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1,688 records · Page 46

SimH 2 : an integrated techno-economic modeling framework for hydrogen pipeline infrastructure and network optimization

Large-scale hydrogen (H 2 ) pipeline transport design and network optimization have seldom been reported due to the lack of a cost model accounting for the relationship between transport cost and hydrogen mass flow rate. Here, this work introduced a system-level cost model for hydrogen pipeline transport at supercritical state and integrated it with an existing CO 2 pipeline network tool, SimCCS, for hydrogen-specific pipeline design and optimization. The Intermountain West (I-West) region of the U.S., historically dependent on fossil fuel-based economies, is chosen to demonstrate the capabilities of our H 2 pipeline cost model and transport network optimization platform called SimH 2 . Two scenarios are examined: one where the pipeline is not allowed to pass through disadvantaged communities and the other where it is permitted. The results highlight that incorporating disadvantaged-community constraints lead to longer pipeline routes and increased transport costs, reflecting the trade-offs involved in equitable infrastructure development. It is demonstrated that the newly developed SimH 2 tool not only enables the efficient design of H 2 transportation pipelines but also optimizes the network by accounting for local terrain and the presence of disadvantaged areas.

08 HYDROGEN

Progress and Perspectives: Zirconium Electrodeposition from Different Electrolytes

Zirconium (Zr) possesses outstanding properties, including exceptional chemical resistance and a high melting point, and is therefore desirable for use in a wide variety of challenging environments, such as in nuclear reactors and the chemical processing industry. To minimize the amount of Zr required for any given application, developing methods for generating metallic Zr coatings is highly advantageous. Owing to Zr’s highly negative reduction potential, electrodeposition in traditional solvents at near ambient temperatures remains challenging and thus not well understood. Due to the extreme conditions required to deposit this metal, extensive work has been conducted in molten salt electrolytes, however the broad applicability of this methodology is limited due to its corrosivity. The primary focus of this article is to present an overview of Zr’s electrochemical behavior and to consolidate the efforts of researchers in exploring electrodeposition techniques for Zr involving aqueous, organic, ionic liquid, deep eutectic, and molten salt solvents. With this information, we highlight trends across solvent systems and opportunities for future research.

42 ENGINEERING

Improved Protein Semi-Synthesis Enables Biophysical Studies of Thioamide Destabilization of β-Sheet Interactions

Abstract Thioamides are natural post-translational modifications of the peptide backbone and can be introduced synthetically to probe protein folding or functionalize peptides for translational applications. In this work, we demonstrate that thioamide-containing peptides with C-terminal thioesters can be efficiently generated using Knorr pyrazole activation and used in subsequent native chemical ligation reactions to generate thioamide-containing proteins. We compare this method to acyl azide activation and find that both routes provide similar yields. We also investigate ultrasound-mediated desulfurization of the ligation site cysteine for potential advantages over chemical radical initiators. Scaling up our syntheses allows us to study thioamide perturbations to the β-sheet region of the B1 domain of protein G (GB1) as well as β-strand interactions in amyloid fibrils of the Parkinson’s disease protein α-synuclein. In both contexts, we observe dramatic destabilization of the β-sheet networks, manifested in decreased GB1 thermal stability and altered folding and slowed aggregation of α-synuclein. These findings illustrate the impact that a single atom substitution can have on cooperative hydrogen-bonding networks and prompt future study of both systems.

Yanagawa, Evan S. K. [University of Pennsylvania ,

Cation valency in water-in-salt electrolytes alters the short- and long-range structure of the electrical double layer

