Search Results (147)

The efficient depolymerization of lignin has become a key challenge in the preparation of high-value-added chemicals. Graphitic carbon nitride (g-C₃N₄)-based photocatalytic system shows potential due to its mild and green characteristics over other depolymerization methods. However, its inherent defects, such as a wide band gap and rapid carrier recombination, severely limit its catalytic performance. In this paper, a g-C₃N₄ modification strategy of K⁺ doping and surface alkalinization is proposed, which is firstly applied to the photocatalytic depolymerization of the lignin β-O-4 model compound (2-phenoxy-1-phenylethanol). K⁺ doping is achieved by introducing KCl in the precursor thermal polymerization stage to weaken the edge structure strength of g-C₃N₄, and post-treatment with KOH solution is combined to optimize the surface basic groups. The structural/compositional evolution of the materials was analyzed by XRD, FTIR, and XPS. The morphology/element distribution was visualized by SEM-EDS, and the optoelectronic properties were evaluated by UV–vis DRS, PL, EIS, and transient photocurrent (TPC). K⁺ doping and surface alkalinization synergistically regulate the layered structure of the material, significantly increase the specific surface area, introduce nitrogen vacancies and hydroxyl functional groups, effectively narrow the band gap (optimized to 2.35 eV), and inhibit the recombination of photogenerated carriers by forming electron capture centers. Photocatalytic experiments show that the alkalinized g-C₃N₄ can completely depolymerize 2-phenoxy-1-phenylethanol with tunable product selectivity. By adjusting reaction time and catalyst dosage, the dominant product can be shifted from benzaldehyde (up to 77.28% selectivity) to benzoic acid, demonstrating precise control over oxidation degree. Mechanistic analysis shows that the surface alkaline sites synergistically optimize the C_β-O bond breakage path by enhancing substrate adsorption and promoting the generation of active oxygen species (·OH, ·O₂⁻). This study provides a new idea for the efficient photocatalytic depolymerization of lignin and lays an experimental foundation for the interface engineering and band regulation strategies of g-C₃N₄-based catalysts. Full article

The deep integration and application of artificial intelligence to organic chemistry are propelling the development of organic chemistry synthesis laboratories toward an intelligent automated laboratory model characterized by “hardware + software + AI”. This paper systematically explores the overall framework of AI-driven intelligent laboratories for organic chemistry synthesis, achieving automation and flexibility through standardized experimental integration workstations and intelligent scheduling and collaborative management of experimental resources. By leveraging multimodal databases, the integration of large models, machine learning, and other AI technologies enables AI-driven closed-loop intelligent chemical experiments, including product prediction, molecular retrosynthetic planning, and synthesis reaction optimization. The paper proposes a cloud-based shared operational model for chemical laboratories, aiming to achieve socialized sharing and intelligent matching of experimental resources, thereby facilitating the accumulation and sharing of chemical experimental data to promote the intelligent development of organic chemistry synthesis experiments. Practical cases of building intelligent chemical laboratories are shared, providing paths for technology implementation in constructing the next generation of automated and intelligent chemical laboratories. Full article

We developed a novel biodegradable poly(lactic-co-glycolic acid) (PLGA) polymer chemically modified with paclitaxel (PTX) to form a PLGA-PTX hybrid. Pre-modification of PTX enhanced its loading in PLGA-PTX nanoparticles (NPs). Background/Objectives: PTX is one of the most effective chemotherapy agents used in cancer therapy. The primary mode of PTX’s action is the hyperstabilization of microtubules leading to cell growth arrest. Although highly potent, the drug is water insoluble and requires the Cremophor EL excipient. The toxic effects of the free drug (e.g., neurotoxicity) as well as its solubilizing agent are well established. Thus, there is strong clinical rationale and need for exploring alternative PTX delivery approaches, retaining biological activity and minimizing systemic effects. Methods: The PTX modification method features reacting the C-2′ and C-7 residues with a linker (succinic anhydride) to produce easily accessible carboxyl groups on the PTX for enhanced coupling to the hydroxyl group of PLGA. The PLGA-PTX hybrid, formed via esterification reaction, was used to formulate lipid-coated PLGA-PTX NPs. As proof of concept, the PLGA-PTX NPs were tested in ovarian cancer (OvCA) models, including several patient-derived cell lines (PDCLs), one of which was generated from a platinum-resistant patient. Results: The PLGA-PTX NPs critically remained stable in water and serum while enabling slow drug release. Importantly, PLGA-PTX NPs demonstrated biological activity. Conclusions: We suggest that this approach offers both a new and effective PTX formulation and a possible path towards the development of a new generation of OvCA treatment. Full article

