Browse Articles

Quantum sensing with triplet pair states: A theoretical study

Molecular quantum sensors represent a promising frontier for the detection of nuclear magnetic resonance signals and alternating current magnetic fields at the nanoscale, potentially reaching single-proton sensitivity. Although the triplet states T̂ of molecular pentacene provide a viable sensing architecture, the triplet pair states T̂T̂ produced by singlet fission of pentacene dimers could enable more flexible quantum manipulations through entanglement. In this work, we model the quantum sensing efficacy of a spin-polarized quintet manifold 5T̂T̂0,±1 in a photoexcited pentacene dimer generated via intramolecular singlet fission. Using a Lindblad master equation approach, we simulate the evolution of the triplet-pair state under standard dynamical decoupling sequences—including spin echo, XY4, and XY8—and provide a direct performance comparison to the traditional pentacene monomer benchmark. While both architectures exhibit comparable sensitivity for isolated single-spin detection, our findings indicate that the dimer architecture provides a superior interaction cross section for detecting small ensembles of nuclear spins. Analytical expressions derived for fluorescence modulation demonstrate that sensitivity is optimized in the low-magnetic field regime (≤0.01 T) and scales with the number of pulses in the sensing protocol. This study establishes a theoretical baseline for utilizing high-spin multi-excitonic states as chemically tunable, high-sensitivity quantum probes.

White‐Light‐Excitable Deep‐Red/NIR Organic Afterglow Nanoparticles for High‐Contrast In Vivo Imaging

ABSTRACT Near‐infrared (NIR) organic afterglow probes are attractive for deep‐tissue, high‐contrast bioimaging, yet simultaneously achieving white‐light excitation, long‐lived NIR phosphorescence, and uniform nanoparticle fabrication remains challenging. Herein, we develop a bottom‐up route to lattice‐matched host–guest nanocrystals by incorporating a rigid phenylcarbazole host (BMC) with scaffold‐matched, extended‐conjugation guests (PyC or BPC). The resulting doped crystals show guest‐dominated deep‐red/NIR afterglow, with the longest‐wavelength vibronic band reaching 762 nm and can be activated by visible light up to 475 nm, delivering an ultralong lifetime of 126.1 ms and a phosphorescence quantum yield of up to 2.7%. Importantly, the intrinsic homogeneity of the lattice‐matched incorporation enables direct formation of monodisperse phosphorescent nanoparticles via simple bottom‐up nanoprecipitation, avoiding the size heterogeneity and material loss typically associated with top‐down crystal fragmentation. These nanoparticles exhibit negligible cytotoxicity and deliver bright, persistent deep‐red/NIR emission under white‐light excitation for high‐contrast in vivo imaging.

Ordered Hollow Sphere Array Nanoreactors for Direct Electroreduction of Diluted CO ₂ Into Ethylene

ABSTRACT Direct electroreduction of industrially diluted CO 2 into C 2 H 4 represents a promising route for sustainable energy conversion, yet the selectivity and current density of this process are fundamentally constrained by the insufficient reactant concentration and generation of *CO intermediates. Herein, we addressed this issue by designing an ordered hollow sphere array nanoreactor with Cu nanoparticle and Ni single atom as the tandem catalytic sites (Cu‐NP/Ni‐NC OHSpA) using a unique reverse templating protocol. Mechanistic studies demonstrate that *CO can be generated on Ni site and undergoes spillover to the neighboring Cu particle. Significantly, the ordered hollow sphere array serves as effective CO reservoir to enhance the *CO coverage and thereby promote the C‐C coupling to form C 2 H 4 . As a consequence, Cu‐NP/Ni‐NC OHSpA exhibits excellent electrocatalytic performance toward the conversion of diluted CO 2 (i.e., 15% CO 2 /Ar), affording a C 2 H 4 Faradaic efficiency (FE C2H4 ) of 57.5% with a partial current density (J C2H4 ) of 110 mA cm −2 .