Highly concentrated aqueous electrolytes (termed water-in-salt electrolytes, WiSEs) at solid-liquid interfaces are ubiquitous in myriad applications including biological signaling, electrosynthesis, and energy storage. This interface, known as the electrical double layer (EDL), has a different structure in WiSEs than in dilute electrolytes. Here, we investigate how divalent salts [zinc bis(trifluoromethylsulfonyl)imide, Zn(TFSI) 2 ], as well as mixtures of mono- and divalent salts [lithium bis(trifluoromethylsulfonyl)imide (LiTFSI) mixed with Zn(TFSI) 2 ], affect the short- and long-range structure of the EDL under confinement using a multimodal combination of scattering, spectroscopy, and surface forces measurements. Raman spectroscopy of bulk electrolytes suggests that the cation is closely associated with the anion regardless of valency. Wide-angle X-ray scattering reveals that all bulk electrolytes form ion clusters; however, the clusters are suppressed with increasing concentration of the divalent ion. To probe the EDL under confinement, we use a Surface Forces Apparatus and demonstrate that the thickness of the adsorbed layer of ions at the interface grows with increasing divalent ion concentration. Multiple interfacial layers form following this adlayer; their thicknesses appear dependent on anion size, rather than cation. Importantly, all electrolytes exhibit very long electrostatic decay lengths that are insensitive to valency. It is likely that in the WiSE regime, electrostatic screening is mediated by the formation of ion clusters rather than individual well-solvated ions. This work contributes to understanding the structure and charge-neutralization mechanism in this class of electrolytes and the interfacial behavior of mixed-electrolyte systems encountered in electrochemistry and biology.

Science & Technology - Other Topics

Chromium versus Aluminum: Impact of Nickel Alloy Composition and Interfacial Kinetics on High-Temperature Passivating Oxide Formation

High-temperature corrosion resistance depends critically on the formation of a passivating surface oxide, which is highly sensitive to alloy composition and structure. Such details often elude experimental investigation, and simplified analytical models fail to provide a truly chemical view of passivating oxide evolution. Here, we explicitly compare the fundamental chemistry of Cr and Al as prototypical passivating elements in Ni alloys by directly simulating competing reaction and diffusion processes within the oxide film using kinetic Monte Carlo and density functional theory. We find that the origin and expression of passivating behavior during early-stage thermal oxidation are qualitatively different between the two alloy systems. Ni–Cr alloys feature a sudden onset of passivation associated with a sharp phase transition upon Cr enrichment that directly couples oxidation kinetics to phase transformation behavior. In contrast, Ni–Al alloys display more continuous oxide phase variation with Al enrichment, ultimately resulting in a lower composition threshold for passivation and a thinner passivating layer. In addition, we elucidate the nonobvious role of metal exchange within the alloy near the oxide boundary, which fundamentally alters film composition and passivating behavior. Furthermore, our results have key implications for engineering improved corrosion-resistant alloys, both in terms of compositional variation and processing.

Alloys

Direct Measurement of Cl − Activity in Metal Chloride Molten Salts using a Cl 2 /Cl − Electrode

Molten metal chloride salts are promising candidates for advanced heat transfer fluids in generation IV nuclear reactors and beyond. The activity of the chloride ion in the salt has a large influence on the redox characteristics of the corresponding molten salt. There exists a knowledge gap for the direct measurement of chlorobasicity (Lewis basicity) in molten-salt mixtures. Here, the focus of this work was to develop a Cl 2 /Cl − electrode for the direct measurement of chloride activity in molten metal-chloride salt mixtures. The LiCl–KCl eutectic system was utilized as the reference melt to determine the change in chloride ion activity as increasing concentrations of MgCl 2 are added to the LiCl–KCl eutectic working electrode. The results of the measurements indicated a reduction in chloride ion activity as the concentration of magnesium chloride increased, consistent with the complexation of free chlorides by Lewis acidic magnesium cationic species. The Temkin model was used to estimate the thermodynamic properties of MgCl 4 2− complex.

Chloride

N-Doped Graphene (N-G)/MOF(ZIF-8)-Based/Derived Materials for Electrochemical Energy Applications: Synthesis, Characteristics, and Functionality

In recent years, graphene-type materials originating from metal–organic frameworks (MOFs) or integrated with MOFs have exhibited notable performances across various applications. However, a comprehensive understanding of these complex materials and their functionalities remains obscure. While some studies have reviewed graphene/MOF composites from different perspectives, due to their structural–functional intricacies, it is crucial to conduct more in-depth reviews focusing on specific sets of graphene/MOF composites designed for particular applications. In this review, we thoroughly investigate the syntheses, characteristics, and performances of N-G/MOF(ZIF-8)-based/derived materials employed in electrochemical energy conversion and storage systems. Special attention is given to realizing their fundamental functionalities. The discussions are divided into three segments based on the application of N-G/ZIF-8-based/derived materials as electrode materials for batteries, electrodes for electrochemical capacitors, and electrocatalysts. As electrodes for batteries, N-G/MOF(ZIF-8) materials can mitigate issues like an electrode volume expansion for Li-ion batteries and the ‘shuttle effect’ for Li-S batteries. As electrodes for electrochemical capacitors, these materials can considerably improve the ion transfer rate and electronic conductivity, thereby enhancing the specific capacitance while maintaining the structural stability. Also, it was observed that these materials could occasionally outperform standard platinum-based catalysts for the electrochemical oxygen reduction reaction (ORR). The reported electrochemical performances and structural parameters of these materials were carefully tabulated in uniform units and scales. Through a critical analysis of the present synthesis trends, characteristics, and functionalities of these materials, specific aspects were identified that required further exploration to fully utilize their inherent capabilities.

