Top Read Articles

Published in last 1 year |

In last 2 years |

In last 3 years |

All

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Mechanistic Insights into S-Doped g-C3N4 for Enhanced Photocatalytic Performance: A Theoretical Study YANG Yufei, ZHAO Yi, YIN Lifang, ZHAO Jiaying, GAO Qiang, SU Tan, ZHANG Heyang, YIN Yajun, SU Zhongmin, ZOU Luyi Chemical Research in Chinese Universities    2025, 41 (5): 1067-1075.   DOI: 10.1007/s40242-025-5187-5 Abstract （669）            Knowledge map    Save Non-metal doping is an effective strategy to modulate the electronic structure of graphitic carbon nitride (g-C3N4) and optimize its photocatalytic activity. Based on first-principles density functional theory, this work calculated the formation energy, electronic properties, and optical performance of S-doped monolayer g-C3N4. The results demonstrate that S atoms preferentially occupy interstitial sites, as characterized by low formation energy and thermodynamic spontaneity, which leads to stabilization, followed by the edge N2-sites. After introducing S impurities via the N2 and interstitial doping sites, the band gap of g-C3N4 is narrowed from 2.63 eV (calculated by the HSE06 functional) to 2.35 eV (for N2-site doping) and 1.99 eV (for interstitial-site doping), respectively. Both C3N4-N2 and S-interstitial doping enhance the delocalization of the highest occupied molecular orbital and the lowest unoccupied molecular orbital. Specifically, interstitial S atoms act as "bridges" to connect adjacent structural units, significantly improving carrier mobility and facilitating the separation of photogenerated electron-hole pairs. Furthermore, S-interstitial doping reduces the work function of g-C3N4 from 4.16 eV to 3.64 eV, which strengthens visible light absorption. This work provides theoretical support for the design and preparation of non-metal-doped modified g-C3N4 photocatalysts. Reference | Related Articles | Metrics

Select

A Global Fundamental Invariants Neural Networks Potential Energy Surface and Dynamics Study of the H+HCN Reaction CHEN Qun, LIU Shu, FU Bina, ZHANG Donghui Chemical Research in Chinese Universities    2025, 41 (5): 1021-1028.   DOI: 10.1007/s40242-025-5140-7 Abstract （614）            Knowledge map    Save A global potential energy surface (PES) for the H+HCN reaction has been constructed using the fundamental invariants neural networks (FI-NN) fitting method, based on 38662 ab initio energy points calculated at the UCCSD(T)-F12a/AVTZ theoretical level. The PES not only covers the well-studied abstract channel, but also accurately describes the stationary points and reaction pathways of the exchange channel, achieving an overall root-mean-square error (RMSE) of 2.85 meV. Total integral cross sections of both channels were computed, and the branching ratios of HCN and HNC product isomers were also analyzed, with HNC further distinguished by its formation through three different pathways. Reference | Related Articles | Metrics

Select

Calculation of the Green’s Function on Near-term Quantum Computers via Cartan Decomposition WAN Lingyun, LIU Jie, YANG Jinlong Chemical Research in Chinese Universities    2025, 41 (5): 1029-1036.   DOI: 10.1007/s40242-025-5149-y Abstract （572）            Knowledge map    Save Accurate computation of the Green’s function is crucial for connecting experimental observations to the underlying quantum states. A major challenge in evaluating the Green’s function in the time domain is the efficient simulation of quantum state evolution under a given Hamiltonian, a task that becomes exponentially complex for strongly correlated systems on classical computers. Quantum computing provides a promising pathway to overcome this challenge by enabling efficient simulation of the time evolution operator. However, for near-term quantum devices with limited coherence times and fidelity, the deep quantum circuits required to implement time-evolution operators present a significant challenge for practical applications. In this work, we introduce an efficient algorithm for computing Green's functions via Cartan decomposition, which requires only fixed-depth quantum circuits for arbitrarily long time simulations. Additionally, analytical gradients are formulated to accelerate the Cartan decomposition by leveraging a unitary transformation in the factorized form. The new algorithm is applied to simulating long-time Green’s functions for the Fermi-Hubbard and transverse-field Ising models, extracting the spectral functions through Fourier transformation. Reference | Related Articles | Metrics