Taming the Hydrogen‐Mediated Kinetic Switch for Sulfur‐Tolerant CO ₂ Electroreduction

ABSTRACT Direct electrochemical conversion of industrial flue gas offers a promising route to carbon neutrality, but it remains limited by trace sulfur dioxide (SO 2 , 10–400 ppm) impurities. These impurities cause rapid catalyst deactivation, particularly under the high reaction rates required for industrial application. Here, we introduce a hydrophobic molecular gate strategy to decouple impurity transport from catalyst deactivation. By regulating the interfacial water solvation structure and proton transfer pathways, this design creates a water‐deficient regime to lock the kinetic switch. As a result, SO 2 is isolated from the hydrogen‐mediated reduction, while the transient water required for efficient CO 2 conversion is preserved. When paired with a lattice‐strained copper catalyst, this architecture allows a scaled‐up 100 cm 2 membrane electrode assembly (MEA) to operate at a total current of 20 A for over 120 h, maintaining an ethylene (C 2 H 4 ) Faradaic efficiency (FE) >56% in simulated flue gas.

Buried‐Interface Iodine Redox Regulation for Durable All‐Perovskite Tandem Photovoltaics

ABSTRACT Tin–lead (Sn–Pb) mixed perovskites have propelled all‐perovskite tandem solar cells (APTSCs) beyond 30% efficiency, yet buried‐interface instability impedes commercialization. The ubiquitous PEDOT:PSS layer readily facilitates the oxidation of I − , and the subsequent diffusion of corrosive I 2 severely compromises device performance—a fundamental chemical degradation pathway that leaves unresolved. Here, we introduce 6‐amino‐2‐thiouracil (ATU) as a multifunctional additive that chemically targets this degradation pathway. Embedded within the PEDOT:PSS layer, the interaction between ATU and PSS contributes to alleviating the oxidation of I − while its C═S moiety actively reduces corrosive I 2 back to I − , establishing a dynamic iodine‐recycling mechanism that addresses the root chemical cause of instability. Concurrent defect passivation and crystallization modulation further enhance film quality. Benefiting from these synergistic effects, the optimized APTSCs achieve a champion efficiency of 29.29% (certified 28.79%) and exhibit significantly improved stability, maintaining over 85% of their initial efficiency after 500 h of maximum power point tracking. By targeting buried‐interface corrosive I 2 , this work provides a rational framework beyond conventional passivation for durable perovskite photovoltaics.

Reductive Activation of White Phosphorus to [P ₄ ] ^2– , [P ₂ ] ^2– , and a Formal P ^2– Radical by Rare‐Earth Dinitrogen Complexes

ABSTRACT Activation of white phosphorus (P 4 ) to smaller P n units by rare‐earth compounds remains a synthetic challenge. Here, we show that the rare‐earth dinitrogen complexes [{(Cp ttt ) 2  M} 2 (μ‐1,2‐N 2 )] (M = Y, Gd; Cp ttt  = 1,2,4‐tri( tert ‐butyl)cyclopentadienyl), reductively cleave P 4 to give a homologous series of phosphorus anions of decreasing nuclearity, that is, [{(Cp ttt ) 2  M} 2 (μ‐P 4 )] ( 1 M ), [{(Cp ttt ) 2  M} 2 (μ‐η 2 :η 2 ‐P 2 )] ( 2 M ), and [{(Cp ttt ) 2  M} 2 (μ‐P)] ( 3 M ). Structural, spectroscopic, and computational studies show that 1 M contains a bicyclobutane‐like [P 4 ] 2– ligand, whereas 2 M features a side‐on coordinated [P═P] 2– ligand, and 3 M comprises a monatomic P 2– ligand formulated as a phosphorus‐centered radical with S  = 1/2. The EPR spectrum of 3 Y confirms hyperfine coupling to 31 P and 89 Y, while magnetic measurements on 3 Gd reveal strong antiferromagnetic exchange between the Gd 3+ ions and the radical ligand. Density functional theory supports a three‐center π‐type M–P–M interaction in 3 M , with the unpaired spin localized primarily on phosphorus and only weak delocalization onto the metal centers. These findings represent progressive fragmentation of P 4 to diatomic and monatomic phosphorus anions by rare‐earth reagents, thereby extending the chemistry of multiply bonded phosphorus and persistent phosphorus radicals into the rare‐earth series.

