Molecular Scale Research Articles

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 CO2 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. 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.

An adaptive biomolecular condensation response is conserved across environmentally divergent species

Cells must sense and respond to sudden maladaptive environmental changes—stresses—to survive and thrive. Across eukaryotes, stresses such as heat shock trigger conserved responses: growth arrest, a specific transcriptional response, and biomolecular condensation of protein and mRNA into structures known as stress granules under severe stress. The composition, formation mechanism, adaptive significance, and even evolutionary conservation of these condensed structures remain enigmatic. Here we provide a remarkable view into stress-triggered condensation, its evolutionary conservation and tuning, and its integration into other well-studied aspects of the stress response. Using three morphologically near-identical budding yeast species adapted to different thermal environments and diverged by up to 100 million years, we show that proteome-scale biomolecular condensation is tuned to species-specific thermal niches, closely tracking corresponding growth and transcriptional responses. In each species, poly(A)-binding protein—a core marker of stress granules—condenses in isolation at species-specific temperatures, with conserved molecular features and conformational changes modulating condensation. From the ecological to the molecular scale, our results reveal previously unappreciated levels of evolutionary selection in the eukaryotic stress response, while establishing a rich, tractable system for further inquiry.

Investigation of Conductance and Capacitance of Mesoscopic and Molecular Scale Systems

Investigation of Conductance and Capacitance of Mesoscopic and Molecular Scale Systems

Molecular Mechanisms of Sorbed Ion Effects during Boehmite Particle Aggregation.

Classical theories of particle aggregation, such as Derjaguin-Landau-Verwey-Overbeek (DLVO), do not explain recent observations of ion-specific effects or the complex concentration dependence for aggregation. Thus, here, we probe the molecular mechanisms by which selected alkali nitrate ions (Na+, K+, and NO3-) influence aggregation of the mineral boehmite (γ-AlOOH) nanoparticles. Nanoparticle aggregation was analyzed using classical molecular dynamics (CMD) simulations coupled with the metadynamics rare event approach for stoichiometric surface terminations of two boehmite crystal faces. Calculated free energy landscapes reveal how electrolyte ions alter aggregation on different crystal faces relative to pure water. Consistent with experimental observations, we find that adding an electrolyte significantly reduces the energy barrier for particle aggregation (∼3-4×). However, in this work, we show this is due to the ions disrupting interstitial water networks, and that aggregation between stoichiometric (010) basal-basal surfaces is more favorable than between (001) edge-edge surfaces (∼5-6×) due to the higher interfacial water densities on edge surfaces. The interfacial distances in the interlayer between aggregated particles with electrolytes (∼5-10 Å) are larger than those in pure water (a few Ångströms). Together, aggregation/disaggregation in salt solutions is predicted to be more reversible due to these lower energy barriers, but there is uncertainty on the magnitudes of the energies that lead to aggregation at the molecular scale. By analyzing the peak water densities of the first monolayer of interstitial water as a proxy for solvent ordering, we find that the extent of solvent ordering likely determines the structures of aggregated states as well as the energy barriers to move between them. The results suggest a path for developing a molecular-level basis to predict the synergies between ions and crystal faces that facilitate aggregation under given solution conditions. Such fundamental understanding could be applied extensively to the aggregation and precipitation utilization in the biological, pharmaceutical, materials design, environmental remediation, and geological regimes.

Microfluidic-oriented green synthesis of pepsin-doped gold nanoparticles for colorimetric and photothermal dual-readout detection of food hazards

Gold nanoparticles (AuNPs)-based immunochromatographic assay has gained popularity as a rapid detection method for food hazards. Synthesizing highly stable AuNPs in a rapid, simple and environmentally friendly manner is a key focus in this field. Here, we present a green microfluidic strategy for the rapid, automated, and size-controllable synthesis of pepsin-doped AuNPs (AuNPs@Pep) by employing glucose-pepsin as a versatile reducing agent and stabilizer. Through combining the colorimetric and photothermal (PoT) properties of AuNPs@Pep, both “signal-off” and “signal-on” formats of microfluidic paper analytical devices (PADs) were developed for detection of a small molecule antibiotic, florfenicol, and an egg allergen, ovalbumin. Compared to the colorimetric mode, a 4-fold and 3-fold improvement in limit of detection was observed in the “signal-off” detection of florfenicol and the “signal-on” detection of ovalbumin, respectively. The results demonstrated the practicality of AuNPs@Pep as a colorimetric/PoT dual-readout probe for immunochromatographic detection of food hazards at different molecular scales.