Electrochemistry

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability

Rinse-Free, Sodium-Efficient Synthesis of O3-Type Layered Oxide Materials Enabled by Acetate Precursors

Sodium-ion batteries (SIBs) are a sustainable alternative to lithium-ion systems for global electrification, with O3-type layered oxide cathodes offering high specific capacity and feasibility of scalable synthesis. Industrial co-precipitation synthesis of these cathodes typically uses transition metal sulfates, requiring extensive water rinsing to remove Na 2 SO 4 impurities, a process that consumes significant water and risks residual inactive phases if incomplete. Here, this work introduces a rinse-free, resource-efficient approach using metal acetate precursors. Residual sodium acetate in non-rinsed precursors decomposes during sintering to generate Na 2 CO 3 in situ, partially substituting an external sodium resource (e.g., NaOH and Na 2 CO 3 ) and reducing its consumption by ∼18–20%. Phase-pure O3-Na 1.0 Ni 1/3 Fe 1/3 Mn 1/3 O 2 (NFM111) cathodes synthesized via this method exhibit microstructure and electrochemical performance comparable to rinsed sulfate-derived counterparts, with initial capacities of 141 mAh g −1 at C/20 (7.5 mA g −1 ). By eliminating rinsing and minimizing sodium reagent use, this acetate-based route enhances sustainability and scalability of layered oxide production for SIBs.

acetate vs. sulfate

Adsorptive behavior of poly (vinylidene fluoride) membranes for the recovery of lignin-derived hydrophobic deep eutectic solvents

Abstract Recently, membrane technology has gained significant traction as an energy-efficient alternative to traditional thermal processes for solvent recovery. Deep eutectic solvents (DESs) have emerged as sustainable alternatives to conventional organic solvents, yet a systematic methodology for selecting compatible membrane materials for their recovery remains underdeveloped. This study established a predictive framework for membrane material selection in hydrophobic DES applications using Hansen Solubility Parameters (HSP) with inverted criteria targeting materials with relative energy difference (RED) values greater than 1.0. Flat sheet membranes were fabricated via the non-solvent induced phase separation (NIPS) technique. Four NIPS fabricated polymer membranes were evaluated: polysulfone, cellulose acetate, polyvinylidene fluoride (PVDF) fabricated with polyethylene glycol (PEG) as a pore-forming agent, and polybenzimidazole (PBI). The HSP approach successfully predicted membrane-solvent compatibility, with polysulfone (RED = 0.6) and cellulose acetate (RED = 0.9) dissolving completely within 24 h, while PVDF (RED = 1.9) and PBI (RED = 1.1) maintained structural integrity throughout a 7-day exposure period. Furthermore, PVDF demonstrated superior performance with minimal weight gain (3.0%), hydrophobic surface characteristics (122° water contact angle), and enhanced mechanical properties following DES exposure. Comprehensive chemical and morphological characterization confirmed PVDF’s chemical stability and revealed a surface-selective interaction mechanism involving simultaneous PEG (pore-forming agent) extraction and DES component adsorption. Adsorption kinetics followed pseudo-first-order behavior with reversible characteristics, best described by the Temkin isotherm model (R² = 0.9987). PVDF membranes-maintained separation functionality with average lignin rejection (75.2 ± 7.69%) and demonstrated filtration permeability of 2.0 ± 0.34 LMH/bar. This methodology provides a rational approach for membrane selection in emerging solvent systems, contributing to the advancement of sustainable separation technologies for DES-based biomass processing applications.