Select

Darwin4Matter: A Platform Integrating Machine Learning and Quantum Chemistry for New Materials Design RONG Hui, CHEN Yili, ZHANG Shubo, CHEN Yue, SHEN Lin, FANG Wei-Hai Chemical Research in Chinese Universities    2025, 41 (5): 1014-1020.   DOI: 10.1007/s40242-025-5170-1 Abstract （551）            Knowledge map    Save Machine learning (ML) has emerged to play a more and more important role in material science. Here, we develop a platform named Darwin4Matter that integrates machine learning and quantum chemistry for new materials discovery. The framework consists of six steps: quantum chemistry prediction, Δ-machine learning correction, molecular augmentation, machine learning prediction, molecular production, and verification. Using this platform, we start from a very small dataset and design three new functional molecules with high refractive indexes in the visible spectrum, which serves as the capping layer of organic light-emitting diode devices for improving light extraction efficiency. The superior performance over currently used materials has been verified experimentally, exhibiting significant commercial value in the field of advanced display materials. Reference | Related Articles | Metrics

Select

Substrate-mediated Self-assembly of 1,3,5-Benzene/Triazine Functionalized by Flexible Isopropylethynyl Groups LIN Yu, YOU Sifan, XIE Miao, ZHANG Meng, XU Chaojie, CHI Lifeng Chemical Research in Chinese Universities    2025, 41 (5): 1048-1055.   DOI: 10.1007/s40242-025-5077-x Abstract （545）            Knowledge map    Save Nanofabrication of tunable two-dimensional (2D) supramolecular architecture relies on the delicate balance between molecule-molecule and molecule-substrate interactions, where carefully designed molecules as building blocks are required. In this study, we introduced isopropylethynyl groups into two tripodal molecules, i.e., 1,3,5-tris-(isopropylethynyl)-benzene (iPr-TEB) and 2,4,6-tris-(isopropylethynyl)-1,3,5-triazine (iPr-TET), and investigated their self-assembly on Au(111) and Ag(111) surfaces under ultra-high-vacuum using scanning tunneling microscopy (STM). On Au(111) and Ag(111), iPr-TEB formed relatively comparable self-assembled nanopatterns through side-by-side dimers aggregation. These subtle differences in aggregation correlate with their negligible variations in adsorption conformation and energy. In contrast, iPr-TET exhibited pronounced substrate-dependent adsorption geometries due to stronger molecule-substrate interactions, resulting in disparate self-assembled nanoarchitectures on these two surfaces. Our results highlight the rotational flexibility of the isopropyl groups enabled by the single bond connecting them to the main acetylenic core, modulating intermolecular interactions and fine-tuning molecule-substrate interactions strength, hence providing a new strategy for crystal engineering in two dimensions. Reference | Related Articles | Metrics

Select

Efficient CO2 Photoreduction into Solar Fuels over MoO3-x/COF S-Scheme Photocatalyst LIU Chuang, GAO Tengyuan, WANG Guohong, CHENG Qiang, WANG Kai Chemical Research in Chinese Universities    2025, 41 (4): 726-733.   DOI: 10.1007/s40242-025-5033-9 Abstract （542）            Knowledge map    Save The restricted electron transport and slow surface reaction kinetics are two fundamental limitations affecting the photocatalytic efficiency of covalent organic frameworks (COFs). To address these challenges and enhance charge separation, this study utilizes an in-situ growth strategy to incorporate MoO3-x into COF (denoted as BTTA), forming MoO3-x/COF composites (MOCOF). These composites demonstrate significantly enhanced solar fuel performance through photocatalytic CO2 reduction. In-situ irradiated X-ray photoelectron spectroscopy and electron spin resonance analyses confirm the presence of an S-scheme carrier transfer mechanism, which effectively spatially separates photogenerated carriers with substantial redox potential. The nanoarchitecture of MOCOF-2 demonstrates the capability to efficiently convert CO2 into valuable CO and CH4 fuels, achieving reduction rates of 8.7 and 4.6 μmol∙g-1∙h-1, respectively. This study provides a valuable reference for the rational design of COF-based S-scheme heterojunction photocatalysts aimed at solar fuel production. Reference | Related Articles | Metrics

