Chemistry Interactions Research Articles

Improved nanoformulation and bio-functionalization of linear-dendritic block copolymers with biocompatible ionic liquids.

Linear-dendritic block copolymers (LDBCs) have emerged as promising materials for drug delivery applications, with their hybrid structure exploiting advantageous properties of both linear and dendritic polymers. LDBCs have promising encapsulation efficiencies that can be used to encapsulate both hydrophobic and hydrophilic dyes for bioimaging, cancer therapeutics, and small biomolecules. Additionally, LDBCS can be readily functionalized with varying terminal groups for more efficient targeted delivery. However, depending on structural composition and surface properties, LDBCs also exhibit high dispersities (Đ), poor shelf-life, and potentially high cytotoxicity to non-target interfacing blood cells during intravenous drug delivery. Here, we show that choline carboxylic acid-based ionic liquids (ILs) electrostatically solvate LDBCs by direct dissolution and form stable and biocompatible IL-integrated LDBC nano-assemblies. These nano-assemblies are endowed with red blood cell-hitchhiking capabilities and show altered cellular uptake behavior ex vivo. When modified with choline and trans-2-hexenoic acid, IL-LDBC dispersity dropped by half compared to bare LDBCs, and showed a significant shift of the cationic surface charge towards neutrality. Proton nuclear magnetic resonance spectroscopy evidenced twice the total amount of IL on the LDBCs relative to an established IL-linear PLGA platform. Transmission electron microscopy suggested the formation of a nanoparticle surface coating, which acted as a protective agent against RBC hemolysis, reducing hemolysis from 73% (LDBC) to 25% (IL-LDBC). However, dramatically different uptake behavior of IL-LDBCs vs. IL-PLGA NPs in RAW 264.7 macrophage cells suggests a different conformational IL-NP surface assembly on the linear versus the linear-dendritic nanoparticles. These results suggest that by controlling the physical chemistry of polymer-IL interactions and assembly on the nanoscale, biological function can be tailored toward the development of more effective and more precisely targeted therapies.

SELF-HEALING STRATEGIES IN RUBBER COMPOSITES

Inspired by some of the mechanisms that occur in nature, self-healing materials are characterized by the ability to recover, partially or totally, their initial properties after suffering damage. These materials constitute an efficient alternative for extending the lifecycle of products, as well as for reducing the amount of waste generated. At the same time, they reduce maintenance and repair costs. In this work, examples of recent developments in the field of elastomeric composite materials are presented, studying different matrices, natural rubber (NR), epoxidized natural rubber (ENR), styrene-butadiene rubber (SBR) and nitrile rubber (NBR), and using diverse repair strategies, hydrogen bonds, disulfide exchange reactions, Diels-Alder chemistry and ionic interactions. The effect of adding carbon-derived reinforcing fillers (graphene oxide) and sustainable alternative fillers (ground tire rubber) is also analyzed. It is studied how the presence and type of filler influences the healing capacity of elastomeric matrices, reaching repair efficiencies of up to ~80%, without detriment to their mechanical performance.

Bioenergy Underground: Challenges and opportunities for phenotyping roots and the microbiome for sustainable bioenergy crop production

AbstractBioenergy production often focuses on the aboveground feedstock production for conversion to fuel and other materials. However, the belowground component is crucial for soil carbon sequestration, greenhouse gas fluxes, and ecosystem function. Roots maximize feedstock production on marginal lands by acquiring soil resources and mediating soil ecosystem processes through interactions with the microbial community. This belowground world is challenging to observe and quantify; however, there are unprecedented opportunities using current methodologies to bring roots, microbes, and soil into focus. These opportunities allow not only breeding for increased feedstock production but breeding for increased soil health and carbon sequestration as well. A recent workshop hosted by the USDOE Bioenergy Research Centers highlighted these challenges and opportunities while creating a roadmap for increased collaboration and data interoperability through standardization of methodologies and data using F.A.I.R. principles. This article provides a background on the need for belowground research in bioenergy cropping systems, a primer on root system properties of major U.S. bioenergy crops, and an overview of the roles of root chemistry, exudation, and microbial interactions on sustainability. Crucially, we outline how to adopt standardized measures and databases to meet the most pressing methodological needs to accelerate root, soil, and microbial research to meet the pressing societal challenges of the century.