Science & Technology - Other Topics

Photosynthetic capacity is reduced by warming but unaffected by elevated CO2 in seedlings of five boreal tree species

Abstract Increasing atmospheric CO2 concentrations fuel global warming, with boreal regions warming at a faster rate than many other areas. Boreal forests are an important component of the global carbon cycle, yet we have little data on photosynthetic responses of boreal trees to elevated CO2 (EC) and warming. We grew seedlings of 5 widespread North American boreal tree species (from Betula, Larix, Picea, and Pinus) under current (410 ppm) or elevated (750 ppm) CO2 and either ambient (+0 °C) or increased (+4 °C or +8 °C) temperature, then measured photosynthetic traits over a range of leaf temperatures. Our results were generally consistent across species: photosynthetic capacity (maximum rates of Rubisco carboxylation, Vcmax, and electron transport, Jmax) was unaffected by EC but decreased under +8 °C warming. Accordingly, net photosynthesis measured at the growth CO2 concentration (Agrowth) was reduced under warming and increased under EC. The thermal optimum for Agrowth (ToptA) increased by ∼1.8 °C with EC but increased with warming in only two species. In contrast, the activation energies and thermal optima for Vcmax and Jmax, which are used to estimate photosynthesis in Earth System Models, were unaffected by growth environment. There were a few interactions between growth, CO2, and warming. These results suggest increased photosynthesis of widespread boreal tree species under EC may be offset by future reductions in photosynthetic capacity related to warming. We also show that the temperature sensitivities of parameters used to estimate global photosynthesis in large-scale models are generally unaffected by simulated climate change in these species.

Plant Sciences

Reconstruction and Dissolution of Copper Catalysts during Electrocatalytic Nitrate Reduction

Copper-based electrocatalysts are widely explored for electrochemical nitrate remediation, yet their stability under operating conditions remains poorly understood. While nanoscale and subnanoscale Cu motifs are known to restructure during the nitrate reduction reaction (NO 3 RR), how these transformations translate into irreversible material loss remains unclear. Here, we quantify Cu dissolution during NO 3 RR as a function of catalyst architecture and electrolyte chemistry using two model systems: single-atom Cu (Cu 1 ) and Cu nanoparticles (Cu NP ). Time-resolved leaching measurements, integrated with in situ X-ray absorption spectroscopy (XAS), reveal measurable Cu loss for both catalysts during NO 3 RR. Dissolution is concentrated at the initiation of electrolysis, coinciding with rapid restructuring, and depends strongly on morphology, with Cu NP consistently exhibiting greater Cu loss than Cu 1 . In situ XAS reveals that Cu 1 forms transient metallic clusters under reduction that largely redisperse upon returning to open-circuit voltage, whereas Cu NP undergoes reduction of an oxidized surface layer accompanied by sustained Cu loss during electrolysis. Notably, the presence of nitrate significantly intensifies restructuring and Cu loss, highlighting the critical role of electrolyte composition. Furthermore, these findings establish a direct link between electrochemical restructuring and Cu dissolution, unveiling electrolyte-dependent interactions as key determinants of catalyst durability in electrochemical nitrate conversion.

36 MATERIALS SCIENCE

Coexistence of Synchronization and Stochasticity in Thermally Coupled Mott Oscillators

Synchronization is conventionally regarded as a mechanism for suppressing variability and enforcing order in coupled systems, from pendula and lasers to neurons and electronic oscillators. Here, we show that synchronization can also embed stochasticity at finer scales. We observe this phenomenon in thermally coupled VO 2 neuristors, where robust in-phase synchronization at the microsecond scale coexists with spike onset fluctuations at the nanosecond scale, with no fixed leader. The coexistence of order and disorder originates from stochastic domain-level physics of the insulator–metal and metal–insulator transitions, where local variations in transition temperature drive cycle-to-cycle randomness in nucleation, percolation, and relaxation. A stochastic domain model reproduces this effect by generating synchronized spike trains with random lead–lag jitter, and experimental interspike interval statistics confirm the persistence of fine-scale variability despite macroscopic phase locking. These findings establish that synchronization and stochasticity can coexist within the same physical platform, revealing hidden disorder within collective order. Furthermore, this insight reframes synchronization as not purely deterministic, but as a universal context where microscopic variability can persist, with implications for electronics, cryptography, and the fundamental physics of order–disorder coexistence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Improved nylon polymerization using amide diads