Select

Thermal Annealing-modulated Ion Doping and Synaptic Behavior of Organic Electrochemical Transistors Based on Block Copolymers XIANG Chuan, JIANG Xingyu, Li Bin, JIANG Jichao, WANG Qi, SHI Cheng, DONG Xinyu, LIU Dianjue, XUE Di, ZHANG Jidong, HUANG Lizhen, CHI Lifeng Chemical Research in Chinese Universities    2025, 41 (5): 1037-1047.   DOI: 10.1007/s40242-025-5076-y Abstract （517）            Knowledge map    Save Organic electrochemical transistors (OECTs) garner significant attention in biosensing and neuromorphic computing applications owing to their high transconductance, low operating voltage, and biocompatibility. Among the various factors influencing OECTs performance and functionality, particularly synaptic behavior emulation, ion doping/dedoping kinetics play a pivotal role. However, precise control of ion dynamics remains challenging because of the complex interplay between material properties and microstructural characteristics. In this study, we demonstrate the modulation of the ion doping dynamics and synaptic behavior of OECTs based on hydrophilic-hydrophobic block copolymers (DPP-b-g2T-T) through thermal annealing. We investigate the correlations among segmental hydrophilicity/hydrophobicity, crystallinity, and ion transport kinetics. Our findings reveal that hydrophilic g2T-T segments enhance the ion doping efficiency, whereas hydrophobic DPP segments restrict ion transport. Thermal annealing reduces the ion doping/dedoping rates for both segments, particularly Au-gated OECTs. This phenomenon is attributed to the enhanced film crystallinity, which impedes ion transport, especially under the relatively weak gate control effect characteristic of Au. Leveraging the annealing-modulated ion doping/dedoping dynamics and prolonged retention time, we emulate short-term plasticity (STP) and long-term plasticity (LTP). This work establishes a strategy for optimizing OECTs synaptic performance through synergistic molecular design and thermal annealing, contributing to the advancement of neuromorphic technology. Reference | Related Articles | Metrics

Select

Developing Quantum Chemical Topology for Polypeptide Charge Distributions Using Kohn-Sham One-electron Potential GUO Xin, CONG Yunhong, ZHAO Jian, ZHAO Dongxia, YANG Zhongzhi Chemical Research in Chinese Universities    2025, 41 (5): 1121-1132.   DOI: 10.1007/s40242-025-5150-5 Abstract （485）            Knowledge map    Save We introduce a quantum chemical topology (QCT) approach using the Kohn-Sham one-electron potential (KSpot) as a scalar function, revealing unique spatial features of atoms in molecules and the chemical bonds. The KSpot and its electron force lines demonstrate that an atom is a 3D basin governed by its nucleus as an attractor. Notably, KSpot atomic charges exhibit less basis set dependence, whose physical reliability is further confirmed through accurate reproduction of electrostatic potentials and dipole moments. To assess performance, we systematically compared KSpot QCT atomic charges with six established methods (QTAIM, Hirshfeld, Mülliken, NPA, CHELPG, and MK) across 20 amino acid dipeptides. KSpot charges have strong correlations with QTAIM and Hirshfeld ones, with correlation coefficients of 0.9207 and 0.9160, respectively. Furthermore, we successfully parameterized the atom bond electronegativity equalization method (ABEEM) using KSpot QCT charges, achieving a good linear agreement between them. These results establish KSpot QCT as a robust tool for molecular structure analysis, electrostatic interaction studies, and force field development. Reference | Related Articles | Metrics