Turbulent flame-wall interaction of premixed flames using Quadrature-based Moment Methods (QbMM) and tabulated chemistry: An a priori analysis

Presumed probability density function (PDF) and transported PDF methods are commonly applied to model the turbulence chemistry interaction in turbulent reacting flows. However, little focus has been given to the turbulence chemistry interaction PDF closure for flame-wall interaction. In this study, a quasi-DNS of a turbulent premixed, stoichiometric methane-air flame ignited in a fully developed turbulent channel flow undergoing side-wall quenching is investigated. The objective of this study is twofold. First, the joint PDF of the progress variable and enthalpy that needs to be accounted for in turbulence chemistry interaction closure models is analyzed in the quasi-DNS configuration, both in the core flow and the near-wall region. Secondly, a transported PDF closure model, based on a Conditional Quadrature Method of Moments approach, and a presumed PDF approach are examined in an a priori analysis using the quasi-DNS as a reference both in the context of Reynolds-Averaged Navier Stokes (RANS) and Large-Eddy Simulations (LESs). The analysis of the joint PDF demonstrates the high complexity of the reactive scalar distribution in the near-wall region. Here, a high correlation between the progress variable and enthalpy is found, where the flame propagation and quenching are present simultaneously. The transported PDF approach presented in this work, based on the Conditional Quadrature Method of Moments, accounts for the moments of the joint PDF of progress variable and enthalpy coupled to a Quenching-Flamelet Generated Manifold. In the a priori analysis both turbulence chemistry interaction PDF closure models show a high accuracy in the core flow. In the near-wall region, however, only the Conditional Quadrature Method of Moments approach is suitable to predict the flame structures.

Interactive Android Module Development Containing Three Chemical Representation Levels on Material of Salt Hydrolysis

Three chemical representation is an important aspect of chemistry learning. However, the database study shows that interactive chemistry learning media containing three levels of representation is not available. This research aims to develop and assess the feasibility of an interactive Android-based learning module for senior high school students containing three chemical representation levels on the material of salt hydrolys-is. The study was conducted using research and development (RD) method. Stages of research were con-ducted as follows, analysis, development process, product validation and assessment. The Android module was subsequently validated by media and concept experts and then limitedly assessed by five chemistry teachers and ten senior high school students. The instrument used was validated by an instrument expert. The validation results by media and concept experts indicated that the media was valid in terms of media performance and salt hydrolysis material. Based on teachers' and students' assessments, the media received a score of 87.5% and 83.0%, with very good category. It can be concluded that the interactive Android-based learning module containing three chemical representations on the material of salt hydrolysis was successful-ly developed and can be tested extensively in senior high school. The developed media closed a significant gap in the need of interactive chemistry learning media containing three levels of chemical representation, especially in the material of salt hydrolisis

Identifying Data Needed to Reduce Parameter Uncertainty in a Coupled Microbial Soil C and N Decomposition Model

AbstractAdvancements in microbially explicit ecosystem models incorporate increasingly accurate representations of microbial physiology and enzyme‐mediated depolymerization of soil organic matter in predicting biogeochemical responses to global change. However, a major challenge with model structural improvements is the requirement for additional parameters, which are often poorly constrained sources of uncertainty. Furthermore, it is often unclear how to best focus data collection efforts toward reducing model uncertainty. Here, we use Dual Arrhenius Michaelis‐Menten Microbial Carbon and Nitrogen Physiology, a microbially mediated, coupled soil C and N cycling model, as a tool to explore the influence of microbial physiological and enzyme kinetic parameters on model estimates. We first quantify the potential for constraining model parameters using empirical measurements of soil respiration. We then use simulated data to identify which additional sources of data collection from the field would provide the greatest impact for constraining model estimates. We find that modeled soil C and N pools and fluxes are disproportionately sensitive to only a few parameters (e.g., activation energies and microbial CUE), while others exert less influence (e.g., Michaelis‐Menten half‐saturation constants). While some parameters can be constrained by the available data on heterotrophic respiration, the collection of additional data on dissolved organic C and N pools in the soil is identified as a high‐priority data need. Improving our ability to model the interactions of soil microbial physiology, soil chemistry, enzyme activities, and environmental factors on C and N cycling will require closely considering model uncertainties and prioritizing future data collection opportunities based on their impact on model performance.