Catalysts with anionic metal centers have recently been proposed to enhance the performance of various chemical processes. Here, we focus on the reactivity of ${\mathrm{Co}\left(\mathrm{CO}\right)}_4^{-}$ for the polymerization of aziridine and carbon monoxide to form polypeptoids, motivated by earlier experimental studies. We used multi-reference and density functional theory methods to investigate possible reaction mechanisms and provide insights into the role of the negatively charged cobalt center. Two different reaction paths were identified. In the first path, ${\mathrm{Co}}^{-}$ acts as a nucleophile, donating an electron pair to the reaction substrate, while in the second path, it performs a single electron transfer to the substrate, initiating radical polymerization. The difference in the activation barriers for the two key steps is small and falls within the accuracy of our calculations. As suggested in the literature, solvent effects can play a primary role in determining the outcomes of such reactions. Future investigations will involve different metals or ligands and will investigate the effects of these two reaction paths on other chemical transformations. Full article

The massive loss of nitrogen (N) and phosphorus (P) from farmland ditches contributes to non-point source pollution, posing a significant global environmental challenge. Effectively removing these nutrients remains difficult in intensive agricultural systems. To address this, a novel composite ecological ditch system (CEDS) was developed by modifying traditional drainage ditches to integrate a grit chamber, zeolite, and ecological floating beds. Dynamic monitoring of N and P levels in water, plants, and zeolite was conducted to evaluate the system’s nutrient interception performance and mechanisms. The results showed the following: (1) Water quality improved markedly after passing through the CEDS, with nutrient concentrations decreasing progressively along the flow path. The system intercepted 41.0% of N and 31.9% of P, with inorganic N and particulate P as the primary forms of nutrient loss. (2) Zeolite removes N primarily through ion exchange, and P likely through chemical reactions, with maximum capacities of 3.47 g/kg for N and 1.83 g/kg for P. (3) Ecological floating beds with hydroponic cultivation enhanced nutrient uptake by the roots of Canna indica and Iris pseudacorus, with N uptake surpassing P. (4) Nutrient interception efficiency was positively correlated with temperature, ditch inlet concentrations, and rice runoff concentrations, but negatively with precipitation. This study demonstrates the CEDS’s potential for improving farmland water quality and suggests further enhancements in design and management to increase its economic and aesthetic value. Full article

The detailed n-heptane mechanism, which is widely used today, is suitable for a wide range of operating conditions. However, due to the large model involved, it is difficult to use this mechanism for computational fluid dynamics (CFD) simulation. In addition, the prediction accuracy of the existing simplified mechanism cannot meet simulation requirements with respect to low-temperature combustion and the negative temperature coefficient region. In this study, we sought to solve these problems by constructing a new simplified mechanism (NC2024) of the n-heptane chemical reaction based on the mechanism of Kuiwen Zhang using path analysis and sensitivity analysis. The mechanism involves 72 substances and 126 reactions. A comparison with the commonly used mechanism and an analysis of experimental data revealed that the NC2024 mechanism delivers high accuracy in predicting the ignition delay period under the low- to high-temperature conditions of 600–1100 K and a large pressure range of 13.5–42 bar and thus meets the accuracy requirements for CFD simulation of diesel low-temperature combustion. Full article

