Achieving Predictive Description of Negative Differential Resistance in Molecular Junctions Using a Range-Separated Hybrid Functional
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Capturing carbon dioxide (CO2) from post-combustion gas streams is an energy-intensive process that is required prior to either converting or sequestering CO2. There are a few commercial offerings of 1st and 2nd generation aqueous amine technologies, however the cost of capturing CO2 with these technologies remains high. To decrease costs of capture, researchers are designing efficient solvent systems with the goal of being drop-in replacements for 1st and 2nd generation infrastructure. One approach has seen the development of water-lean solvents that aim to increase efficiency by reducing the water content in solution. Water-lean solvents such as GE’s GAP/TEG are promising technologies, with potential to halve the parasitic load to a coal-fired power plant, only if the intrinsically high solution viscosities and hydrolysis of the siloxane moieties could be mitigated. We present here, an integrated multidisciplinary approach to overhaul the GAP/TEG solvent system at the molecular level to mitigate hydrolysis while also reducing viscosity. We present molecular-level insights into chemical speciation of CO2-containing ions, showing that co-solvents and diluents have a negligible effect on reducing viscosity and are not needed. This finding allowed for the design of singlecomponent siloxane-free diamine derivatives with site-specific incorporation of selective chemical moieties for direct placement and orientation of hydrogen bonding to reduce viscosity. Ultimately, we present new single-component diamine formulations less susceptible to hydrolysis that exhibit up to a 98% reduction in viscosity compared to the initial GAP/TEG formulation.
Rare earth elements (REEs) are critical for advanced technologies, yet in hydrothermal aqueous solutions the molecular level details of their interaction with ligands that control their geochemical transport and deposition remain poorly understood. Here, this study elucidates the coordination behavior of Yb 3+ in sulfate-rich hydrothermal fluids using in situ extended X-ray absorption fine structure (EXAFS) spectroscopy and ab initio molecular dynamics (AIMD) simulations. By integrating multi-angle EXAFS with AIMD-derived constraints, we precisely resolve Yb 3+ coordination structures and ligand interactions under hydrothermal conditions. At room temperature, Yb 3+ is coordinated by five water molecules and two sulfate ligands (coordination number, CN = 8), forming a distorted square antiprism geometry. Increasing temperature induces progressive dehydration, reducing the hydration shell and favoring stronger sulfate complexation. At 200°C, sulfate ligands reorganize around Yb 3+ , shifting its geometry to a capped octahedron (CN = 7). At 300 °C, sulfate binding dominates, leading to structural reorganization that parallels the onset of sulfate mineral precipitation, consistent with the retrograde solubility of REE sulfates. These findings provide direct molecular-scale evidence that sulfate acts as both a transport and deposition ligand, critically influencing REE mobility in geochemical environments. Our results can also help to refine thermodynamic models of REE speciation in high-temperature hydrothermal fluids and improve our understanding of REE ore formation processes in nature.
The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.
Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.
In this work, polymer-grafted nanoparticle (PGN) films were prepared from polystyrene (PS) grafted to rodlike cellulose nanocrystals (MxG-CNC-g-PS) with a controllable grafting density (0.03–0.25 chains/nm 2 ) and molecular weight (5–60 kg/mol). These nanorod-based PGNs are solution- and melt-processible, permitting access to one-component composite films with high nanofiller loadings (with up to 55 wt %). The impact of both grafted polymer density and molecular weight on the mechanical properties of the films was investigated and related to the polymer brush conformation: concentrated polymer brush (CPB), semidilute polymer brush (SDPB), or CPB core with SDPB corona (CPB/SDPB). The rubbery regime storage modulus (above $T_g$) showed 2 orders of magnitude increase, maximizing at a low degree of polymerization (N) and low grafting density (σ). Fracture toughness was maximized in samples with the grafted polymer in the SDPB or CPD/SDPB (higher N and relatively low σ) regime and showed enhancement relative to PS of molecular weight similar to the graft. In line with prior computation predictions, optimizing for both rubbery modulus and fracture toughness in such nanorod-based PGN films requires the polymers in the SDPB regime and CNC loading levels (ca. 50–60 wt %) that are difficult to attain in more traditional two-component CNC composites.
