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Zhou, Jian

Publications and source records attributed to Zhou, Jian.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Achieving High-Yield Conversion of Janus Transition Metal Dichalcogenides on Diverse Substrates

Janus transition metal dichalcogenides (TMDCs) with intrinsic broken mirror symmetry and vertical dipole moment provide an additional degree of freedom to manipulate material symmetry down to atomic-layer thickness. However, despite advances in synthesis strategies, fundamental understanding of this atomic substitution process remains limited, which has impeded their implementation in advanced devices. Here, by using a room-temperature atomic-layer substitution (RT-ALS) strategy, we systematically investigate the critical factors facilitating the high-yield conversion of Janus TMDCs on diverse substrates. Combining Raman spectroscopy probes, X-ray photoelectron spectroscopy (XPS) measurements, and density functional theory (DFT) calculations, we demonstrate that substrates with enhanced electron doping or larger surface polarity substantially benefit the conversion of Janus TMDCs reaching a near-unity yield. Intriguingly, the strong affinity between Janus TMDCs and substrates (e.g., Au) brings about abnormal Raman spectroscopic phenomena. These findings highlight the significance of substrates in achieving the reliable synthesis of Janus two-dimensional materials with improved homogeneity on various substrates. In addition, this takes us one step closer to utilizing Janus TMDCs as a versatile platform in next-generation optoelectronic devices, sensors, and quantum technologies.

Doping↗
DOE OSTI2024

Enhanced Interfacial Electron Transfer in Photocatalyst-Natural Enzyme Coupled Artificial Photosynthesis System: Tuning Strategies and Molecular Simulations

Laccase is capable of catalyzing a vast array of reactions, but its low redox potential limits its potential applications. The use of photocatalytic materials offers a solution to this problem by converting absorbed visible light into electrons to facilitate enzyme catalysis. Herein, MIL-53(Fe) and NH 2 -MIL-53(Fe) serve as both light absorbers and enzyme immobilization carriers, and laccase is employed for solar-driven chemical conversion. Electron spin resonance spectroscopy results confirm that visible light irradiation causes rapid transfer of photogenerated electrons from MOF excitation to T1 Cu(II) of laccase, significantly increasing the degradation rate constant of tetracycline (TC) from 0.0062 to 0.0127 min -1 . Conversely, there is only minimal or no electron transfer between MOF and laccase in the physical mixture state. Theoretical calculations demonstrate that the immobilization of laccase's active site and its covalent binding to the metal-organic framework surface augment the coupled system's activity, reducing the active site accessible from 27.8 to 18.1 Å. In conclusion, the constructed photo-enzyme coupled system successfully combines enzyme catalysis’ selectivity with photocatalysis's high reactivity, providing a promising solution for solar energy use.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Comparative verification of hydro-mechanical fracture behavior: Task G of international research project DECOVALEX–2023

Numerical simulations become a necessity when experimental approaches cannot cover the required physical and time scale of interest. One of such area is a simulation of long-term host rock behaviors for nuclear waste disposal and simulation tools involved in the assessment must go through rigorous validation tests. The DECOVALEX project (Development of COupled models and their VAlidation against EXperiments) is dedicated to this purpose by international participants. This work is part of the ongoing phase DECOVALEX–2023 (D–2023, Task G) particularly aiming to simulate fracture behaviors under various conditions. Here, in this study, we cross-verified a variety of numerical methods including continuous and discontinuous approaches against four benchmark exercises with emphasis on numerical accuracy and parameterization of the various numerical approaches. The systematic inter-comparisons of test cases highlight advantages and disadvantages of the different numerical models. Numerical details on discretization effects (e.g. mesh density and orientation) and domain size were investigated in detail for practical applications. It became evident that meticulous attention to mesh resolution and domain size is imperative for achieving accurate numerical simulations, even for static cracks. Moreover, when comparing numerical methods to closed-form solutions for static cracks, all models successfully reproduced the maximum crack opening but encountered challenges near the crack tips. Finally, the paper discusses how to convert between and therefore compare parameters of various numerical approaches. Our benchmark studies reveal that each model necessitates a distinct number of parameters, even in simple scenarios like static crack aperture benchmarks. It is generally more practical to employ fewer parameters to mitigate model over-parameterization and enhance experimental feasibility.