Diffusion calculations on reconstructed bentonite microstructures with anion exclusion effects.

Due to their prevalence in the lithosphere and their high capability of sorbing pollutants, smectite clays play a foreground role in environmental pollution studies, waste management, and soil science. In complementarity with existing approaches at the molecular or macroscopic scales, real microstructures have been employed to investigate ionic transport by diffusion through montmorillonite and water-saturated Wyoming bentonite at intermediate scales ranging between the nanometer and the micrometer. The coupled solute transport and electrostatic phenomena investigated at the nanopore scale are upscaled using the homogenization of porous media approach. Homogenization computations rely on a hierarchical description of bentonite that acknowledges the existence of pores networks at different scales. At the scale of montmorillonite layers, digitized TEM images have been employed to simulate the diffusion of ionic solutes by considering electrostatic interactions in the vicinity of the negatively charged clay platelets' surface. Finite element microstructures are created after extraction of the contours of the layers using dedicated image processing algorithms. Local electric potential distribution, anion exclusion, and cation inclusion are displayed by ion distribution maps. The effective diffusion tensor and the transport equation obtained through volume averaging are then used to simulate diffusion at the scale of a Wyoming bentonite sample composed of clay gels of variable density, solid grains, and micropores. Qualitative comparisons were made with existing diffusion data, and a particular attention is given to the anisotropy of the diffusion tensors at both the mesoscopic and macroscopic scales.

Edge effects in quantum cellular automata binary wire

The molecular quantum cellular automata approach provides a paradigm for molecular electronics, where the charge configurations at reduction–oxidation centers of molecules represent binary information. The QCA cells are coupled by electrostatic fields and enable implementing devices for digital data transmission and logic operation at the molecular scale. Designing inputs for the desired operation of molecular QCA devices has been a challenging task, where the edge effects of electrodes may reduce the reliability of the QCA devices. We calculate the fringing fields of a pair of electrodes implemented on a model platform for the operation of a molecular QCA binary wire. The calculated nanogap and fringing fields are used in a simple quantum mechanical model to analyze the edge effects on the polarization propagation and polarization loss throughout the wire. Discussions on the stability of the wire in the presence of the fringing fields using the excited state of the wire and polarization uncertainties are presented.

Genetic control of MRI contrast using the manganese transporter Zip14.

Gene-expression reporter systems, such as green fluorescent protein, have been instrumental to understanding biological processes in living organisms at organ system, tissue, cell, and molecular scales. More than 30 years of work on developing MRI-visible gene-expression reporter systems has resulted in a variety of clever application-specific methods. However, these techniques have not yet been widely adopted, so a general-purpose expression reporter is still required. Here, we demonstrate that the manganese ion transporter Zip14 is an in vivo MRI-visible, flexible, and robust gene-expression reporter to meet this need. Plasmid constructs consisting of a cell type-specific promoter, gene coding for human Zip14, and a histology-visible tag were packaged into adeno-associated viruses. These viruses were intracranially injected into the mouse brain. Serial in vivo MRI was performed using a vendor-supplied 3D-MPRAGE sequence. No additional contrast agents were administered. Animals were sacrificed after the last imaging timepoint for immunohistological validation. Neuron-specific overexpression of Zip14 produced substantial and long-lasting changes in MRI contrast. Using appropriate viruses enabled both anterograde and retrograde neural tracing. Expression of Zip14 in astrocytes also enabled MRI of glia populations in the living mammalian brain. The flexibility of this system as an MRI-visible gene-expression reporter will enable many applications of serial, high-resolution imaging of gene expression for basic science and therapy development.

