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Zhonglin Cao

Bio: Zhonglin Cao is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Medicine & Nanopore. The author has an hindex of 4, co-authored 9 publications receiving 87 citations.

Papers
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Journal ArticleDOI
TL;DR: This work demonstrated that ultrathin Metal Organic Framework (MOF) is capable of efficiently rejecting ions while giving access to high water flux, and discovered perfect ion rejection rate by two-dimensional multi-layer MOF.
Abstract: Providing fresh and drinkable water is a grand challenge the world is facing today. Development in nanomaterials can create possibilities of using energy-efficient nanoporous materials for water desalination. In this work, we demonstrated that ultrathin conductive metal-organic framework (MOF) is capable of efficiently rejecting ions while giving access to high water flux. Through molecular dynamic simulation, we discovered perfect ion rejection rate by two-dimensional (2D) multilayer MOF. The naturally porous structure of 2D MOF enables significantly 3-6 orders of magnitude higher water permeation compared to that of traditional membranes. Few layers MOF membranes show 1 order of magnitude higher water flux compared to that of single-layer nanoporous graphene or molybdenum disulfide (MoS2) without the requirement of drilling pores. The excellent performance of 2D MOF membranes is supported by water permeation calculations, water density/velocity profiles at the pore, and the water interfacial diffusion near the pore. Water desalination performance of MOF offers a potential solution for energy-efficient water desalination.

102 citations

Journal ArticleDOI
TL;DR: In this paper, the discovery and application of two-dimensional (2D) nanoporous materials for water desalination has been discussed in many regions of the world, including India and China.
Abstract: Water desalination technologies are extensively utilized to solve water scarcity problems in many regions of the world. Discovery and application of two-dimensional (2D) nanoporous materials provid...

66 citations

Journal ArticleDOI
TL;DR: In this paper , a contrastive estimator maximizes the agreement of graph augmentations from the same molecule while minimizing the agreement between different molecules, which can improve the performance of GNNs on various molecular property benchmarks.
Abstract: Molecular Machine Learning (ML) bears promise for efficient molecule property prediction and drug discovery. However, labeled molecule data can be expensive and time-consuming to acquire. Due to the limited labeled data, it is a great challenge for supervised-learning ML models to generalize to the giant chemical space. In this work, we present MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks (GNNs), a self-supervised learning framework that leverages large unlabeled data (~10M unique molecules). In MolCLR pre-training, we build molecule graphs and develop GNN encoders to learn differentiable representations. Three molecule graph augmentations are proposed: atom masking, bond deletion, and subgraph removal. A contrastive estimator maximizes the agreement of augmentations from the same molecule while minimizing the agreement of different molecules. Experiments show that our contrastive learning framework significantly improves the performance of GNNs on various molecular property benchmarks including both classification and regression tasks. Benefiting from pre-training on the large unlabeled database, MolCLR even achieves state-of-the-art on several challenging benchmarks after fine-tuning. Additionally, further investigations demonstrate that MolCLR learns to embed molecules into representations that can distinguish chemically reasonable molecular similarities.

62 citations

Journal ArticleDOI
TL;DR: In this article , a one-step covalent functionalization of transition metal dichalcogenide (MoS2) nanosheets for membrane fabrication is reported, which is accomplished by simultaneous exfoliating and grafting the lithium-ion-intercalated MoS2 in organic iodide water solution.
Abstract: Transition metal dichalcogenide membranes exhibit good antiswelling properties but poor water desalination property. Here, a one‐step covalent functionalization of MoS2 nanosheets for membrane fabrication is reported, which is accomplished by simultaneous exfoliating and grafting the lithium‐ion‐intercalated MoS2 in organic iodide water solution. The lithium intercalation amount in MoS2 is optimized so that the quality of the produced 2D nanosheets is improved with homogeneous size distribution. The lamellar MoS2 membranes are tested in reverse osmosis (RO), and the functionalized MoS2 membrane exhibits rejection rates of >90% and >80% for various dyes (Rhodamine B, Crystal Violet, Acid Fuchsin, Methyl Orange, and Evans Blue) and NaCl, respectively. The excellent ion‐sieving performance and good water permeability of the functionalized MoS2 membranes are attributed to the suitable channel widths that are tuned by iodoacetamide. Furthermore, the stability of the functionalized MoS2 membranes in NaCl and dye solutions is also confirmed by RO tests. Molecular dynamics simulation shows that water molecules tend to form a single layer between the amide‐functionalized MoS2 layers but a double layer between the ethanol‐functionalized MoS2 (MoS2‐ethanol) layers, which indicates that a less packed structure of water between the MoS2‐ethanol layers leads to lower hydrodynamic resistance and higher permeation.