Select

Theoretical Studies on the Deacylation Stage of the Hydrolysis of PET Heptamer by PETase GUO Xuehui, ZHOU Yanzi, XIE Daiqian Chemical Research in Chinese Universities    2025, 41 (5): 1076-1083.   DOI: 10.1007/s40242-025-5133-6 Abstract （477）            Knowledge map    Save The extensive use and excellent durability of polyethylene terephthalate (PET) have caused a surge in plastic waste. The discovery of the Ideonella sakaiensis PETase (IsPETase) has opened up a promising avenue for PET bio-recycling, as it can effectively depolymerize PET into valuable monomers. In this work, we employed the M06-2X/MM-MD method (MM-MD: molecular mechanics-molecular dynamics) to study the deacylation reaction of a PET heptamer and reveal the structural features that influence the free energy barrier. This reaction proceeds in a stepwise manner, and the first step is rate-limiting. The energy barrier is 20.4 kcal/mol (1 kcal=4.18 kJ), higher than those for other PET substrates with shorter chains, which supports our previous finding that the deacylation becomes difficult with increasing PET chain length. The hydrogen bonds in the oxyanion hole and between His208 and Asp177 play an important role in the reaction mechanism. In addition, PET self-interaction increases the free energy barrier compared with the short oligomers. This work reveals the catalytic mechanism of PETase in degrading long-chain PET, aiming to promote the engineering of a critical class of enzymes in plastic recycling. Reference | Related Articles | Metrics

Select

Crystal Packing Factor-guided Design of Stress-resistant Alloying-type Anodes for Durable Sodium-ion Storage LV Zhuoran, LV Ximeng, DONG Wujie, HUANG Fuqiang Chemical Research in Chinese Universities    2025, 41 (5): 1092-1099.   DOI: 10.1007/s40242-025-5184-8 Abstract （476）            Knowledge map    Save Alloying-type anodes hold promise for sodium-ion batteries (SIBs) due to their high theoretical capacities, yet they suffer from severe capacity fading caused by large volume expansion during sodiation. Identifying a universal structural descriptor that links lattice chemistry with stress resistance and ion transport is therefore critical. Here, we introduce the crystal packing factor (PF) as a predictive metric and validate its effectiveness in layered bismuth compounds (BiOCl, Bi2O2S, and Bi2O2NCN) spanning a broad PF range. Bi2O2NCN, characterized by an atomically sparse and electronically conjugated [Bi2O2]2+-NCN2- layered framework with the lowest PF (0.613), markedly outperforms Bi2O2S (0.694) and BiOCl (0.763). Its open framework provides abundant interlayer free volume and weak steric constraints, thereby buffering mechanical strain and accelerating Na+ diffusion. First-principles calculations corroborate that Bi2O2NCN shows suppressed stress accumulation and a lower migration barrier of 0.18 eV compared to Bi2O2S and BiOCl. Experimentally, Bi2O2NCN delivers a high capacity of 486 mA·h·g-1 at 0.3 C (1 C=656 mA·g-1) and maintains 230 mA·h·g-1 after 6600 cycles at 15 C with 93% capacity retention. Multimodal structural characterizations further confirm a reversible conversion-alloying mechanism. These findings establish the crystal PF as a generalizable guideline for designing stress-resistant alloying-type anodes, offering a powerful pathway toward durable, high-performance SIBs. Reference | Related Articles | Metrics