Molecular insight into the initial hydration of tricalcium aluminate

Portland cement (PC) is ubiquitously used in construction for centuries, yet the elucidation of its early-age hydration remains a challenge. Understanding the initial hydration progress of tricalcium aluminate (C3A) at molecular scale is thus crucial for tackling this challenge as it exhibits a proclivity for early-stage hydration and plays a pivotal role in structural build-up of cement colloids. Herein, we implement a series of ab-initio calculations to probe the intricate molecular interactions of C3A during its initial hydration process. The C3A surface exhibits remarkable chemical activity in promoting water dissociation, which in turn facilitates the gradual desorption of Ca ions through a metal-proton exchange reaction. The dissolution pathways and free energies of these Ca ions follow the ligand-exchange mechanism with multiple sequential reactions to form the ultimate products where Ca ions adopt fivefold or sixfold coordination. Finally, these Ca complexes reprecipitate on the remaining Al-rich layer through the interface-coupled dissolution-reprecipitation mechanism, demonstrating dynamically stable inner-sphere adsorption states. The above results are helpful in unmasking the early-age hydration of PC and advancing the rational design of cement-based materials through the bottom-up approach.

A zincophobic interface engineering achieving crystal-facet manipulation for ultra-long-life zinc-based flow batteries

Zinc-based flow batteries (ZFBs) have attracted considerable attention due to their high energy density, high safety, and low cost. However, the notorious dendrite problem is universally recognized as a bottleneck limiting the commercial application of ZFBs. This work proposes a zincophobic interface engineering strategy based on electrostatic repulsion to achieve uniform distribution of zincate ions along the membrane-electrode interface, where the carboxymethyl cellulose (CMC) is introduced for customized optimization of membrane surface charge. Such interface engineering successfully realizes crystal-facet manipulation that contributes to a 33.76% increase in the exposure of preferential crystallographic orientation ((002) plane), as evidenced by molecular scale characterization techniques, in-situ dynamic observation and density functional theory study. Moreover, the good wettability of hydrophilic CMC and the positive impact of its abundant –OH functional groups on the transport dynamics of charge carrier (OH−) synergistically enable the prepared membrane delivering high ion conductivity. Consequently, the battery employing the as-prepared membrane achieves stable operation for over 3000 cycles at 80 mA cm−2 with an average energy efficiency of ∼80%. This study provides a new solution for metal dendrite problem by crystal-facet manipulation, and so as to facilitate the commercialization of ZFBs in long-term energy storage.

Morphological analysis of mechanically recycled blends of high density polyethylene and polypropylene with strong difference in melt flow index

Polyolefin (PO) blends are difficult to separate due to density and chemical structure similarities. The associated waste treatment in the context of mechanical recycling is therefore complicated by the establishment of multi-phase morphologies that are not yet fully understood. In the present work, a high density polyethylene (HDPE) with a very high melt flow index (MFI) and a polypropylene (PP) with a very low MFI are deliberately mingled to better understand the full spectrum of morphological variations for PO blending. The linkage with the control over injection mold-based mechanical properties such as tensile strength, elasticity modulus, elongation at break, and impact strength is made. This is done supported by the connecting of experimental analyses at different scales, including (i) the molecular scale via size exclusion chromatography and Fourier transform infrared spectroscopy (FTIR), and (ii) the meso-scale via scanning electron and polarized light microscopy as well as differential scanning calorimetry, including a differentiation between the bulk and surface region. Emphasis is both on blends processed once and re-processed either once, twice or three times. For the single processing, it is demonstrated that in most cases a droplet morphology is obtained, with smaller droplets in case HDPE is the minor component and with a dominance of HDPE at the surface even for 60% PP, due to a better HDPE flowability. It is further shown that the scission of PP chains and crosslinking of HDPE chains respectively facilitates and inhibits crystallization, at least if meso-scale -mixing as more evident during re-processing is not taking over. It is also highlighted that the properties of PP can be enhanced by adding up to 10 wt% HDPE, acting as a filler, and that the (ideally) reprocessed blends remain suitable for application.

