infancy, with almost all studies still focused on uranyl nitrate as the precatalyst. Here, hydrocarbon-soluble uranyl nitrate and chloride complexes supported by substituted phenanthroline (Ph₂phen) ligands are compared to each other, and to the parent salts, as photocatalysts for the functionalization of cyclooctane by H atom abstraction. Analysis of the absorption and emission spectra, and emission lifetimes of Ph₂phen-coordinated uranyl complexes demonstrate the utility of the ligand in light absorption in the photocatalysis, which is related to the energy and kinetic decay profile of the uranyl photoexcited state. Density functional theory computational analysis of the C-H activation steps in the reaction show how a set of dispersion forces between the hydrocarbon substrate and the Ph₂phen ligand provide control over the H atom abstraction, and provide predictions of selectivity of H atom abstraction by the uranyl oxo of the ring C-H over the ethyl C-H in an ethylcyclohexane substrate.

Mineral-polymer composites found in nature exhibit exceptional structural properties essential to their function, and transferring these attributes to the synthetic design of functional materials holds promise across various sectors. Biomimetic fabrication of nanocomposites introduces new pathways for advanced material design and explores biomineralization strategies. This study presents a novel approach for producing single platelet nanocomposites composed of CaCO₃ and biomimetic peptoid (N-substituted glycines) polymers, akin to the bricks found in the brick-and-mortar structure of nacre, the inner layer of certain mollusc shells. The significant aspect of the proposed strategy is the use of organic peptoid nanosheets as the scaffolds for brick formation, along with their controlled mineralization in solution. Here, we employ the B28 peptoid nanosheet as a scaffold, which readily forms free-floating zwitterionic bilayers in aqueous solution. The peptoid nanosheets were mineralized under consistent initial conditions (σ_calcite = 1.2, pH 9.00), with variations in mixing conditions and supersaturation profiles over time aimed at controlling the final product. Nanosheets were mineralized in both feedback control experiments, where supersaturation was continuously replenished by titrant addition and in batch experiments without a feedback loop. Complete coverage of the nanosheet surface by amorphous calcium carbonate was achieved under specific conditions with feedback control mineralization, whereas vaterite was the primary CaCO₃ phase observed after batch experiments. Thermodynamic calculations suggest that time-dependent supersaturation profiles as well as the spatial distribution of supersaturation are effective controls for tuning the mineralization extent and product. We anticipate that the control strategies outlined in this work can serve as a foundation for the advanced and scalable fabrication of nanocomposites as building blocks for nacre-mimetic and functional materials.

All solid-state batteries (SSBs) are considered the most promising path to enabling higher energy-density portable energy, while concurrently improving safety as compared to current liquid electrolyte solutions. However, the desire for high energy necessitates the choice of high-voltage cathodes, such as nickel-rich layered oxides, where degradation phenomena related to oxygen loss and structural densification at the cathode surface are known to significantly compromise the cycle and thermal stability. In this work, we show, for the first time, that even in an SSB, and when protected by an intact amorphous coating, the LiNi_0.5Mn_0.3Co_0.2O₂ (NMC⁵³²) surface transforms from a layered structure into a rocksalt-like structure after electrochemical cycling. The transformation of the surface structure of the Li₃B₁₁O₁₈ (LBO)-coated NMC⁵³² cathode in a thiophosphate-based solid-state cell is characterized by high-resolution complementary electron microscopy techniques and electron energy loss spectroscopy. Ab initio molecular dynamics corroborate facile transport of O^2- in the LBO coating and in other typical coating materials. This work identifies that oxygen loss remains a formidable challenge and barrier to long-cycle life high-energy storage, even in SSBs with durable, amorphous cathode coatings, and directs attention to considering oxygen permeability as an important new design criteria for coating materials.

The ability to control and manipulate semiconductor/bio interfaces is essential to enable biological nanofabrication pathways and bioelectronic devices. Traditional surface functionalization methods, such as self-assembled monolayers (SAMs), provide limited customization for these interfaces. Polymer brushes offer a wider range of chemistries, but choices that maintain compatibility with both lithographic patterning and biological systems are scarce. Here, we developed a class of bioinspired, sequence-defined polymers, i.e., polypeptoids, as tailored polymer brushes for surface modification of semiconductor substrates. Polypeptoids featuring a terminal hydroxyl (-OH) group are designed and synthesized for efficient melt grafting onto the native oxide layer of Si substrates, forming ultrathin (∼1 nm) monolayers. By programming monomer chemistry, our polypeptoid brush platform offers versatile surface modification, including adjustments to surface energy, passivation, preferential biomolecule attachment, and specific biomolecule binding. Importantly, the polypeptoid brush monolayers remain compatible with electron-beam lithographic patterning and retain their chemical characteristics even under harsh lithographic conditions. Electron-beam lithography is used over polypeptoid brushes to generate highly precise, binary nanoscale patterns with localized functionality for the selective immobilization (or passivation) of biomacromolecules, such as DNA origami or streptavidin, onto addressable arrays. This surface modification strategy with bioinspired, sequence-defined polypeptoid brushes enables monomer-level control over surface properties with a large parameter space of monomer chemistry and sequence and therefore is a highly versatile platform to precisely engineer semiconductor/bio interfaces for bioelectronics applications.

Activation barriers of elementary reactions are essential to predict molecular reaction mechanisms and kinetics. However, computing these energy barriers by identifying transition states with electronic structure methods (e.g., density functional theory) can be time-consuming and computationally expensive. In this work, we introduce CoeffNet, an equivariant graph neural network that predicts activation barriers using coefficients of any frontier molecular orbital (such as the highest occupied molecular orbital) of reactant and product complexes as graph node features. We show that using coefficients as features offer several advantages, such as chemical interpretability and physical constraints on the network's behaviour and numerical range. Model outputs are either activation barriers or coefficients of the chosen molecular orbital of the transition state; the latter quantity allows us to interpret the results of the neural network through chemical intuition. We test CoeffNet on a dataset of S_N2 reactions as a proof-of-concept and show that the activation barriers are predicted with a mean absolute error of less than 0.025 eV. The highest occupied molecular orbital of the transition state is visualized and the distribution of the orbital densities of the transition states is described for a few prototype S_N2 reactions.