Select

Lithium and Scattered Metals from Liquid Ores: A Roadmap for Future Extraction Technologies MA Xinyi, FU Yuan, LIU Jia Chemical Research in Chinese Universities    2025, 41 (6): 1294-1313.   DOI: 10.1007/s40242-025-5204-8 Abstract （470）            Knowledge map    Save Driven by the dual-carbon strategy and the artificial intelligence revolution, rare scattered metals, such as lithium, rubidium, and cesium have become critical strategic resources supporting new energy and high-tech industries. However, China’s high external dependency on these resources poses risks to supply security and geopolitical stability. Liquid mineral resources, such as salt lake brines, characterized by vast reserves, low extraction costs, and environmental friendliness, represent a crucial direction for future resource security. This review systematically summarizes mainstream and emerging technologies for extracting lithium and rare scattered metals from brines, including precipitation, solvent extraction, adsorption, membrane separation, and electrochemical methods. It focuses on analyzing the principles, application status, and research progress of related materials for each method. Among them, adsorption, membrane separation and electrochemical methods are widely studied due to their green and efficient characteristics. By comparing their advantages and limitations in terms of selectivity, energy consumption, environmental impact, and industrialization potential, the study outlines future trends in green, efficient, and low-energy consumption extraction technologies, providing technical support for China’s autonomous supply of strategic metal resources. Reference | Related Articles | Metrics

Select

Descriptors Assisted in Design High-performance Nonlinear Optical Materials with Donor-Acceptor Framework Systems LI Bo, GU Feng Long Chemical Research in Chinese Universities    2025, 41 (5): 1084-1091.   DOI: 10.1007/s40242-025-5114-9 Abstract （466）            Knowledge map    Save Descriptors can accelerate the search for high-performance nonlinear optical (NLO) materials. Herein, we constructed 48 donor-acceptor (D-A) skeleton systems based on intramolecular B-locking strategies involving TPA-TCN, TPA-CN-N4, and TPA-CN-N4-2Py. The calculated results demonstrated that the constructed D-A molecules can serve as potential NLO material candidates, and torsion angles between donor and acceptor units are concentrated in narrow ranges is beneficial to obtain the large first hyperpolarizability (β). Intriguingly, the desirable R2 reached to 0.95 for the TPA-TCN series, 0.96 for the TPA-CN-N4 series and 0.96 for the TPA-CN-N4-2Py series when torsion angles were served as features. Furthermore, when charge transfer and the excited energy of crucial states are used as features, several comprehensive descriptors have been also identified. And the favorable R2 values of 0.95 for the TPA-TCN series, 0.97 for the TPA-CN-N4 series, and 0.93 for the TPA-CN-N4-2Py series were achieved between these parameters and lgβ values. These high R2 values confirm that these parameters can be regarded as valuable features connecting them to β, aiding in the design of NLO materials with D-A architecture systems. Consequently, these findings provide novel insights into the relationships among torsion angles and β, which facilitates effort to identify high-performance NLO materials within D-A backbone systems tailored for specific application requirements. Reference | Related Articles | Metrics

Select

Chemical Research in Chinese Universities Vol.41 No.5 October 2025 Chemical Research in Chinese Universities    2025, 41 (5): 0-0.   Abstract （461）      PDF（pc） （694KB）（141）       Knowledge map    Save Related Articles | Metrics

Select

Effect of Tube Diameter and Tube Length on Confined Water in Nanotubes: A Molecular Dynamics Simulation Study YAN Zidi, ZHU Zhi, KONG Xiang-Yu, XIAO Hongyan, JIANG Lei Chemical Research in Chinese Universities    2025, 41 (5): 1056-1066.   DOI: 10.1007/s40242-025-5144-3 Abstract （452）            Knowledge map    Save The confined water in carbon nanotubes (CNTs) has an extremely fast transport rate, which has aroused great research interest. Previous studies have explored how various factors affect the structures and transport properties of confined water in CNTs. However, the fundamental understanding is still incomplete. Therefore, we studied confined water systems of different diameters and lengths in detail, and considered the effects of thermal fields and terahertz fields through molecular dynamics simulations. The simulation results revealed that the tube diameter mainly affected confined water structure; the tube length regulated the overall transport performance by adjusting the dipole flipping process and molecular translocation distance of confined water. Increasing the tube length led to a decrease in water flow, but enhanced the stability of transient unidirectional transport events. When the temperature rose, water molecules accelerated their movement, resulting in an increase in the system flow. Meanwhile, the increase in temperature caused the dipole flipping of confined water more frequently, thereby making the unidirectional transport unstable and affecting the system flux. Unlike the non-selectivity of the thermal effect, terahertz light could selectively enhance the transport of confined water. The research results are expected to promote a deeper understanding of confined water in CNTs. Reference | Related Articles | Metrics