Slip topology of steady flows around a critical point: Taking the linear velocity field as an example

The flow of viscous fluids is considered as the aggregation of the motion of fluid particles when the fluid is conceived to be made up by an infinite number of particles. As an alternative of this conventional model, fluid motion could be understood as the slip of fluid layers with a molecular scale over each other, where the slip structures of fluid and their associated small-scale motion are characterized by an axial-vector-valued differential 1-form, called the vortex field. In this paper, in the case of steady flows we define the swirling degree of the velocity field at a point, and further the swirl field of the steady flow, to study the slip topology of fluid or the local streamline pattern around the critical point. The linear velocity field in the right real Schur form is used to carry out detailed analyses around the isolated critical point. Theoretical deduction and numerical test unveil the connection between the swirling degree and the swirl field, greatly make clear the topological property of slip structures of fluid in steady flows, especially in three-dimensional space.

Adsorption mechanism of Cs+ and Pb2+ on the N-A-S-H surface under the different Si/Al ratio and temperature

The application of low-calcium alkali-activated geopolymers has significantly enhanced the removal of Pb2+ and Cs+ from the contaminated soils and water. However, the adsorption mechanisms of Pb2+ and Cs+ influenced by the temperature and Si/Al at the molecular scale remain unclear, which were the two critical factors influencing the adsorption capacity. This study employed molecular dynamics simulation to elucidate the effects of temperature and Si/Al ratio on the adsorption mechanism and behavior of Pb2+ and Cs+ on the N-A-S-H surface. Research findings demonstrate that the adsorption of Pb2+ and Cs+ on the N-A-S-H surface is attributed to chemical adsorption. Increasing temperature can regulate the removal ratio of heavy metal ions by enhancing the quantity of cation exchange (correlation coefficient of 0.88). Temperature also influences the removal ratio by changing in adsorption energy, potential of mean force, and controlling the maximum adsorption capacity, hydration, and diffusion ability of the heavy metals (correlation coefficient of 0.67, 0.55, 0.6, and 0.57). While the Si/Al ratio influences the adsorption of heavy metals by enhancing the negative charge density of N-A-S-H gel and strengthening the interaction between heavy metals and oxygen atoms on the N-A-S-H surface (correlation coefficient of 0.96 and 0.52). Additionally, temperature exhibits a more pronounced effect on enhancing in the removal ratio of heavy metals. The heavy metal removal was maximally increased by 435 % (for Cs+) and 439 % (for Pb2+) via elevated temperature, while it was increased by 63 % (for Cs+) and 98 % (for Pb2+) via decreased Si/Al ratio. This study can not only provide a new perspective on the removal of heavy metals by N-A-S-H gel, but also can contribute to the achievement of green and sustainable development goals.

Density Functional Waltz: Molecular Theory of Spin Dynamics

Spin dynamics in molecular systems lies at the heart of contemporary research, promising revolutionary applications in fields like spintronics and quantum information processing. The paper provides insights into green techniques to improve spin dynamics for utilization in quantum computing and magnetic materials. This dynamic approach describes the temperature-dependent evolution of spin-lattice interactions. Snapshots acquired from various simulations enable additional DFT investigations, providing a more sophisticated understanding of spin dynamics under temperature variations. By seamlessly integrating theoretical insights with computational approaches, the Density Functional Waltz emerges as a potent paradigm for unraveling the mesmerizing choreography of spin dynamics at the molecular scale. This review analyzes the evolution of machine-learning approaches in the field of chemical sciences. The proposed review will highlight the significance of collaboration between quantum catalysis and the chemical physics community. There is an outline of the unique features of electron spin alongside the ingenious integration of macromolecules to control and fine-tune electron spin-based innovation