Synthesis, characterization and biocompatibility of guar gum-benzoic acid

A novel chemical functionalization of guar gum (GG) by benzoic acid (BA) via nucleophilic substitution reaction in aqueous solution has been reported. BA moieties are chosen due to coordination chemistry of carboxylic acid moieties, hydrophobicity and intermolecular interaction of aromatic rings. The presence of conjugated BA on guar gum-benzoic acid (GG-BA) with grafting density of 5.5% is confirmed by 1H NMR. Amorphous GG-BA with irregular morphology has been studied by UV–Vis, FTIR, XRD, SEM, TEM, TGA, computational chemistry and contact angle measurement. GG-BA in a concentration range from 0 to 4000 μg mL−1 has good biocompatibility to mouse embryonic fibroblasts (MEF), human mammary epithelial cells (MCF-10A) after 48 and 72 h of treatment using WST-1 assay. GG-BA shows great potential for the development of biomaterials such as bioadhesives, hydrogels, and coacervates.

Raman spectroscopy for quantitative measurements of temperature and major species in high-pressure non-premixed NH3/H2/N2 counterflow flames

Ammonia has shown great potential as a carbon-free fuel, in particular for marine transportation and energy production. Its low laminar flame speed, and the tradeoff between ammonia slip and NOx emission, pose challenges for industrial applications, and a more in-depth understanding of the combustion of ammonia is therefore needed. Raman spectroscopy is a powerful diagnostic often employed to investigate turbulence chemistry interactions and resolve the thermo-chemical structure of hydrogen and hydrocarbon-air flames. This work extends Raman spectroscopy to the instantaneous and spatially resolved measurement of major species concentrations and temperature in ammonia flames. The lack of detailed ammonia spectra at high temperatures, the strong flame luminosity, and fluorescence interference are the major obstacles to the implementation of Raman spectroscopy to ammonia flames. This paper introduces a novel approach to estimate the temperature dependence of the Raman signal and of fluorescence interference contributions from a series of counterflow diffusion flames. This approach was first validated in high-pressure hydrogen flame, and then extended this approach to high-pressure ammonia flames to obtain the Raman response of ammonia and its crosstalk. A high-contrast optical shutter is sufficient to suppress flame luminosity. Finally, species concentrations and temperature profiles from measurements are shown, and their accuracy and precision are discussed.

Numerical investigation on implication of innovative hydrogen strut injector on performance and combustion characteristics in a scramjet combustor

Abstract A detailed numerical analysis on a scramjet combustor is carried out by introducing an innovative shaped strut in place of the conventional strut. The design of newly added strut aids in generating intense vorticity which helps in efficient mixing of fuel and oxidizer. The air from the isolator enters the combustor at Mach 2.0, whereas fuel enters from the trailing edge of the strut sonically. In this study the flow dynamics with finite volume approach on commercial software Ansys-Fluent 20.0 to solve the two-dimensional Reynolds average Navier Stokes equation (RANS) with compressible fluid flow by considering the density-based solver with SST k-ε turbulent model. The species transport model with volumetric reaction and finite rate/eddy dissipation turbulence chemistry interaction is adopted to study the combustion phenomena and validated with the experimental results, and it is found that the interaction of the shear shock layer enhances the mixing rate by intensifying turbulence. The modified strut injector’s mixing efficiency is compared to the base strut and observed that with a 40% reduction in length, the modified strut injection technique exhibited a mixing efficiency of >95%. The combustion efficiency is then estimated streamwise, and the plot follows the same pattern as the mixing efficiency with fuel burns down completely when x = 150 mm for the modified strut whereas x = 200 mm for the base strut. This can compact the combustion chamber and increases the thrust-to-weight ratio. So, the innovative strut adopted can improvise the combustion efficiency.