58 GEOSCIENCES↗
DOE OSTI2023

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

A resilient network recovery framework against cascading failures with deep graph learning

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. Here this work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗
DOE OSTI2022

Computational study of inertial migration of prolate particles in a straight rectangular channel

Inertial migration of spherical particles has been investigated extensively using experiments, theory, and computational modeling. Yet, a systematic investigation of the effect of particle shape on inertial migration is still lacking. Herein, we numerically mapped the migration dynamics of a prolate particle in a straight rectangular microchannel using smoothed particle hydrodynamics at moderate Reynolds number flows. After validation, we applied our model to 2:1 and 3:1 shape aspect ratio particles at multiple confinement ratios. Their effects on the final focusing position, rotational behavior, and transitional dynamics were studied. In addition to the commonly reported tumbling motion, for the first time, we identified a new logrolling behavior of a prolate ellipsoidal particle in the confined channel. This new behavior occurs when the confinement ratio is above an approximate threshold value of K = 0.72. Our microfluidic experiments using cell aggregates with similar shape aspect ratio and confinement ratio confirmed this new predicted logrolling motion. In this study, we also found that the same particle can undergo different rotational modes, including kayaking behavior, depending on its initial cross-sectional position and orientation. Furthermore, we examined the migration speed, angular velocity, and rotation period as well as their dependence on both particle shape aspect ratio and confinement ratio. Our findings are especially relevant to the applications where particle shape and alignment are used for sorting and analysis, such as the use of barcoded particles for biochemical assays through optical reading, or the shape-based enrichment of microalgae, bacteria, and chromosomes.

42 ENGINEERING↗
DOE OSTI2022

Exclusive double quarkonium production and generalized TMDs of gluons

Being the “mother distributions” of all types of two-parton correlation functions, generalized transverse momentum dependent parton distributions (GTMDs) have attracted a lot of attention over the last years. We argue that exclusive double production of pseudoscalar quarkonia (η c or η b ) in nucleon-nucleon collisions gives access to GTMDs of gluons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Crystallizing Kagome Artificial Spin Ice

Artificial spin ices are engineered arrays of dipolarly coupled nanobar magnets. They enable direct investigations of fascinating collective phenomena from their diverse microstates. However, experimental access to ground states in the geometrically frustrated systems has proven difficult, limiting studies and applications of novel properties and functionalities from the low energy states. In this work, we introduce a convenient approach to control the competing diploar interactions between the neighboring nanomagnets, allowing us to tailor the vertex degeneracy of the ground states. We achieve this by tuning the length of selected nanobar magnets in the spin ice lattice. We demonstrate the effectiveness of our method by realizing multiple low energy microstates in a kagome artificial spin ice, particularly the hardly accessible long range ordered ground state—the spin crystal state. Our strategy can be directly applied to other artificial spin systems to achieve exotic phases and explore new emergent collective behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Outsourced hearing in an orb-weaving spider that uses its web as an auditory sensor

Hearing is a fundamental sense of many animals, including all mammals, birds, some reptiles, amphibians, fish, and arthropods. The auditory organs of these animals are extremely diverse in anatomy after hundreds of millions of years of evolution, yet all are made up of cellular tissue and are morphologically part of the bodies of animals. Here, we show that hearing in the orb-weaving spider Larinioides sclopetarius is not constrained by the organism’s body but is extended through outsourcing hearing to its extended phenotype, the proteinaceous, self-manufactured orb web. We find that the wispy, wheel-shaped orb web acts as a hyperacute acoustic antenna to capture the sound-induced air particle movements that approach the maximum physical efficiency better than the acoustic responsivity of all previously known eardrums. By sensing the motion of web threads, the spider remotely detects and localizes the source of an incoming airborne acoustic wave, such as those emitted by approaching prey or predators. By outsourcing its acoustic sensors to its web, the spider is released from body size constraints and permits the araneid spider to increase its sound-sensitive surface area enormously, up to 10,000 times greater than the spider itself. The spider also enables the flexibility to functionally adjust and regularly regenerate its external "eardrum" according to its needs. The outsourcing and supersizing of auditory function in spiders provides unique features for studying extended and regenerative sensing and designing novel acoustic flow detectors for precise fluid dynamic measurement and manipulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Influence of the Anions on the Interaction Energy between Water and Ionic Liquids