Resource allocation modeling for autonomous prediction of plant cell phenotypes

Predicting the plant cell response in complex environmental conditions is a challenge in plant biology. Here we developed a resource allocation model of cellular and molecular scale for the leaf photosynthetic cell of Arabidopsis thaliana, based on the Resource Balance Analysis (RBA) constraint-based modeling framework. The RBA model contains the metabolic network and the major macromolecular processes involved in the plant cell growth and survival and localized in cellular compartments. We simulated the model for varying environmental conditions of temperature, irradiance, partial pressure of CO2 and O2, and compared RBA predictions to known resource distributions and quantitative phenotypic traits such as the relative growth rate, the C:N ratio, and finally to the empirical characteristics of CO2 fixation given by the well-established Farquhar model. In comparison to other standard constraint-based modeling methods like Flux Balance Analysis, the RBA model makes accurate quantitative predictions without the need for empirical constraints. Altogether, we show that RBA significantly improves the autonomous prediction of plant cell phenotypes in complex environmental conditions, and provides mechanistic links between the genotype and the phenotype of the plant cell.

Molecular scale nanophotonics: hot carriers, strong coupling, and electrically driven plasmonic processes

Abstract Plasmonic modes confined to metallic nanostructures at the atomic and molecular scale push the boundaries of light–matter interactions. Within these extreme plasmonic structures of ultrathin nanogaps, coupled nanoparticles, and tunnelling junctions, new physical phenomena arise when plasmon resonances couple to electronic, exitonic, or vibrational excitations, as well as the efficient generation of non-radiative hot carriers. This review surveys the latest experimental and theoretical advances in the regime of extreme nano-plasmonics, with an emphasis on plasmon-induced hot carriers, strong coupling effects, and electrically driven processes at the molecular scale. We will also highlight related nanophotonic and optoelectronic applications including plasmon-enhanced molecular light sources, photocatalysis, photodetection, and strong coupling with low dimensional materials.

Salt damage on asphalt surfaces under repeated dissolution at molecular scale

Salt damage on asphalt surfaces is primarily attributed to migration of ions, with repeated dissolution exacerbating the degradation of asphalt performance. To investigate micro mechanism of salt corrosion on asphalt surfaces during repeated dissolution, this research uses molecular dynamics (MD) simulation and experiments to measure interactions among asphalt, salt, and water. Asphalt-salt systems and asphalt-water interfaces are built to calculate molecular damage behaviors by energies, mobilities, and distributions, along with micro-morphology and rheological properties of asphalt samples under salt corrosion. The interaction energies of salt with asphalt exhibit a hierarchy with Mg2+ ˃ Ca2+ ˃ Na+ and SO42- ˃ Cl-, predominantly governed by electrostatic energies. Repeated dissolution is a dynamic damage process. When water contacts on salt-eroded asphalt surfaces, salt ions migrate into water, forming solutions. Sulfates exhibit slower mobility and higher structural stability compared to chlorides, owing to smaller free volume, stronger interaction, and weaker water debonding. Rheologically, salt-eroded asphalt manifests as stiffer and tougher than water-eroded or base asphalt. These asphalt samples undergo softening and increased viscosity due to loss of salt ions. Consequently, compared to chlorides, sulfates demonstrate stronger interactions with asphalt and more difficulty in diffusing to water, resulting in severer damage on asphalt surfaces.