Select

Generalized Breathing Orbital Valence Bond Approach YING Fuming, ZHOU Chen, WU Wei Chemical Research in Chinese Universities    2025, 41 (5): 1100-1105.   DOI: 10.1007/s40242-025-5172-z Abstract （451）            Knowledge map    Save We present a novel breathing orbital valence bond (BOVB) scheme, termed generalized BOVB (GBOVB), which constructs the wave function as a linear combination of valence bond self-consistent field (VBSCF) and its excited structures without requiring SCF orbital optimization. By applying different truncation levels to the excited configurations, multiple GBOVB variants are developed, offering flexible trade-offs between computational efficiency and accuracy. Benchmark tests reveal that GBOVB4 achieves the highest accuracy at a greater computational cost, while GBOVB4(D) provides the best balance between performance and efficiency. Notably, GBOVB overcomes convergence challenges of conventional BOVB methods when dealing with delocalized orbitals. Despite these advantages, limitations remain: excitations beyond double excitations may be important, and neglecting interactions between doubly excited structures in GBOVB4(D) can reduce accuracy, especially for systems with large active spaces. Reference | Related Articles | Metrics

Select

Intelligent Algorithm-guided Parameter Learning for the ABEEM Model MENG Peiran, YOU Zhuo, GUO Kaixuan, YU Chunyang, GONG Lidong, YANG Zhongzhi Chemical Research in Chinese Universities    2025, 41 (5): 1114-1120.   DOI: 10.1007/s40242-025-5153-2 Abstract （448）            Knowledge map    Save Accurate modeling of charge distribution plays a vital role in molecular simulations, electrostatic energy evaluation, and mechanistic analysis. The atom-bond electronegativity equalization method (ABEEM) provides a physically interpretable framework for computing atomic and electronic site charges by partitioning molecular space into atoms, bonds, and lone-pair regions. However, conventional ABEEM parameterization relies heavily on manual tuning, limiting its adaptability and predictive accuracy. In this work, an automated parameter learning strategy for ABEEM was proposed, guided by intelligent optimization algorithms and formulated within a goal programming framework. The framework systematically calibrates the key parameters of multiple types of charge sites. A chemically diverse training set including proteins, lipids, and nucleotides was constructed, and a dual-level objective function was designed to improve accuracy at both site and atomic levels. This approach significantly enhances the predictive performance and consistency of the ABEEM model across complex biomolecular systems. It also eliminates human bias and provides a scalable and generalizable pathway for force field development. Reference | Related Articles | Metrics