With the wide application of the gallium nitride (GaN) preparation method based on Metal–Organic Chemical Vapor Deposition (MOCVD), the automation of MOCVD equipment has become a research hotspot. This paper explores the automation scheme of MOCVD reaction chamber cleaning to improve productivity and reduce labor costs. Firstly, this paper establishes the kinematic solution model of a MOCVD cleaning robot and designs the cleaning robot path planning control algorithm. Considering the error between the initial position of the robot end-effector and the desired initial position in practical applications, this paper further designs a fault-tolerant motion planning algorithm for the initial position error. The simulation results show that the method can effectively reduce the initial position error and make it converge exponentially to zero. Finally, this paper builds the robot control system of the cleaning system and verifies the cleaning effect through tests. The test results show that the system can meet the actual use requirements and realize the reaction chamber cleaning automation goal. Full article

Over the years, the ammonia concentration in water streams and the environment is increasing at an alarming rate. Many membrane-based processes have been studied to alleviate this concern via adsorption and filtration. On the other hand, ammonia electro-oxidation is an approach of particular interest owing to its energetic and environmental benefits. Thus, a plausible alternative to combine these two paths is by using an electroconductive membrane (ECM) to complete the ammonia oxidation reaction (AOR). This combination of processes has been studied very limitedly, and it can be an area for development. Herein, we developed a multilayered membrane with hydrophilic and electrocatalytic properties capable of completing the AOR. The porosity of carbon black (CB) particles was embedded in the polymeric support (CBES) and the active side was composed of a triple layer consisting of polyamide/CB/Pt nanoparticles (PA:CB:Pt). The CBES increased the membrane porosity, changed the pores morphology, and enhanced water permeability and electroconductivity. The deposition of each layer was monitored and corroborated physically, chemically, and electrochemically. The final membrane CBES:PA:VXC:Pt reached higher water flux than its PSF counterpart (3.9 ± 0.3 LMH), had a hydrophilic surface (water contact angle: 19.8 ± 0.4°), and achieved the AOR at −0.3 V vs. Ag/AgCl. Our results suggest that ECMs with conductive material in both membrane layers enhanced their electrical properties. Moreover, this study is proof-of-concept that the AOR can be succeeded by a polymeric FO-ECMs. Full article

1-Methylnaphthalene is a critical component for constructing fuel surrogates of diesel and aviation kerosene. However, the reaction pathways of 1-methylnaphthalene included in existing detailed chemical kinetic models vary from each other, leading to discrepancies in the simulation of ignition and oxidation processes. In the present study, reaction classes and pathways involved in the combustion of 1-methylnaphthalene were analyzed, and effects of rate constants of reactions related to 1-methylnaphthalene and its significant intermediates on ignition delay times and species concentration profiles were discussed, involving hydrogen abstraction and substitution reactions of 1-methylnaphthalene, oxidation, isomerization, and addition reactions of 1-naphthylmethyl, hydrogen abstraction and oxidation reactions of indene, as well as the oxidation of indenyl and naphthalene. On this basis, a new detailed chemical kinetic model for 1-methylnaphthalene was developed, which includes 1389 species and 7185 reactions. The validation of this mechanism shows that it can predict accurately the available experimental ignition delay times, species concentration profiles, and laminar flame speeds of 1-methylnaphthalene. Finally, reaction paths and sensitivity analysis of ignition delay times were performed using the proposed reaction mechanism, and the result shows that the conversion of 1-methylnaphthalene to 1-naphthaldehyde plays an important role in its ignition. Full article

In order to reveal the deflagration mechanism of DME/H₂-blended gasses, the micro-mechanism was studied based on the constructed UC San Diego 2016 pyrolysis oxidation mechanism model. The results show that adiabatic flame temperature and laminar flame speed increase with the increase in the equivalence ratio (Φ); they first increase and then decrease with the increase in the hydrogen (H₂)-blended ratio (λ), and with the increase in λ, the Φ corresponding to the peak laminar flame speed of the blended gas increases. The addition of H₂ increases the consumption of O₂, and H₂ reacts with CO to form H₂O and CO₂, promoting complete combustion. When Φ = 1.0–1.2, the equilibrium mole fraction of H and OH-activated radicals reach the maximum, and with the addition of H₂, the concentration of activating radicals gradually increases, while the number of promoted elementary reactions increases by two, and the number of inhibited elementary reactions does not increase. Meanwhile, the addition of H₂ increases the reaction rate of most reactions on the main chemical reaction path CH₃OCH₃→CH₃OCH₂→CH₂O→HCO→CO→CO₂ of DME and increases the risk of the deflagration of DME/H₂-blended gas. Full article