Harnessing Noncovalent Interactions for a Directed Evolution of a Six-Component Molecular Crystal.

Building up on weak orthogonal interactions in supramolecular chemistry, a six-component crystal is designed. Using five distinctly different noncovalent forces, namely, hydrogen bonding, halogen bonding, cation-π, anion-π, and ion-pair interactions, three six-component crystals were designed with crown-ether (I), thiourea (II), 2,3,5,6-tetrafluoro-1,4-dibromobenzene (III), lone-pair donating anion (IV), ammonium cation (V), and electron-rich aromatic ring (VI). The M06-2X functional which is highly suitable in describing other weak interactions fails for ion-pairs. Tuned range-separated (RS)-DFT calculations are found to be capable in describing the ionic interactions in molecular solids. Molecular dynamics simulations show that the predicted multicomponent crystals are stable at room temperature and reducing the ionic charges for the ion-pairs destabilizes them. The strong electrostatic interactions between the three ion-pairs, NH4+···ClO4-, NH4+···HSO4-, and NH4+···HCO3- is the primary driving force for the stabilization of the six-component crystal. Using a hybrid of strong and weak intermolecular interactions, one may generate exotic molecular complexity like n-component crystals.

Pedagogy of Emerging Technologies in Chemical Education during the Era of Digitalization and Artificial Intelligence: A Systematic Review

The technological advancement and rapid development of artificial intelligence have led to a growing number of studies investigating pedagogical innovations incorporated with emerging technologies in this digital era. An increasing amount of empirical evidence has suggested the potential benefits of incorporating digital technologies and artificial intelligence in various educational contexts, such as the K-12 education, and a change in learning modality in the unprecedented period of COVID-19. In chemical education, various types of emerging technologies, such as eye-tracking techniques, learning analytics, robotics, virtual reality (VR), and augmented reality (AR), have seen wide applications and promising prospects. In this paper, a systematic review of emerging technologies adopted in chemical education during this era of digitalization and artificial intelligence is presented. The current study aims to identify the major types of technologies adopted in chemical education and analyze the empirical findings from relevant studies. A total of 45 studies between 2010 and 2021 were analyzed through a literature search in three inter-disciplinary databases: Web of Science, Scopus, and the Educational Information Resource Center. Full-text retrieval and analysis of the included studies were conducted. The present study finds that AR and VR applications were most extensively investigated among the identified types of technologies adopted in chemical education, while the major focus areas were associated with virtual chemistry laboratories, visualization and interaction with chemical structures, and classroom hands-on activities. The evidence presented in this study also indicates the promising applications of artificial intelligence and learning analytics in the analysis of students’ feedback and behavior, assessment of students’ understanding of chemical concepts, and investigations of students’ reasoning and cognitive processes during chemical tasks such as spectral interpretation. Furthermore, areas requiring more research, investigations, potential future applications, as well as pedagogical implications of education for sustainable development will be identified based on the evidence presented in this study. The findings of this study are expected to give insight on the evolving areas of chemical education research and technology-enhanced teaching and learning.

Turbulent jet ignition of ultra-lean methane/air mixture under engine-like condition

Turbulent jet ignition (TJI) is a promising technology that enables engines to operate stably at ultra-lean-burn conditions for improved thermal efficiency. In the present work, TJI of an ultra-lean methane/air mixture (excessive air ratio λ = 2.0) under an engine-like condition (temperature of 900 K and pressure of 5.8 MPa) was numerically studied, with particular interest on the ignition patterns and the critical/favorable conditions for successful ignition/rapid combustion. A high-fidelity large eddy simulation was performed, with the linear eddy model being incorporated to account for turbulence–chemistry interaction. To represent the different amount/state of energy released from a pre-chamber, a variety of turbulent jet temperatures, inlet velocities, and orifice diameters were covered. The results identified two successful ignition patterns, including a flame propagation pattern and a jet re-ignition pattern. An ignition regime was also established, with the boundary between ignition success/failure identified by a global Damköhler number (Da) of 0.1. In terms of the combustion rate, heat release in the propagative flame is governed by the growth of the flame surface, which is primarily controlled by stretch and enlarges with the jet Reynolds number (Re). The present results suggest that, for low-reactivity fuels such as methane, the pre-chamber combustion in a TJI system should pursue complete heat release and increase Re and Da simultaneously for the injected turbulent jet into the main combustion chamber.