Select

Multicoated GO Nanocomposite Membranes with Long-term Stability in Aqueous Environment for Dye Removal ZHANG Hongfa, HUANG Chang, YANG Siyuan, XU Zimeng, LI Yi, WU Qingyun, XUE Ming Chemical Research in Chinese Universities    2025, 41 (5): 1208-1216.   DOI: 10.1007/s40242-025-5056-2 Abstract （448）            Knowledge map    Save Graphene oxide (GO)-based membranes have garnered significant attention in water purification and dye separation due to their electrostatic interactions arising from abundant functional groups and exceptional molecular sieving capabilities. However, challenges such as the inability to produce uniform GO membranes at an industrial scale and poor stability in an aqueous environment hinder their widespread application in industry. In this work, a scalable and easily adjustable technique is proposed to GO membrane with long-term stability in an aqueous environment by multilayer integration rod-coating with high-power UV reduction. A piece of multilayer graphene oxide membrane (MGM) with a size of 30 cm×30 cm with uniformity and efficiency can be easily formed. MGM demonstrates remarkable performance in dye separation, achieving a stable flux of 10.76 LMH·bar-1 [LMH: L/(m2·h); 1 bar=105 Pa] over more than 300 h of testing, along with a dye separation efficiency exceeding 95.0%. Moreover, the separation performance as well as the pore parameter can be flexibly modulated by changing the rod-coating times to adapt to the dye molecules under different conditions. The excellent performance of MGM paves the way for their large-scale industrial production in dye separation applications. Reference | Related Articles | Metrics

Select

Chemical Research in Chinese Universities Vol.41 No.6 December 2025 Chemical Research in Chinese Universities    2025, 41 (6): 0-0.   Abstract （440）      PDF（pc） （21679KB）（50）       Knowledge map    Save Related Articles | Metrics

Select

Prediction of the Assembly Process and Structure of Heteromultimeric Proteins via Multilevel Conformational Merging ZHANG Dinglin, LI Yan, LIU Ye, LI Guohui, CHU Huiying Chemical Research in Chinese Universities    2025, 41 (5): 1144-1156.   DOI: 10.1007/s40242-025-5157-y Abstract （438）            Knowledge map    Save Understanding the assembly pathways of heteromultimeric protein complexes is crucial for deciphering their functional mechanisms. However, traditional computational methods often struggle with the combinatorial NP-hard (non-deterministic polynomial-time hard) problem. This study employs a computational method, multilevel merge dock (MuMD), which uses a competition-based strategy to simulate the actual assembly process of heteromultimeric proteins. By avoiding the combinatorial NP-hard problem typically associated with the exhaustive conformation sampling, MuMD reduces the need to generate and evaluate a large number of conformations, thereby reducing computational costs while improving accuracy and efficiency. In the process, the ZDOCK scoring function is used to select optimal protein pair, followed by subsequent assembly using the roulette-wheel algorithm. Each component undergoes competition during the assembly process, with the subcomplex having the highest score taking priority in assembly steps. The results showed that MuMD can effectively simulate the dynamic assembly process of heteromultimeric protein complexes. Additionally, it accurately predicts the assembly pathway of the heteromultimeric protein complexes. Notably, MuMD method demonstrates significant advantages in accurately predicting the assembly pathways of complexes with fewer than 6 chains. This work provides an efficient and accurate tool for studying protein complex assembly. Reference | Related Articles | Metrics

Select

High-resolution and Tunable Red Indium Phosphide Quantum Dot Microlaser Arrays HE Ke, LI Hui, GUO Ning, WU Yuchen Chemical Research in Chinese Universities    2025, 41 (5): 1234-1238.   DOI: 10.1007/s40242-025-5147-0 Abstract （436）            Knowledge map    Save Quantum dot (QD) lasers exhibit exceptional promise in optical communication, laser display, and biomedical diagnostic applications. However, the toxicity of heavy metals in II-VI QDs has impeded their broader deployment. Herein, red-emitting InP QDs bearing a gradient ZnSeS alloy shell were synthesized to suppress Auger recombination and thereby attain a lasing threshold as low as 32.1 μJ/cm2. A capillary-bridge confined self-assembly method was employed to arrange these InP QDs into high-density micro-ring resonator arrays with resolutions exceeding 1000 ppi (ppi: proton pump inhibitor). Systematic variation of the microring diameter enabled modulation of the lasing mode structure, and single-mode lasing was realized in 6 μm rings under defined pumping conditions. This work establishes a heavy-metal- free platform for scalable, high-resolution quantum dot laser arrays. Reference | Related Articles | Metrics