It is essential to understand the interaction energy between water and ionic liquids (ILs) in search of ILs for dehumidification applications. In this paper, the intermolecular interaction energy between water and 1-ethyl-3-methylimidazolium ([EMIM])-based ILs was investigated. The vapor-liquid equilibrium data were first measured for solutions of [EMIM][BF 4 ], [EMIM][N(CN) 2 ], [EMIM][CF 3 SO 3 ], and [EMIM][CH 3 SO 3 ] with water molar fractions of 8–95 % at temperatures of 303–343 K. The IL-IL and water-IL intermolecular interaction energies were determined by using the correlated non-random two-liquid model. The results revealed that fluorine atoms in anions reduce the attraction energy between IL and water, and thus, decrease the water affinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Uranium In Situ Electrolytic Deposition with a Reusable Functional Graphene-Foam Electrode

Nuclear fission produces 400 GWe which represents 11% of the global electricity output. Uranium is the essential element as both fission fuel and radioactive waste. Therefore, the recovery of uranium is of great importance. In this study, an in situ electrolytic deposition method to extract uranium from aqueous solution is reported. A functionalized reduced graphene oxide foam (3D-FrGOF) is used as the working electrode, which acts as both a hydrogen evolution reaction catalyst and a uranium deposition substrate. The specific electrolytic deposition capacity for U(VI) ions with the 3D-FrGOF is 4560 mg g –1 without reaching saturation, and the Coulombic efficiency can reach 54%. Moreover, reduction of the uranium concentration in spiked seawater from 3 ppm to 19.9 ppb is achieved, which is lower than the US Environmental Protection Agency uranium limits for drinking water (30 ppb). Furthermore, the collection electrode can be efficiently regenerated and recycled at least nine times without much efficiency fading, by ejecting into 2000 ppm concentrated uranium solution in a second bath with reverse voltage bias. All these findings open new opportunities in using free-standing 3D-FrGOF electrode as an advanced separation technique for water treatment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

In this report computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO 2 -NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.

molecular fingerprint↗
DOE OSTI2021

Autonomous nondestructive evaluation of resistance spot welded joints

The application of non-destructive evaluation approaches has attracted strong interests in modern automotive industries. Here, we present an autonomous deep-computing framework to analyze raw videos from infrared systems and to predict weld nugget shape and size with unprecedented accuracy and speed. In a comprehensive training and testing experiment with 90 videos (seven sets of welding material stack-ups), a new method was developed to assemble sufficient datasets for neural network training. Our framework successfully predicts all the nugget shapes with F1 scores that range from 0.84 to 0.92. The total training time on Nvidia DGX station takes less than 10 min for each set of welding material stack-up. The real inference time of an individual dataset (with 30 video frames) takes about 0.005 s. The procedure and methods developed in the study can be applied to other image-based weld property prediction, as well as other manufacturing processes. Furthermore, our well-trained neural networks take limited memory resources (2.3 MB) and are suitable for embedded microprocessors for in-situ welding quality control as edge computing within an intelligent welding framework.

42 ENGINEERING↗
DOE OSTI2021

Layer number dependent ferroelasticity in 2D Ruddlesden–Popper organic-inorganic hybrid perovskites

Ferroelasticity represents material domains possessing spontaneous strain that can be switched by external stress. Three-dimensional perovskites like methylammonium lead iodide are determined to be ferroelastic. Layered perovskites have been applied in optoelectronic devices with outstanding performance. However, the understanding of lattice strain and ferroelasticity in layered perovskites is still lacking. Here, using the in-situ observation of switching domains in layered perovskite single crystals under external strain, we discover the evidence of ferroelasticity in layered perovskites with layer number more than one, while the perovskites with single octahedra layer do not show ferroelasticity. Density functional theory calculation shows that ferroelasticity in layered perovskites originates from the distortion of inorganic octahedra resulting from the rotation of aspherical methylammonium cations. The absence of methylammonium cations in single layer perovskite accounts for the lack of ferroelasticity. These ferroelastic domains do not induce non-radiative recombination or reduce the photoluminescence quantum yield.

36 MATERIALS SCIENCE↗