UNS: Collaborative Research: Non-Membrane, Low Temperature and Low Emission Water Desalination Using Directional Solvent

UNS:合作研究:使用定向溶剂的非膜、低温、低排​​放海水淡化

基本信息

  • 批准号:
    1510826
  • 负责人:
  • 金额:
    $ 24.85万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-07-01 至 2018-06-30
  • 项目状态:
    已结题

项目摘要

1510826/1512113Luo / ShahProject Overview:Water scarcity is among the most serious challenges faced by the world today. Desalination has emerged as a potential solution. This collaborative project will examine a novel water desalination technology which does not use membranes.Current water desalination technologies are either evaporation-based or membrane-based, and they are costly and energy intensive, and also contribute to global-warming CO2 emissions. The proposed research will be driven by the hypothesis that the water solubility in directional solvents can be tuned by varying their molecular structures. Monte Carlo and molecular dynamics simulations will be performed to calculate the phase-equilibria of directional solvents with salt and water as a function of temperature. The knowledge of interactions, obtained from the simulations, between the functional groups and water will form the basis of a correlation between the chemical structure and directionality of water and salt solubilities in the solvent, enabling rational design of high-performance directional solvents. According to the extracted trend, high throughput experimental screening of promising directional solvents will be performed to identify highly efficient directional solvents. Based on the directional solvents, a lab-scale continuous desalination system will be designed and demonstrated.
1510826/1512113 Luo/Shah项目概述:缺水是当今世界面临的最严重挑战之一。海水淡化已成为一种潜在的解决方案。这个合作项目将研究一种不使用膜的新型水淡化技术。目前的水淡化技术要么基于蒸发,要么基于膜,它们成本高昂,能源密集型,而且还会导致全球变暖的二氧化碳排放。这项拟议的研究将受到这样一个假设的推动,即通过改变定向溶剂的分子结构可以调节其在水中的溶解度。蒙特卡罗和分子动力学模拟将被用来计算定向溶剂与盐和水作为温度的函数的相平衡。从模拟中获得的官能团与水之间相互作用的知识将形成化学结构与水和盐在溶剂中的溶解度之间的相关性的基础,从而能够合理设计高性能的定向溶剂。根据提取的趋势,将进行高通量的定向溶剂的高通量实验筛选,以确定高效的定向溶剂。以定向溶剂为基础,设计并演示了实验室规模的连续海水淡化系统。

项目成果

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Tengfei Luo其他文献

Quantum annealing for combinatorial optimization: a benchmarking study
用于组合优化的量子退火:一项基准测试研究
  • DOI:
    10.1038/s41534-025-01020-1
  • 发表时间:
    2025-05-16
  • 期刊:
  • 影响因子:
    8.300
  • 作者:
    Seongmin Kim;Sang-Woo Ahn;In-Saeng Suh;Alexander W. Dowling;Eungkyu Lee;Tengfei Luo
  • 通讯作者:
    Tengfei Luo
Thermal transport in thermoelectrics from first-principles calculations
根据第一性原理计算热电学中的热传输
  • DOI:
  • 发表时间:
    2012
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Keivan Esfarjani;Junichiro Shiorai;Takuma Shiga;Zhiting Tian;Tengfei Luo;Gang Chen
  • 通讯作者:
    Gang Chen
Environmental protein corona on nanoplastics altered the responses of skin keratinocytes and fibroblast cells to the particles
纳米塑料上的环境蛋白冠改变了皮肤角质形成细胞和成纤维细胞对颗粒的反应
  • DOI:
    10.1016/j.jhazmat.2025.138722
  • 发表时间:
    2025-08-15
  • 期刊:
  • 影响因子:
    11.300
  • 作者:
    Kayla Simpson;Leisha Martin;Shamus L. O’Leary;John Watt;Seunghyun Moon;Tengfei Luo;Wei Xu
  • 通讯作者:
    Wei Xu
Inverse binary optimization of convolutional neural network in active learning efficiently designs nanophotonic structures
基于主动学习的卷积神经网络逆二值化优化有效设计纳米光子结构
  • DOI:
    10.1038/s41598-025-99570-z
  • 发表时间:
    2025-04-30
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Jaehyeon Park;Zhihao Xu;Gyeong-Moon Park;Tengfei Luo;Eungkyu Lee
  • 通讯作者:
    Eungkyu Lee
Quantum-Inspired Genetic Algorithm for Designing Planar Multilayer Photonic Structure
用于设计平面多层光子结构的量子启发遗传算法
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhihao Xu;Wenjie Shang;Seongmin Kim;Alexandria Bobbitt;Eungkyu Lee;Tengfei Luo
  • 通讯作者:
    Tengfei Luo

Tengfei Luo的其他文献

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{{ truncateString('Tengfei Luo', 18)}}的其他基金

Collaborative Research: Material Simulation-driven Electrolyte Designs in Intermediate-temperature Na-K / S Batteries for Long-duration Energy Storage
合作研究:用于长期储能的中温Na-K / S电池中材料模拟驱动的电解质设计
  • 批准号:
    2341995
  • 财政年份:
    2024
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
Developing and Understanding Thermally Conductive Polymers by Combining Molecular Simulation, Machine Learning and Experiment
通过结合分子模拟、机器学习和实验来开发和理解导热聚合物
  • 批准号:
    2332270
  • 财政年份:
    2024
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
ISS: Plasmonic Bubble Enabled Nanoparticle Deposition under Micro-Gravity
ISS:微重力下等离子气泡实现纳米颗粒沉积
  • 批准号:
    2224307
  • 财政年份:
    2022
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
US-Japan Joint Workshop on Thermal Transport, Materials Informatics and Quantum Computing
美日热传输、材料信息学和量子计算联合研讨会
  • 批准号:
    2124850
  • 财政年份:
    2021
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
Discover and Understand Microporous Polymers for Size-sieving Separation Membranes using Active Learning
使用主动学习发现和了解用于尺寸筛分分离膜的微孔聚合物
  • 批准号:
    2102592
  • 财政年份:
    2021
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Dynamics of Nanoparticles in Light-Excited Supercavitation
EAGER:合作研究:光激发超空化中纳米粒子的动力学
  • 批准号:
    2040565
  • 财政年份:
    2020
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
Collaborative Research: Using molecular functionalization to tune nanoscale interfacial energy and momentum transport
合作研究:利用分子功能化来调节纳米级界面能量和动量传输
  • 批准号:
    2001079
  • 财政年份:
    2020
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Continuing Grant
Collaborative Research: Chemically Modified, Plasma-Nanoengineered Graphene Nanopetals for Spontaneous, Self-Powered and Efficient Oil Contamination Remediation
合作研究:化学改性、等离子体纳米工程石墨烯纳米花瓣用于自发、自供电和高效的石油污染修复
  • 批准号:
    1949910
  • 财政年份:
    2020
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
Collaborative Research: Understanding the Synergistic Effect of Graphene Plasmonics and Nanoscale Spatial Confinement on Solar-Driven Water Phase Change
合作研究:了解石墨烯等离子体和纳米尺度空间约束对太阳能驱动水相变的协同效应
  • 批准号:
    1937923
  • 财政年份:
    2020
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant
Highly Sensitive Multiplexed Nanocone Array for Point-of-Care Pan-Cancer Screening
用于护理点泛癌症筛查的高灵敏度多重纳米锥阵列
  • 批准号:
    1931850
  • 财政年份:
    2019
  • 资助金额:
    $ 24.85万
  • 项目类别:
    Standard Grant

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    $ 24.85万
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