AIMC Topic: Polymers

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Machine learning analysis based on deep learning for fatigue diagnostics in carbon fiber reinforced polymers.

PloS one
Fatigue-induced degradation in Carbon Fiber Reinforced Polymer (CFRP) structures poses a critical challenge in long-term structural health monitoring (SHM) applications. In this study, a hybrid deep learning framework is proposed for fatigue state cl...

HepatoAI: Machine-Learning-Assisted Nano-enhanced Point-of-Care System for Personalized Precise Diagnosis of Hepatocellular Carcinoma.

Nano letters
Early diagnosis significantly improves survival rates for hepatocellular carcinoma (HCC), yet traditional methods face limitations, including specialized instruments/personnel and prolonged reporting cycles. While lateral flow immunoassay (LFA) offer...

Polymer-Functionalized Liposomes as Universal Nanocarriers for Drug Delivery: Single Particle Insights on Size-Dependent Performance and Intracellular Behavior.

ACS applied materials & interfaces
Nanomedicine requires smart delivery systems that are precise, robust, and universal. While liposomes are established vehicles in drug delivery, their full potential is challenged by limited stability, leakage, insufficient response, and limited insi...

From Bits to Bonds: High-Throughput Virtual Screening of Ribonucleic Acid Nanocarriers Using a Combinatorial Approach of Machine Learning and Molecular Dynamics.

Journal of the American Chemical Society
The implementation of high-throughput methods for fuelling the design of effective nanocarriers for RNA delivery remains challenging. Traditional experimental screening is resource-intensive, while purely computational approaches face limitations, su...

LiteBoost: a lightweight and explainable boosting model for predicting polymer density from SMILES data.

Journal of computer-aided molecular design
Accurately predicting polymer density from SMILES strings remains challenging due to the small size, high noise, and chemically diversity of typical datasets. We introduce LiteBoost, a deliberately minimalist gradient boosting model that employs shal...

Multifunctional Ag-PDA@PCM composite eutectogel based electronic skin for personal thermal management and a machine learning assisted wearable sensor.

Journal of materials chemistry. B
Inspired by the perception and temperature regulation functionalities of human skin, multifunctional electronic skin (E-skin) for human motion detection and personal thermal management has attracted great attention. Here, we design an E-skin with str...

Dual Embedding: A Fine-Tuned Language Model Approach for Accurate Polymer Glass Transition Temperature Prediction.

Journal of chemical information and modeling
Recent years have witnessed major advances in polymer informatics, yet accurately predicting polymer properties, such as the glass transition temperature (), remains a challenge. Language models like BERT have been leveraged to derive embeddings from...

Polymer-Functionalized Carbon Nanotube Sensors for Volatile Organic Compound Signal Exchange and Bioinspired Molecular Communication.

ACS sensors
Conventional electromagnetic communication systems face limitations in dense environments, including high energy consumption, signal attenuation, and interference. To overcome these challenges, we present a bioinspired molecular communication (MC) pl...

Multistep Machine Learning Pipeline For Polymeric Nanoparticle Design.

AAPS PharmSciTech
Integrating machine learning (ML) into nanotechnology represents a promising strategy for rational design and accelerated development of drug delivery systems. However, studies in this field are scarce and face methodological and interpretative probl...

Joule Heating-Driven Modulation of Analyte Partitioning in Chemically Diverse, Conducting Composite Sensor Arrays: A New Approach for Active Sensing in Machine Olfaction.

ACS sensors
Animals adapt to dynamic olfactory environments through active sensing behaviors like sniffing, which create a dynamic baseline to detect new odors. In this work, we explore the use of Joule heating of individual sensors as an efficient thermal modul...