Chemically Regulated STING‐Activating Prodrugs of Deoxyribose Cyclic Dinucleotides Elicit Robust Immune Activation and Durable Antitumor Immunity

ABSTRACT Derivatives of deoxyribose cyclic dinucleotides (dCDNs) displayed notable advantageous properties in the activation of STING pathway. The chirality of the phosphotriester of dCDN prodrugs may influence the stability, cellular permeability, bioactivity and duration, which remains inadequately explored through systematic evaluations in cellular and animal models. Herein, we isolated and characterized all three diastereoisomers of alkyne‐conjugated esterase‐sensitive dCDN prodrugs, and meticulously examined their difference in stability, cellular uptake and bioactivity. Within THP1 cells, the ( Rp,Rp ) diastereoisomer demonstrated the highest level of activation of STING pathway (EC 50 = 1.7 nM), and induced more robust and prolonged activation pulse than the ( Rp,Sp ) and ( Sp,Sp ) diastereoisomers. In murine models, prodrugs elicited significantly stronger stimulation in the development of an antitumor immune response compared to the parent CDN 3′,3′‐c‐di‐dAMP, as well as the clinically relevant STING agonist ADU‐S100. The ( Rp,Rp ) diastereoisomer exhibited the most pronounced antitumor activity in the context of intravenous administration, significantly suppressing tumor proliferation, extending the survival with a complete response (CR) rate of 90% in a mouse CT26 tumor model, and establishing long‐lasting tumor‐specific immunological memory. These findings underscore the importance of considering the chirality of phosphotriesters in the development of more effective, safer, and sustainable STING agonist in tumor immunotherapy.

Complete Linker Desymmetrization Enabled Construction of an eft‐Topological Zr(IV)‐MOF Comprising Two Types of Hexazirconium Nodes for Ammonia Capture

ABSTRACT Rational design and serendipitous discovery constitute the two wheels of molecular science. Despite the fruitful achievements of constructing metal‐organic frameworks from highly symmetric linkers under the guidance of reticular chemistry principles, the formulation of synthetic principles with unsymmetric organic linkers, while fundamentally important for targeting unexpected structures and functions, has been underdeveloped. Herein, we achieved a Zr(IV)‐based MOF (SJTU‐24) with a computationally modelled trinodal (3,4,8)‐connected eft topology where two types of Zr 6 secondary building units (SBUs) co‐exist, including an unprecedented 4‐connected concave coordination figure, through a complete linker desymmetrization approach. This topology, to our knowledge, has not been experimentally achieved in Zr‐based MOFs, highlighting the pivotal role of linker symmetry manipulation in the discovery of materials with non‐default topology. SJTU‐24 exhibits exceptional ammonia capture performance among Zr‐based MOFs, reaching 14.1 and 4.8 mmol/g adsorption capacity at 1 and 0.1 bar, respectively. Semi‐in situ Infrared (IR) and x‐ray photoelectron spectroscopic (XPS) studies decipher that both the Brønsted acidic hydroxyl sites in the Zr 6 SBUs and the monodentately‐coordinated carboxylate moieties in the linkers participate in the interactions with NH 3 . This work, thus provides a valuable insight into leveraging complete linker desymmetrization engineering to unlock non‐default and sophisticated structures with improved properties.

Non‐Dilute Synthesis of Macrodiolides and Macrotetrolides Enabled by Confinement Catalysis

ABSTRACT Macrodiolides are widespread motifs in functional molecules, yet their synthesis remains challenging. Existing methods typically still rely on high‐dilution conditions to suppress undesired oligomerization, limiting efficiency and scalability. Therefore, developing macrocyclization strategies under non‐dilute conditions remains a long‐standing goal. Herein, we report a confinement approach to address this challenge by utilizing the spatial restriction and conformational preorganization provided by the hexameric resorcin[4]arene capsule. Such supramolecular confinement enables the cyclization of readily accessible diols and diacyl chlorides to afford 18–32‐membered macrodiolides under non‐dilute conditions and without the need for slow‐addition procedures. Notably, the method also enables the one‐pot formation of 26–32‐membered macrotetrolides, a transformation that is difficult to achieve using conventional strategies, including high‐dilution conditions. Compared with established ring‐closing metathesis, this strategy offers higher efficiency, shorter synthetic routes, and access to more strained macrodiolides. Overall, these findings highlight the power of confinement catalysis for challenging macrocyclization reactions.