Impact of ascorbic acid on polydopamine modified amorphous TiO2-xNx nanosheets

Surface modification of titanium dioxide (TiO2) with enediol like dopamine improves its optoelectronic properties due to chelation of Ti atom by electron donating bidentate ligand. Introduction of N in TiO2 is expected to weaken the interaction between Ti atoms and bidentate ligand because of extra active acceptor sites. Hence, the chemistry of N doped TiO2 and dopamine is likely to display contradictory behavior in comparison to TiO2-dopamine. In this study, amorphous TiO2-xNx nanosheet were synthesized incorporating diethyl triamine (DETA) and acetonitrile (ACN) which plays significant role in obtaining desired morphology. Furthermore, the chemistry of interaction between TiO2-xNx and dopamine was explored, wherein dopamine self-polymerizes on the surface of nanosheets forming TiO2-xNx – Polydopamine (PD). Comparative study of TiO2-xNx–PD and TiO2-PD were investigated in presence of similar enediol ligand such as ascorbic acid (AA) along with weak and strong acid. It was observed that only in presence of AA, TiO2-xNx–PD bond gets weaken from the fluorescence recovery of PD. This behavior of AA was tested with a detection range of 10–100 nM and limit of detection of 2 pM in biological fluid. Our results could be helpful for tuning the optoelectronic properties of TiO2 based hybrid composites for future applications.

Regenerative furnace simulation under flameless combustion regime with natural gas and syngas

The increase in pollutant emissions has generated the development of clean technologies and encouraged the use of alternative fuels like syngas. Flameless combustion is one of the most promising clean technologies due to lower pollutants emissions and high thermal efficiency. In the present study, regenerative furnace simulation under flameless combustion was carried out using a fuel mixture of 70% natural gas and 30% syngas with high H2 content (in vol.); by mean of CFD approach. A symmetrical mesh with 405,632 hexahedral cells was used in the calculations. The κ-ε standard, discrete ordinates and Eddy Dissipation Concept models were used for physical phenomena of turbulence, radiation and turbulence - chemistry interaction, respectively. The combustion chambers thermal uniformity factor was 0.3 and 0.1 for vertical and horizontal planes, respectively. The results confirm that it is possible to achieve the flameless combustion regime in a regenerative furnace using the addition of syngas, preserving the temperature and reaction zone uniformity.

Simulation of Indian Summer Monsoon Rainfall (ISMR) with fully coupled regional chemistry transport model: A case study for 2017

The Indian subcontinent is a major hotspot of enhanced aerosol loading and emission of various chemical compounds due to extensive anthropogenic activities that profoundly impact the hydrological cycle of this region. Using coupled regional atmospheric chemistry transport model, WRF-Chem (Weather Research and Forecasting model coupled with chemistry) with fully interactive chemistry and dynamics, we carried out two sets of 122-days simulation experiments: (1) a control experiment without embedding chemistry and (2) a sensitivity experiment with embedding fully coupled MOZART-MOSAIC chemistry, to examine the impact of chemistry on the Indian Summer Monsoon Rainfall (ISMR) of 2017. The results show that inclusion of chemistry in the model plays a role in altering the spatial distribution of ISMR, reflected by a reduced mean rainfall by about 3 mm/day over the Indian subcontinent. The mean bias of model simulated rainfall reduces from 2.73 mm/day (excluding chemistry) to 1.6 mm/day (including chemistry), and from 1.2 mm/day (excluding chemistry) to 0.81 mm/day (including chemistry) when compared with IMD (India Meteorological Department) and TRMM (Tropical Rainfall Measuring Mission) rainfall data, respectively. Additionally, we found that inclusion of interactive chemistry causes a decrease in the daily convective rainfall by about 3 mm that is contributing largely to the mean rainfall differences. Further, analysis of hydrometeors indicates that the chemistry interacts with the cloud microphysics by modulating the hydrometeor paths of different cloud hydrometeors that consequently impacts the simulation of ISMR over this region. Results indicate that the virtue of detailed and more realistic representation of chemistry in the model has led to more realistic simulation and cannot be ignored in numerical forecasting of ISMR.