Nylons, a major class of synthetic polyamides, are widely used due to their excellent mechanical strength, thermal stability, and chemical resistance. Conventional nylon production relies on the polymerization of lactams or stoichiometric nylon salts. However, applying these approaches to unconventional precursors such as bio-derived glutaric acid produces polymers with low molecular weight and limited applications. To address these challenges, we demonstrated that chemically-synthesized nylon diads enable the production of higher-molecular-weight polyamides compared with traditional salts. We then identified a biosynthetic approach using amide synthetases to convert unprotected bifunctional substrates into nylon-relevant diads. Using a cofactor regeneration system, enzymatic diad synthesis was scaled to produce sufficient material for laboratory-scale characterization and solid-state polymerization. Amide synthetases demonstrated broad substrate scope, catalyzing the regioselective assembly of diverse nylon-relevant diacids, diamines, and ω-amino acids. This strategy offers a novel route to synthesize challenging nylon monomers and advances production of bioderived nylons.

Qian, Liangyu [Oak Ridge National Laboratory (ORNL

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark

Polycarbonate‐Based Solid‐Polymer Electrolytes for Solid‐State Sodium Batteries

Solid-polymer electrolytes comprised of polypropylene carbonate (PPC) and varied sodium bis(fluorosulfonyl)imide (NaFSI) salt concentrations are investigated for implementation as a conductive solid polymer electrolyte into solid-state cathode composites utilizing a sodium-layered oxide active material. The ionic conductivity generally increases with NaFSI salt content, reaching ≈1 mS cm −1 at 80 °C at the highest salt concentration (PPC:NaFSI = 0.5:1). Through an all-in-one slurry casting method, Na 2/3 Ni 1/3 Mn 2/3 O 2 cathode composites are fabricated in which the dispersed PPC electrolyte acts as the primary binder. Enabled by a bilayer polymer electrolyte system, cycling performance with the PPC cathode electrolyte is optimized with respect to salt concentration and anode material. The best cyclability is achieved with a moderate salt concentration electrolyte (PPC:NaFSI = 5:1), showcasing an initial capacity of 83 mA h g −1 with a remarkable 80% capacity retention after 150 cycles at C/5 rate and 60 °C. The superior performance of the lower salt concentration electrolyte is attributed to better electrochemical stability, as confirmed by linear sweep voltammetry and online electrochemical mass spectrometry measurements. In conclusion, these results underscore the potential of carbonate-based polymer electrolytes and the importance of balancing electrolyte conductivity and stability in cell design.

25 ENERGY STORAGE

Seasonal variation of the surface cross-shelf exchange in the northern South China Sea: a Lagrangian perspective

Previous studies on cross-shelf exchange, predominantly adopted an Eulerian perspective, struggled to identify water sources and pathways. Using a high-resolution regional ocean modeling system (ROMS) and Lagrangian particle tracking, this study systematically investigates the seasonal variation and dynamics of surface cross-shelf exchange in the northern South China Sea (NSCS) from a Lagrangian perspective. Based on daily released 30-day drifter trajectories we identify the key pathways, source regions for surface cross-shelf exchange, revealing pronounced seasonal variability. Results show the surface cross-shelf exchange generally following monsoon-driven Ekman transport. However, local dynamics, especially topographic modulation, can outweigh the expected Ekman-driven transport, producing surface exchange patterns opposite to that predicted from the prevailing winds. Topographic effects vary across different scales. In the coastal waters of western Guangdong during winter, despite downwelling-favorable winds, the modulation of alongshore currents by island topography induces an eastward pressure gradient. This gradient, through geostrophic balance, drives offshore flows opposite to wind-driven Ekman onshore transport. Furthermore, the eastern widened shelf exhibits a distinct seasonal variation of cross-shelf exchange, with strong offshore transport (opposite to the direction of Ekman transport) in winter and exceedingly weak exchange in summer. Analysis of the underlying mechanisms reveals that this winter offshore transport is primarily attributed to geostrophic flows driven by surface pressure gradient that is jointly modulated by the Kuroshio intrusion and local widened shelf topography, and enhanced by cumulative submesoscale processes. In summer, a persistent and strong along-isobath jet acts as a dynamic barrier, effectively suppressing the exchange. These findings highlight the important role of topography in regulating surface material transport, and have important implications for predicting the advection and dispersion of plankton or oil spills over the continental shelf influenced by monsoon.

Hao, Dongliang