A simple Schiff base compound as mitigator for the destruction of C-steel in HCl aqueous solutions: practical and theoretical studies

Abstract The corrosion inhibition performance of N-(1-methylpyrrolidin-2-ylidene) benzo[d]thiazol-2-amine (MPBA) for carbon steel in 1.0 M HCl solution was systematically investigated using chemical and electrochemical techniques. The corrosion rate decreased markedly with increasing MPBA concentration. Inhibition efficiency increased progressively with inhibitor concentration, reaching values exceeding 97.0% at 5 mM and 298 K. The inhibition mechanism was primarily governed by the adsorption of MPBA molecules onto the carbon steel surface and was well described by the Langmuir adsorption isotherm. The negative values of the standard Gibbs free energy of adsorption (Δ G ads ) confirm the spontaneous nature of the adsorption process. Depending on temperature, Δ G ° ads values ranged from − 37.75 to − 36.20 kJ mol⁻¹, indicating a mixed physisorption–chemisorption mechanism. The observed decrease in the adsorption equilibrium constant ( K ads ) with increasing temperature can be attributed to the partial desorption of MPBA molecules from the carbon steel surface. Density functional theory (DFT) calculations combined with the conductor-like polarizable continuum model (CPCM), along with Monte Carlo and molecular dynamics simulations, further confirmed the strong adsorption affinity of MPBA toward the steel surface, thereby supporting its excellent corrosion inhibition performance.

Freezing‐Induced Spatial Confinement During Cryo‐Polymerization Enables Stable Intrinsic Luminescence in Hydrogels

ABSTRACT Intrinsic luminescence in polymer hydrogels is highly desirable for soft optoelectronic and information‐security applications, yet remains difficult to achieve under hydrated conditions, where clusterization‐triggered emission (CTE) is easily quenched by water due to disrupted intermolecular interactions. Here, we establish a facile and general strategy to overcome this limitation via directional freezing‐assisted cryo‐polymerization. The anisotropic growth of ice crystals imposes spatial confinement during network formation, driving dense chain packing and stabilizing amide‐based emissive clusters. Such structural confinement suppresses nonradiative decay and enables a robust CTE effect even at ultrahigh water content (∼90 wt%), effectively overcoming the long‐standing challenge of hydration‐induced quenching. The resulting polyacrylamide hydrogel exhibits stable blue emission, structural stability, excellent resistance to water‐induced quenching, and mechanical softness with elasticity and shape programmability, enabling rewritable and multilevel information encryption. More broadly, this work demonstrates that stable intrinsic luminescence in water‐rich soft materials can be achieved through structural confinement rather than molecular modification, providing a general design principle for CTE systems and opening new opportunities for integrating optical functionality with structural programmability in soft materials.

Stratapy: a tool for automated stratigraphic log visualisation

Abstract Stratigraphic logs are the fundamental interface between geological observations and scientific interpretation. Manual log visualisation is time-consuming and difficult to reproduce, yet existing digitisation tools are limited and often tailored to specific fields and applications, with many unable to provide core functions. We present stratapy: a Python package for rapid, high-quality log digitisation, designed to be accessible for non-programmers. The tool enables scientists across a range of disciplines to rapidly generate publication-quality stratigraphic logs with basic text- or spreadsheet-based inputs. We have designed stratapy to be accessible even to non-programmers while maintaining a high degree of flexibility in both style and function using a simple parameter-based customisation approach. We incorporate standardised lithological patterns and curated geological features and symbology, as well as automatic correlation with the chronostratigraphic column, the addition of sample locations, annotations and more. For more tailored visualisation, stratapy can easily assemble multi-panel or stratigraphically correlated logs to illustrate complex systems. With applications across research and industry, we create a standardised framework for log illustration and digitisation. This tool will modernise scientific workflows, improving the quality of stratigraphic logs and their interpretation, while contributing towards improved digital practices in the Earth sciences.

A neurocognitive interactive activation model of semantic priming in lexical decisions

Abstract This study introduces the sequential read-out model (SROM) to investigate the strategic and decision-making contributions to the semantic priming effect in a lexical-decision task (LDT). We use behavioral and fMRI data from two experiments ( n  = 32 and 31), which factorially manipulated the association strength, semantic similarity, and stimulus-onset-asynchrony. Using a leaky competing accumulator layer for lexical decisions, the SROM successfully accounted for behavioral data and showed that switching from short to long stimulus-onset-asynchrony changed the decision-making mode from competitive to independent race regime. We then used the individually estimated SROM parameters to predict the interindividual differences in BOLD responses to targets. We found that lexical-orthographic evidence modulated BOLD amplitudes in the left lingual gyrus, suggesting that it maintains lexico-orthographic evidence in working memory, which is then used for lexical decisions. The decision threshold, inhibition parameters and top-down semantic excitation predicted activation differences in the left inferior frontal gyrus, suggesting it regulates the decision process. Decision noise and top-down semantic excitation were associated with the left angular gyrus, supporting its involvement in evidence accumulation. Overall, the SROM provided mechanistic interpretations of brain activations in the regions involved in the semantically primed LDT, while accounting for associative semantic and strategic factors.