Miniaturization promotes the efficiency and exploration domain in scientific fields such as computer science, engineering, medicine, and biotechnology. In particular, the field of microfluidics is a flourishing technology, which deals with the manipulation of small volumes of liquid. Dispersed droplets or bubbles in a second immiscible liquid are of great interest for screening applications or chemical and biochemical reactions. However, since very small dimensions are characterized by phenomena that differ from those at macroscopic scales, a deep understanding of physics is crucial for effective device design. Due to small volumes in miniaturized systems, common measurement techniques are not applicable as they exceed the dimensions of the device by a multitude. Hence, image analysis is commonly chosen as a method to understand ongoing phenomena. Artificial Intelligence is now the state of the art for recognizing patterns in images or analyzing datasets that are too large for humans to handle. X-ray-based Computer Tomography adds a third dimension to images, which results in more information, but ultimately, also in more complex image analysis. In this work, we present the application of the U-Net neural network to extract certain states during droplet formation in a capillary, which forms a constantly repeated process that is captured on tens of thousands of CT images. The experimental setup features a co-flow setup that is based on 3D-printed capillaries with two different cross-sections with an inner diameter, respectively edge length of 1.6 mm. For droplet formation, water was dispersed in silicon oil. The classification into different droplet states allows for 3D reconstruction and a time-resolved 3D analysis of the present phenomena. The original U-Net was modified to process input images of a size of 688 × 432 pixels while the structure of the encoder and decoder path feature 23 convolutional layers. The U-Net consists of four max pooling layers and four upsampling layers. The training was performed on 90% and validated on 10% of a dataset containing 492 images showing different states of droplet formation. A mean Intersection over Union of 0.732 was achieved for a training of 50 epochs, which is considered a good performance. The presented U-Net needs 120 ms per image to process 60,000 images to categorize emerging droplets into 24 states at 905 angles. Once the model is trained sufficiently, it provides accurate segmentation for various flow conditions. The selected images are used for 3D reconstruction enabling the 2D and 3D quantification of emerging droplets in capillaries that feature circular and square cross-sections. By applying this method, a temporal resolution of 25–40 ms was achieved. Droplets that are emerging in capillaries with a square cross-section become bigger under the same flow conditions in comparison to capillaries with a circular cross section. The presented methodology is promising for other periodic phenomena in different scientific disciplines that focus on imaging techniques. Full article

The conventional iron and steel industry (ISI), driven by coal utilization as its predominant feedstock, constitutes a substantial source of greenhouse gas emissions. Hydrogen metallurgy presents the opportunity to mitigate carbon emissions in ISI from the origin. Among hydrogen metallurgical approaches, the hydrogen-based direct reduction iron (H-DRI) process stands out for its substantial carbon reduction capabilities and established technological maturity. The present paper provides a comprehensive review of the development and application surrounding the H-DRI process. Firstly, the main chemical reactions of H-DRI and the relevant important parameters are introduced. Subsequently, an overview is provided of several prominent H-DRI processes, including HYL, Midrex, Midrex-H₂^®, HYL-III, HYL-ZR, BL, and Finmet, elucidating their characteristics through comparative analysis. Moreover, some research results of H-DRI process optimization are summarized. Leveraging insights garnered from globally representative projects exemplifying the industrial deployment of H-DRI technology in recent years, the trajectory of and prospective trends for industrial development in the field of H-DRI processes are explored. Further, prevailing challenges and impediments encountered in the adoption of H-DRI processes are identified, culminating in strategic recommendations tailored towards fostering future advancements. In the long term, the H-DRI process is expected to become a key path to achieve ISI cleaner production. Full article