Noncovalent Interactions in Organometallic Chemistry: From Cohesion to Reactivity, a New Chapter.

Noncovalent interactions (NCIs) have long interested a vast community of chemists who investigated their "canonical categories" derived from descriptive crystallography, e.g., H-bonds, π-π interactions, halogen/chalcogen/tetrel bonds, cation-π and C-H-π interactions, metallophilic interactions in the broad sense, etc. Recent developments in theoretical chemistry have enabled the treatment of noncovalent interactions under new auspices: dispersion-force-inclusive density functionals have emerged, which are reliable for modeling small to large molecular systems. It is possible to perform the full analysis of the contributions of London, Debye, and Keesom forces, i.e., the main components of van der Waals forces, by the DFT-D and ab initio methods at a reasonable computational cost. Our research has been focusing for now 15 years on the role of NCIs in the cohesion of organometallic complexes. NCIs are not only effective in Werner's secondary coordination sphere but also in the metal's primary one. The stabilization of electron-unsaturated transition metal complexes by hemichelation, metal-metal donor-acceptor complexes, and self-aggregation of cationic Rh(I) chromophores have indeed outlined the significance of the London dispersion force as an attractive force operating throughout the whole molecule or molecular assembly. The recent outburst of interest in C-H bond functionalization led us to address the broader question of reaction and catalyst engineering: although one can now satisfactorily analyze bonding and molecular cohesion in transition-metal-based organometallic systems, can modern theoretical methods guide reactivity exploration and the engineering of novel catalytic systems? We addressed this question by investigating the ambiphilic metal-ligand activation/concerted metalation-deprotonation mechanism involved in transition-metal-catalyzed directed C-H bond functionalization. This endeavor was initiated having in scope the construction of a rationale for the transposition of 4-5d metal chemistry to earth-abundant 3d metals. In this base-assisted mechanism of C-H bond metalation, agostic interactions are necessary but not sufficient because C-H bond breaking actually relies on the attractive NCI coding of a proton-transfer step and the minimization of metal-H repulsion. This Account introduces the recent shift of our research toward the construction of an NCI-inclusive paradigm of chemical reactivity engineering based on experimental efforts propped up by state-of-the-art theoretical tools.

Multiscale modeling of plasma–surface interaction—General picture and a case study of Si and SiO2 etching by fluorocarbon-based plasmas

The physics and chemistry of plasma–surface interaction is a broad domain relevant to various applications and several natural processes, including plasma etching for microelectronics fabrication, plasma deposition, surface functionalization, nanomaterial synthesis, fusion reactors, and some astrophysical and meteorological phenomena. Due to their complex nature, each of these processes is generally investigated in separate subdomains, which are considered to have their own theoretical, modeling, and experimental challenges. In this review, however, we want to emphasize the overarching nature of plasma–surface interaction physics and chemistry, by focusing on the general strategy for its computational simulation. In the first half of the review, we provide a menu card with standard and less standardized computational methods to be used for the multiscale modeling of the underlying processes. In the second half, we illustrate the benefits and potential of the multiscale modeling strategy with a case study of Si and SiO2 etching by fluorocarbon plasmas and identify the gaps in knowledge still present on this intensely investigated plasma–material combination, both on a qualitative and quantitative level. Remarkably, the dominant etching mechanisms remain the least understood. The resulting new insights are of general relevance, for all plasmas and materials, including their various applications. We therefore hope to motivate computational and experimental scientists and engineers to collaborate more intensely on filling the existing gaps in knowledge. In this way, we expect that research will overcome a bottleneck stage in the development and optimization of multiscale models, and thus the fundamental understanding of plasma–surface interaction.