A machine learning-based framework for predicting hypertension using serum hematological factors

Real-time phase-dependent occupational radiation exposure analysis in full-endoscopic spine surgery

Fine-grained lung cancer object detection via dilated reparameterization and explicit positional gating optimization

Abstract Early detection and precise fine-grained radiologic classification of lung cancer are crucial for formulating clinical treatment plans. However, existing computer-aided diagnosis (CAD) systems are mostly limited to binary nodule classification or treat radiologic feature classification and clinical TNM staging as isolated tasks. To address technical challenges such as drastic scale variations of tumors, subtle inter-class differences, and complex anatomical backgrounds, this paper proposes an end-to-end fine-grained lung cancer object detection algorithm based on an improved YOLO architecture. The proposed model accomplishes a complex 7-class detection task within a unified framework, encompassing normal tissue, three major non-small cell lung cancer (NSCLC) subtypes, and specific anatomical locations combined with TNM stages. Specifically, a Dilated Reparameterization Block (C3k2_DRB) is designed in the backbone to effectively enlarge the receptive field via multi-scale dilated convolutions, enhancing feature extraction for multi-scale tumors without introducing inference overhead. Meanwhile, an Explicit Positional Gating Optimization attention mechanism (C2PSA_EPGO) is introduced to adaptively focus on the most discriminative lesion textures and suppress irrelevant background noise. Furthermore, a dynamic upsampling strategy (DySample) is employed in the feature fusion stage to achieve content-aware spatial alignment, maximally preserving the morphological boundary details of the lesions. Experimental results on a complex lung cancer dataset comprising 1886 images demonstrate that the improved model achieves 97.6% Precision and 99.2% mean Average Precision (mAP@0.5) while maintaining extremely low parameters (2.46 M) and computational cost (6.3 GFLOPs). Compared with mainstream object detection algorithms, the proposed method exhibits significant advantages in localization precision and fine-grained classification performance, demonstrating the potential of the proposed architectural enhancements for complex, fine-grained medical vision tasks.

Large-scale flood susceptibility mapping along major tributaries of the Nile River system in Sudan using convolutional neural network

Abstract Every fall season, Sudan experiences devastating floods that result in significant fatalities, displacement of populations, and severe disruptions to agricultural and economic activities. The 2020 floods were particularly catastrophic, reaching the highest Nile River levels in over a century and affecting more than 800,000 people. To the best of the authors’ knowledge, this study represents one of the first large-scale, data-driven flood susceptibility assessments for Sudan using deep Convolutional Neural Network (CNN) model. Twelve conditioning factors spanning topographical, hydrological, geological, and anthropogenic parameters were systematically analyzed. The flood inventory dataset was obtained from the Humanitarian Data Exchange (HDX), comprising geospatially verified flood polygons compiled from remote sensing and field observations. A five-fold cross-validation strategy was implemented to ensure model robustness, yielding a classification accuracy of 97% and demonstrating reliable generalizability across spatial partitions. The analysis generated probability maps with susceptibility values ranging from zero to 1, delineating three discrete risk zones: High, Medium, and Low susceptibility. Results reveal that very high susceptibility zones are concentrated along immediate river corridors, the Khartoum metropolitan confluence area, and low-lying Quaternary alluvial plains in Jazirah and Sennar states, where Sudan’s most critical agricultural production occurs. The susceptibility maps provide essential decision-support tools for evidence-based urban planning, agricultural management, and water resources development, enabling targeted risk reduction strategies that can protect lives, livelihoods, and development investments.

Comparative mitogenomics of Ocnus glacialis reveals lineage-specific evolutionary rates and complex gene rearrangements in Dendrochirotida

mRNA vaccine design targeting Merkel cell polyomavirus for immunotherapy of Merkel cell carcinoma

Research on the influence mechanism of particle size on the migration and deposition law of weathered crust elution-deposited rare earth ores