Fe-N-C materials have been regarded as one of the potential candidates to replace traditional noble-metal-based electrocatalysts for the oxygen reduction reaction (ORR). It is believed that the structure of carbon support in Fe-N-C materials plays an essential role in highly efficient ORR. However, precisely designing the morphology and surface chemical structure of carbon support remains a challenge. Herein, we present a novel synthetic strategy for the preparation of porous carbon spheres (PCSs) with high specific surface area, well-defined pore structure, tunable morphology and controllable heteroatom doping. The synthesis involves Schiff-based polymerization utilizing octaaminophenyl polyhedral oligomeric silsesquioxane (POSS-NH₂) and heteroatom-containing aldehydes, followed by pyrolysis and HF etching. The well-defined pore structure of PCS can provide the confinement field for ferroin and transform into Fe-N-C sites after carbonization. The tunable morphology of PCS can be easily achieved by changing the solvents. The surface chemical structure of PCS can be tailored by utilizing different heteroatom-containing aldehydes. After optimizing the structure of PCS, Fe-N-C loading on N,S-codoped porous carbon sphere (NSPCS-Fe) displays outstanding ORR activity in alkaline solution. This work paves a new path for fabrication of Fe-N-C materials with the desired morphology and well-designed surface chemical structure, demonstrating significant potential for energy-related applications. Full article

In this work, we propose a multi-level protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points on the path are fitted with a machine learning technique (in our case symmetric gradient domain machine learning or sGDML) to produce a semi-local reactive potential energy surface (PES), embracing reactants, products and transition state (TS) regions. This approach has been successfully applied to a unimolecular (Bergman cyclization of enediyne) and a bimolecular (S_N2 substitution) reaction. In particular, we demonstrate that with only 50 to 150 energy-force evaluations with the accurate reference methods (here complete-active-space self-consistent field, CASSCF, and coupled-cluster singles and doubles, CCSD) it is possible to construct a semi-local PES giving qualitative agreement for stationary-point geometries, intrinsic reaction coordinates and barriers. Furthermore, we find a qualitative agreement in vibrational frequencies and reaction rate coefficients. The key aspect of the method’s performance is its multi-level nature, which not only saves computational effort but also allows extracting meaningful information along the reaction path, characterized by zero gradients in all but one direction. Agnostic to the nature of the TS and computationally economic, the protocol can be readily automated and routinely used for mechanistic reaction studies. Full article

Green ammonia has become an increasingly popular fuel in recent years because of its combustion process without carbon oxide release. Adding ammonia to methane fuel for co-combustion has become one of the important research topics in the current combustion field. In the present study, the CH₄/NH₃/Air counterflow diffusion flame was taken as the research object, and Chemkin-2019 R3 software was used to explore and analyze the flame extinction limit and chemical kinetics characteristics under different ammonia mixing ratios, initial pressures, and air preheating temperatures. It was obtained that the flame extinction stretch rate was decreased by increasing the NH₃ mole fraction in the CH₄/NH₃ mixed fuel. The increase in pressure or air preheating temperature would accelerate the chemical reaction rate of each component in the combustion process, increase the flame extinction limit, and counteract the “stretching effect” of the flame, thus restraining the flame extinguishing phenomenon. The results of a path analysis show that the formation and consumption of OH had an important influence on flame extinction in the chain reaction. The net reaction rate of OH increases with increasing the initial pressure or air preheating temperature, which leads to an increase in flame intensity, combustion stability, and the extinction limit. Furthermore, the function curve between the reaction influences the RIF factor and the stretch rate of the first-to-ten reactions, affected by the heat release of flame combustion, was drawn and quantitatively analyzed. Eventually, a sensitivity analysis of the flame under different working conditions was completed, which found that promoting the forward reaction R39 H + O₂<=>O + OH also promotes the positive combustion as a whole when the flame was near extinction. The sensitivity coefficient of R39 in the CH₄/NH₃/Air flame increases with the growing initial pressure. The increasing air preheating temperature was capable of switching the reaction of R248 NH₂ + OH<=>NH + H₂O in the CH₄/NH₃/Air flame from an inhibiting reaction to a promoting reaction, while decreasing the sensitivity coefficient of inhibiting the forward reaction R10 O + CH₃<=>H + CH₂O, R88 OH + HO₂<=>O₂ + H₂O, and R271 H + NO + M<=>HNO + M. Thus, the inhibition effect of flame extinction was weakened, and the positive progress of combustion was promoted. Full article