The β2-adrenergic receptor associates with CXCR4 multimers in human cancer cells

While the existence and functional role of class C G-protein-coupled receptors (GPCR) dimers is well established, there is still a lack of consensus regarding class A and B GPCR multimerization. This lack of consensus is largely due to the inherent challenges of demonstrating the presence of multimeric receptor complexes in a physiologically relevant cellular context. The C-X-C motif chemokine receptor 4 (CXCR4) is a class A GPCR that is a promising target of anticancer therapy. Here, we investigated the potential of CXCR4 to form multimeric complexes with other GPCRs and characterized the relative size of the complexes in a live-cell environment. Using a bimolecular fluorescence complementation (BiFC) assay, we identified the β2 adrenergic receptor (β2AR) as an interaction partner. To investigate the molecular scale details of CXCR4-β2AR interactions, we used a time-resolved fluorescence spectroscopy method called pulsed-interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). PIE-FCCS can resolve membrane protein density, diffusion, and multimerization state in live cells at physiological expression levels. We probed CXCR4 and β2AR homo- and heteromultimerization in model cell lines and found that CXCR4 assembles into multimeric complexes larger than dimers in MDA-MB-231 human breast cancer cells and in HCC4006 human lung cancer cells. We also found that β2AR associates with CXCR4 multimers in MDA-MB-231 and HCC4006 cells to a higher degree than in COS-7 and CHO cells and in a ligand-dependent manner. These results suggest that CXCR4-β2AR heteromers are present in human cancer cells and that GPCR multimerization is significantly affected by the plasma membrane environment.

Optimized Bags of Artificial Neural Networks Can Predict the Viability of Organisms Exposed to Nanoparticles.

Prediction of organismal viability upon exposure to a nanoparticle in varying environments─as fully specified at the molecular scale─has emerged as a useful figure of merit in the design of engineered nanoparticles. We build on our earlier finding that a bag of artificial neural networks (ANNs) can provide such a prediction when such machines are trained with a relatively small data set (with ca. 200 examples). Therein, viabilities were predicted by consensus using the weighted means of the predictions from the bags. Here, we confirm the accuracy and precision of the prediction of nanoparticle viabilities using an optimized bag of ANNs over sets of data examples that had not previously been used in the training and validation process. We also introduce the viability strip, rather than a single value, as the prediction and construct it from the viability probability distribution of an ensemble of ANNs compatible with the data set. Specifically, the ensemble consists of the ANNs arising from subsets of the data set corresponding to different splittings between training and validation, and the different bags (k-folds). A machine uses a single partition (or bag) of k - 1 ANNs each trained on 1/k of the data to obtain a consensus prediction, and a k-bag machine quorum samples the k possible machines available for a given partition. We find that with increasing k in the k-bag or machines, the viability strips become more normally distributed and their predictions become more precise. Benchmark comparisons between ensembles of 4-bag machines and fraction machines suggest that the fraction machine has similar accuracy while overcoming some of the challenges arising from divergent ANNs in the 4-bag machines.

Highly transparent and flame‐retardant polyvinyl alcohol membranes crosslinked with 2‐methyl‐2,5‐dioxo‐1,2‐oxaphospholane

AbstractIn the present paper, crosslinked polyvinyl alcohol (PVA) membranes with high transparency and excellent flame retardancy were obtained by blending 2‐methyl‐2,5‐dioxo‐1,2‐oxaphospholane (OP) with a PVA water solution at the molecular scale. Fourier transform infrared spectrometry and differential scanning calorimetry were used to investigate the crosslinking reaction. The surface morphology and micromechanical assessments of the membrane were examined using nanoindentation. The limited oxygen index (LOI) and vertical flame microscale combustion calorimetry, thermogravimetric analysis, scanning electron microscopy (SEM), energy‐dispersive spectroscopy (EDS), and x‐ray photoelectron spectroscopy (XPS) were employed to evaluate the flame retardancy and reveal the corresponding mechanisms. It was found that OP reacted with PVA below 120°C. The crosslinked membranes have a rougher surface and higher hydrophilicity and lower hardness and modulus than pure PVA does. The crosslinked membranes exhibit enhanced flame retardancy and high transparency. The membrane passes the UL 94 V 0 rating with an LOI of 27.6% and achieves a transmittance of 90.2% when the OP content is 20 wt.%. The SEM, EDS, and XPS results demonstrate that the interaction between OP and PVA effectively promotes the formation of a continuous and stable char in the condensed phase.