Carbon electrodes are ideal for electrochemistry with molecular catalysts, exhibiting facile charge transfer and good stability. Yet for solar-driven catalysis with semiconductor light absorbers, stable semiconductor/carbon interfaces can be difficult to achieve, and carbon’s high optical extinction means it can only be used in ultrathin layers. Here, we demonstrate a plasma-enhanced chemical vapor deposition process that achieves well-controlled deposition of out-of-plane “fuzzy” graphene (FG) on thermally oxidized Si substrates. The resulting Si|FG interfaces possess a silicon oxycarbide (SiOC) interfacial layer, implying covalent bonding between Si and the FG film that is consistent with the mechanical robustness observed from the films. The FG layer is uniform and tunable in thickness and optical transparency by deposition time. Using p-type Si|FG substrates, noncovalent immobilization of cobalt phthalocyanine (CoPc) molecular catalysts was employed for the photoelectrochemical reduction of CO 2 in aqueous solution. The Si|FG|CoPc photocathodes exhibited good catalytic activity, yielding a current density of ∼1 mA/cm 2 , Faradaic efficiency for CO of ∼70% (balance H 2 ), and stable photocurrent for at least 30 h at −1.5 V vs Ag/AgCl under 1-sun illumination. Furthermore, the results suggest that plasma-deposited FG is a robust carbon electrode for molecular catalysts and suitable for further development of aqueous-stable Si photocathodes for CO 2 reduction.
Molecular catalysts, such as metalated porphyrins, are attractive cocatalysts for photocatalytic water splitting owing to their potential to simultaneously catalyze target reactions at their metal center, extend charge-separated-state lifetimes, and accumulate the requisite charge for product formation. However, porphyrin catalysts, like most molecular catalysts, are often limited by poor stability associated with demetalation, inactivation by undesired bonding (e.g., O2 coordination/redox/dimerization), and detachment from electrode supports or semiconducting photoabsorbers. In this study, nanoscopic titanium dioxide (TiO2) overlayers, deposited by atomic layer deposition (ALD), are demonstrated to encapsulate cobalt(III) meso-tetra(4-carboxyphenyl) porphyrin chloride (CoTCPP) molecular catalysts and thereby improve their adhesion to electrode surfaces over a wide range of electrode potentials spanning from -1.0 V vs RHE to +1.8 V vs RHE. Through analysis of Raman and ultraviolet-visible spectroscopy, it was confirmed that the metalloporphyrin structure was maintained when the surface-bound CoTCPP was encapsulated by 10 - 250 ALD cycles (~2 - 18 nm thick) of TiO2. Additional characterization of CoTCPP catalysts before and after electrochemical measurements reveals that up to 97% of the encapsulated CoTCPP remains tethered to the electrode surface after chronoamperometry tests under hydrogen evolution reaction (HER) conditions, compared to <36% for unencapsulated CoTCPP. This study also shows that encapsulated CoTCPP molecules remain partially redox active for overlayers up to 8 nm, which can also attenuate undesired redox mediator back reactions like ferricyanide reduction.
Recent developments in “water-in-salt” electrolytes have precipitated a renewed effort to study imide-based electrolytes. While previous small-/wide-angle X-ray scattering (SAXS/WAXS) studies have attributed the emergence of a low-Q peak in the SAXS profile of aqueous LiTFSI electrolytes to nanometer-scale anion clustering, a molecular-level understanding of the root of these clusters remains unclear. Here, in this study, we combined molecular dynamics simulations and SAXS/WAXS to study the solvation structures of LiTFSI in acetonitrile, methanol, and water. We concluded that hydrogen bonding in water and MeOH stabilizes anion clusters, while nonpolar methyl groups on methanol and acetonitrile interrupt the nanoscale ordering of TFSI anions. This causes LiTFSI in water and MeOH electrolytes to exhibit two low-Q SAXS profile peaks while LiTFSI in acetonitrile exhibits only a single peak below Q = 1 Å –1 . These findings shed light on the underlying molecular origins of nanoscale anion clusters, which may help in the design of the next generation of electrolyte chemistries.
New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.
A novel multi-electrode glow discharge provides increased sensitivity and analytical flexibility for both atomic and molecular MS determinations.
Specific lipid and protein changes characterized term preeclampsia (PRE) and gestational diabetes mellitus (GDM) and novel visualization tools were created to aid in the process.
