AIMC Topic: Polymers

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Machine learning-guided performance prediction of forward osmosis polymeric membranes for boron recovery.

Water research
Efficient recovery of boron is one of the crucial strategies of sustainably extracting valuable resource from water. It however still remains a key technological challenge to efficiently predict boron recovery from unconventional water resources such...

Enhancing the Predictive Performance of Molecularly Imprinted Polymer-Based Electrochemical Sensors Using a Stacking Regressor Ensemble of Machine Learning Models.

ACS sensors
The performance of electrochemical sensors is influenced by various factors. To enhance the effectiveness of these sensors, it is crucial to find the right balance among these factors. Researchers and engineers continually explore innovative approach...

Data-Driven Modeling and Design of Sustainable High Tg Polymers.

International journal of molecular sciences
This paper develops a machine learning methodology for the rapid and robust prediction of the glass transition temperature (Tg) for polymers for the targeted application of sustainable high-temperature polymers. The machine learning framework combine...

Machine Learning for Quantitative Prediction of Protein Adsorption on Well-Defined Polymer Brush Surfaces with Diverse Chemical Properties.

Langmuir : the ACS journal of surfaces and colloids
Polymer informatics has attracted increasing attention because machine learning can establish quantitative structure-property relationships in polymer materials. Understanding and controlling protein adsorption on polymer surfaces are crucial for var...

Hierarchical Crack Engineering-Enabled High-Linearity and Ultrasensitive Strain Sensors.

ACS sensors
Growing imperative for intelligent transformation of electro-ionic actuators in soft robotics has necessitated self-perception for accurately mapping their nonlinear dynamic responses. Despite the promise of integrating crack-based strain sensors for...

Comparative immobilization of 30 PFAS mixtures onto biochar, clay, nanoparticle, and polymer derived engineered adsorbents: Machine learning insights into carbon chain length and removal mechanism.

Journal of hazardous materials
Per- and polyfluoroalkyl substances (PFAS) are a group of fluorinated chemicals that cause potential risk in PFAS-impacted soil and water. The adsorption efficiency of 30 PFAS mixtures using different adsorbents in environmentally relevant concentrat...

Utilizing machine learning for predicting drug release from polymeric drug delivery systems.

Computers in biology and medicine
Polymeric drug delivery systems (PDDS) play a crucial role in controlled drug release, providing improved therapeutic outcomes. However, formulating PDDS and predicting their release profiles remain challenging due to their complex structures and the...

Antifreezing Ultrathin Bioionic Gel-Based Wearable System for Artificial Intelligence-Assisted Arrhythmia Diagnosis in Hypothermia.

ACS nano
Cardiovascular disease (CAD) is a major global public health issue, with mortality rates being significantly impacted by cold temperatures. Stable and reliable electrocardiogram (ECG) monitoring in cold environments is crucial for early detection and...

Development of a Wearable Sleeve-Based System Combining Polymer Optical Fiber Sensors and an LSTM Network for Estimating Knee Kinematics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...

Enhanced Sensitivity and Versatile Detection: Dual-Sized Microsphere-Type Pressure Sensors for Soft Robotics and Wearable Electronics.

ACS applied materials & interfaces
The development of pressure sensors with enhanced sensitivity, expanded working range, and versatile yet decoupling detection capabilities is critical for advancing robotics and medical applications. This work presents a novel pressure sensor design ...