27 citations


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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations

Journal ArticleDOI
TL;DR: In this review, the development of ultrathin 2D nanosheets in the field of electrochemistry is introduced, and their unique dimensional advantages are highlighted.
Abstract: Metal-organic framework (MOF) and covalent organic framework (COF) nanosheets are a new type of two-dimensional (2D) materials with unique design principles and various synthesis methods. They are considered ideal electrochemical devices due to the ultrathin thickness, easily tunable molecular structure, large porosity and other unique properties. There are two common methods to synthesize 2D MOF/COF nanosheets: bottom-up and top-down. The top-down strategy mainly includes ultrasonic assisted exfoliation, electrochemical exfoliation and mechanical exfoliation. Another strategy mainly includes interface synthesis, modulation synthesis, surfactant-assisted synthesis. In this Review, the development of ultrathin 2D nanosheets in the field of electrochemistry (supercapacitors, batteries, oxygen reduction, and hydrogen evolution) is introduced, and their unique dimensional advantages are highlighted.

139 citations

Journal ArticleDOI
TL;DR: In this article, the authors classified the synthesis strategies of pure MOF membranes and MOF-based mixed matrix membranes and provided theoretical basis and technical guidance for realizing the large-scale application of MOF membrane in the field of oil-water separation.

123 citations

Journal Article
TL;DR: Li et al. as mentioned in this paper showed that Li-ion (de)intercalation occurs between interlayers in a sequential manner as evidenced by ex situ X-ray diffraction (XRD).
Abstract: MXenes, as an emerging family of conductive two-dimensional materials, hold promise for late-model electrode materials in Li-ion batteries. A primary challenge hindering the development of MXenes as electrode materials is that a complete understanding of the intrinsic storage mechanism underlying the charge/discharge behavior remains elusive. This article presents two key discoveries: first, the characteristics of the Ti₃C₂Tₓ structure can be modified systematically by calcination in various atmospheres, and second, these structural changes greatly affect Li-ion storage behavior, which reveals the mechanism for lithium storage in Ti₃C₂Tₓ MXene. Specifically, via ammonization, the interlayer spacing gets dilated and uniform, giving rise to only one redox couple. In stark contrast, there are two well-recognized redox couples corresponding to two interlayer spacings in pristine Ti₃C₂Tₓ MXene, in which Li-ion (de)intercalation occurs between interlayers in a sequential manner as evidenced by ex situ X-ray diffraction (XRD). Notably, the XRD diffraction peaks shift hardly in the whole range of charge/discharge voltage, indicating a zero-strain feature upon Li-ion (de)intercalation. Moreover, the diffusion-controlled contribution percentage to capacity inversely depends on the scan rate. The understanding suggests a new design principle of the MXene anode: reduced lateral size to shorten the diffusion path and dilated interlayer spacing.

81 citations

Journal ArticleDOI
TL;DR: In this paper, the discovery and application of two-dimensional (2D) nanoporous materials for water desalination has been discussed in many regions of the world, including India and China.
Abstract: Water desalination technologies are extensively utilized to solve water scarcity problems in many regions of the world. Discovery and application of two-dimensional (2D) nanoporous materials provid...

66 citations