Here, we compare the structure of synthetic dust polarization with synthetic molecular line emission from radiative transfer calculations using a three-dimensional, turbulent collapsing-cloud magnetohydrodynamics simulation. The histogram of relative orientation (HRO) technique and the projected Rayleigh statistic (PRS) are considered. In our trans-Alfvénic (more strongly magnetized) simulation, there is a transition to perpendicular alignment at densities above ~4 × 10 3 cm –3 . This transition is recovered in most of our synthetic observations of optically thin molecular tracers; however, for 12 CO it does not occur and the PRS remains in parallel alignment across the whole observer space. We calculate the physical depth of the optical depth τ = 1 surface and find that for 12 CO it is largely located in front of the cloud mid-plane, suggesting that 12 CO is too optically thick and instead mainly probes low-volume density gas. In our super-Alfvénic simulation, the magnetic field becomes significantly more tangled, and all observed tracers tend towards no preference for perpendicular or parallel alignment. An observable difference in alignment between optically thin and optically thick tracers may indicate the presence of a dynamically important magnetic field, though there is some degeneracy with viewing angle. We convolve our data with a Gaussian beam and compare it with HRO results of the Vela C molecular cloud. We find good agreement between these results and our sub-Alfvénic simulations when viewed with the magnetic field in the plane of the sky (especially when sensitivity limitations are considered), though the observations are also consistent with an intermediately inclined magnetic field.
Here, Feynman path-integral deep potential molecular dynamics (PI-DPMD) calculations have been employed to study both light (H 2 O) and heavy water (D 2 O) within the isothermalisobaric ensemble. In particular, the deep neural network is trained based on ab initio data obtained from the strongly constrained and appropriately normed (SCAN) exchange-correlation functional. Because of the lighter mass of hydrogen than deuteron, the properties of light water are more influenced by nuclear quantum effect than those of heavy water. Clear isotope effects are observed and analyzed in terms of hydrogen-bond structure and electronic properties of water that are closely associated with experimental observables. The molecular structures of both liquid H 2 O and D 2 O agree well with the data extracted from scattering experiments. The delicate isotope effects on radial distribution functions and angular distribution functions are well reproduced as well. Our approach demonstrates that deep neural network combined with SCAN functional based ab initio molecular dynamics provides an accurate theoretical tool for modeling water and its isotope effects.
Techniques of analysis which allow estimates of kinetic temperature, gas density, gas cooling rate, and dust cooling rate are applied to the S140 molecular cloud. Maps of this cloud in various molecular lines are examined which reveal the existence of a strong temperature and density peak near the H-alpha rim and the presence of a strong near-IR source very near that peak. This source is found to have an energy distribution which is very similar to that of the Becklin-Neugebauer object, including the silicate feature at 9.5 microns. The heating and cooling rates for the gas and dust in S140 are estimated, and the predicted cooling rate for dust is shown to be much greater than that for gas. The molecular-line observations are compared with a spherical large-velocity-gradient trapping calculation. An optimum cloud model is developed which indicates that: (1) (C-13)O, HCO(+), and H2CO are about 10 times less abundant in S140 than in dark clouds; (2) the HCN abundance is approximately 4 times the H2CO abundance in S140, compared with roughly equal values in dark clouds; and (3) the (C-13)O/C(O-18) ratio is consistent with terrestrial isotope ratios.
The molecular cloud associated with the S235 H II region has been studied by means of molecular lines and near-infrared observations. The cloud consists of two components, one of which partly surrounds the S235 H II region. The other component contains a dense, hot region of active star formation, marked by self-reversed CO profiles, compact H II regions, masers, and infrared sources. From the molecular line data, the size and mass of the two components are estimated to be 6-8 pc and 3000-4000 solar masses. More detailed studies near the region of active star formation yield estimates of density (approximately 200,000-500,000/cu cm) and the abundances of H2CO, HCO(+), HCN, and (C-13)O. Analysis of the energetics suggests that the cloud is heated by the exciting star of S235 and by the exciting stars of the compact H II regions. Assuming that the gas is heated by collisions with warm dust grains, the far-infrared luminosity has been predicted. The observations of far-infrared emission are in reasonable agreement with predictions.
Work directed toward understanding the high pressure properties of molecular solids and molecular surfaces deposited on hetrogeneous substrates is reported. The motivation, apart from expanding our basic knowledge about these systems, was to understand and predict the properties of new materials synthesized at high pressure, including pressure induced metallic and superconducting states. As a consequence, information about the states of matter of the Jovian planets and their satellites, which are natural high pressure laboratories was also provided. The work on molecular surfaces and finite two and three dimensional clusters of atoms and molecules was connected with the composition and behavior of planetary atmospheres and on the processes involved in forming surface layers, which is vital to the development of composite materials and microcircuitry.