Extreme Ozone Loss Following Nuclear War Results in Enhanced Surface Ultraviolet Radiation

AbstractFor the first time, we use a modern climate model with interactive chemistry including the effects of aerosols on photolysis rates to simulate the consequences of regional and global scale nuclear wars (injecting 5 and 150 Tg of soot respectively) for the ozone layer and surface ultraviolet (UV) light. For a global nuclear war, heating in the stratosphere, reduced photolysis, and an increase in catalytic loss from the HOx cycle cause a 15 year‐long reduction in the ozone column, with a peak loss of 75% globally and 65% in the tropics. This is larger than predictions from the 1980s, which assumed large injections of nitrogen oxides (NOx), but did not include the effects of smoke. NOx from the fireball and the fires provide a small (5%) increase to the global average ozone loss for the first few years. Initially, soot would shield the surface from UV‐B, but UV Index values would become extreme: greater than 35 in the tropics for 4 years, and greater than 45 during the summer in the southern polar regions for 3 years. For a regional war, global column ozone would be reduced by 25% with recovery taking 12 years. This is similar to previous simulations, but with a faster recovery time due to a shorter lifetime for soot in our simulations. In‐line photolysis provides process specific action spectra enabling future integration with biogeochemistry models and allows output that quantifies the potential health impacts from changes in surface UV for this and other larger aerosol injections.

Ultrasensitive detection of endocrine disruptors via superfine plasmonic spectral combs

The apparent increase in hormone-induced cancers and disorders of the reproductive tract has led to a growing demand for new technologies capable of detecting endocrine disruptors. However, a long-lasting challenge unaddressed is how to achieve ultrahigh sensitive, continuous, and in situ measurement with a portable device for in-field and remote environmental monitoring. Here we demonstrate a simple-to-implement plasmonic optical fiber biosensing platform to achieve an improved light–matter interaction and advanced surface chemistry for ultrasensitive detection of endocrine disruptors. Our platform is based on a gold-coated highly tilted fiber Bragg grating that excites high-density narrow cladding mode spectral combs that overlap with the broad absorption of the surface plasmon for high accuracy interrogation, hence enabling the ultrasensitive monitoring of refractive index changes at the fiber surface. Through the use of estrogen receptors as the model, we design an estradiol–streptavidin conjugate with the assistance of molecular dynamics, converting the specific recognition of environmental estrogens (EEs) by estrogen receptor into surface-based affinity bioassay for protein. The ultrasensitive platform with conjugate-induced amplification biosensing approach enables the subsequent detection for EEs down to 1.5 × 10−3 ng ml−1 estradiol equivalent concentration level, which is one order lower than the defined maximal E2 level in drinking water set by the Japanese government. The capability to detect EEs down to nanogram per liter level is the lowest limit of detection for any estrogen receptor-based detection reported thus far. Its compact size, flexible shape, and remote operation capability open the way for detecting other endocrine disruptors with ultrahigh sensitivity and in various hard-to-reach spaces, thereby having the potential to revolutionize environment and health monitoring.

Investigation of pollutants formation in a diesel engine using numerical simulation

The current study aims at simulating the in-cylinder combustion process in a diesel engine and investigating the engine performance and pollutant formation. The combustion simulation is performed on a 3D sector employing appropriate models for various physical and chemical processes contributing in the combustion phenomenon. The overall model includes Transition SST turbulence model, eddy dissipation model for turbulence chemistry interaction, Moss–Brookes model for soot calculation and Zeldovich mechanism for NO production other than the usual transport equations. The numerical solutions are based on the finite volume discretization of the governing partial differential equations. Engine performance has been studied in terms of pressure, temperature and heat release rate while the pollutants formation has been investigated in terms of soot and thermal NO production. The results show that the ignition delay is quite short and that the injection timing may be successfully employed to control the combustion behavior. The simulation results are quite consistent with the expected behavior of the target variables indicating that the CFD analysis can be successfully employed in the diesel engine design. The results validation may be acknowledged in view of the mesh independence test, literature comparison and justification of the models.