AIMC Topic: Metal-Organic Frameworks
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An Intelligent Prediction Model for the Synthesis Conditions of Metal-Organic Frameworks Utilizing Artificial Neural Networks Enhanced by Genetic Algorithm Optimization.
Journal of chemical information and modeling
Jan 19, 2025
In the field of emerging materials, metal-organic frameworks (MOFs) have gained prominence due to their unique porous structures, showing versatility in gas adsorption, storage, separation, and liquid processes. However, their decomposition, collapse...
Deep Learning for the Accurate Prediction of Triggered Drug Delivery.
IEEE transactions on nanobioscience
Jan 2, 2025
The need to mitigate the adverse effects of chemotherapy has driven the exploration of innovative drug delivery approaches. One emerging trend in cancer treatment is the utilization of Drug Delivery Systems (DDSs), facilitated by nanotechnology. Nano...
MOF-Based Biomimetic Enzyme Microrobots for Efficient Detection of Total Antioxidant Capacity of Fruits and Vegetables.
Small (Weinheim an der Bergstrasse, Germany)
Dec 26, 2024
Green and efficient total antioxidant capacity (TAC) detection is significant for healthy diet and disease prevention. This work first proposed the concept of TAC colorimetric detection based on microrobots. A novel metal-organic framework (MOF)-base...
Bioinspired Iron Porphyrin Covalent Organic Frameworks-Based Nanozymes Sensor Array: Machine Learning-Assisted Identification and Detection of Thiols.
ACS applied materials & interfaces
Dec 12, 2024
Given the crucial role of thiols in maintaining normal physiological functions, it is essential to establish a high-throughput and sensitive analytical method to identify and quantify various thiols accurately. Inspired by the iron porphyrin active c...
Exploiting Metal-Organic Frameworks for Vinylidene Fluoride Adsorption: From Force Field Development, Computational Screening to Machine Learning.
Environmental science & technology
Sep 1, 2024
Metal-organic frameworks (MOFs) represent a distinctive class of nanoporous materials with considerable potential across a wide range of applications. Recently, a handful of MOFs has been explored for the storage of environmentally hazardous fluorina...
A MOF-on-MOF heterostructure ratiometric/colorimetric dual-mode fluorescence sensor based on support vector machine for detecting tetracyclines in animal-derived foods.
Food chemistry
Jul 31, 2024
The misuse of tetracyclines in livestock production poses significant health risks. Thus, establishing convenient detection methods to replace complex laboratory tests for food safety is crucial. In this study, a heterostructure Zn-BTC/IRMOF-3 (denot...
Classifying and Predicting the Thermal Expansion Properties of Metal-Organic Frameworks: A Data-Driven Approach.
Journal of chemical information and modeling
Jun 26, 2024
Metal-organic frameworks (MOFs) are versatile materials for a wide variety of potential applications. Tunable thermal expansion properties promote the application of MOFs in thermally sensitive composite materials; however, they are currently availab...
Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.
Nanoscale
May 9, 2024
Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography and mass spectrometry, have limitations for fast screening due to their limited availability, operational complexity, and high cost. As potential repla...
The drug loading capacity prediction and cytotoxicity analysis of metal-organic frameworks using stacking algorithms of machine learning.
International journal of pharmaceutics
Apr 15, 2024
Metal-organic frameworks (MOFs) have shown excellent performance in the field of drug delivery. Despite the synthesis of a vast array of MOFs exceeding 100,000 varieties, certain formulations have exhibited suboptimal performance characteristics. The...
Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis.
ACS sensors
Mar 12, 2024
A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identificati...
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