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Adsorption

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Assessing subvisible particle risks in monoclonal antibodies: insights from quartz crystal microbalance with dissipation, machine learning, and in silico analysis.

mAbs
Throughout the lifecycle of biopharmaceutical development and manufacturing, monoclonal antibodies (mAbs) are subjected to diverse interfacial stresses and encounter various container surfaces. These interactions can cause the formation of subvisible...

Integrated learning framework for enhanced specific surface area, pore size, and pore volume prediction of biochar.

Bioresource technology
Specific surface area, pore size, and pore volume are essential biochar properties. Optimization typically reduces yield by focusing on per gram of biochar. This work introduces new indicators and an integrated model to balance quality and quantity, ...

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...

Development of hybrid robust model based on computational modeling and machine learning for analysis of drug sorption onto porous adsorbents.

Scientific reports
This study investigates the utilization of three regression models, i.e., Kernel Ridge Regression (KRR), nu-Support Vector Regression ([Formula: see text]-SVR), and Polynomial Regression (PR) for the purpose of forecasting the concentration (C) of a ...

Biohybrid microrobots with a Spirulina skeleton and MOF skin for efficient organic pollutant adsorption.

Nanoscale
Wastewater treatment is a key component in maintaining environmental health and sustainable urban life, and the rapid development of micro/nanotechnology has opened up new avenues for more efficient treatment processes. This work developed a novel bi...

Lab-made open-source controlled robotic workstation for sorbent-based dispersive microextraction of low-volume samples.

Analytica chimica acta
BACKGROUND: Despite microextraction techniques have gained prominence over traditional extraction ones, they usually involve repetitive and tedious manual procedures. Full or partial automation could help alleviate this drawback. Even though commerci...

Electrochemical activation of alum sludge for the adsorption of lead (Pb(II)) and arsenic (As): Mechanistic insights and machine learning (ML) analysis.

Bioresource technology
Alum sludge (AlS) has emerged as an effective adsorbent for anionic contaminants, with traditional activation methods like acid/base treatments and calcination employed to enhance its adsorption capacity. However, these approaches encounter significa...

Modeling PFAS Sorption in Soils Using Machine Learning.

Environmental science & technology
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...

Discovering Ultra-Stable Metal-Organic Frameworks for CO Capture from A Wet Flue Gas: Integrating Machine Learning and Molecular Simulation.

Environmental science & technology
The rapid increase in atmospheric CO, arising from anthropogenic sources, has posed a severe threat to global climate and raised widespread environmental concern. Metal-organic frameworks (MOFs) are promising adsorbents to potentially reduce CO emiss...

Predicting biomolecule adsorption on nanomaterials: a hybrid framework of molecular simulations and machine learning.

Nanoscale
The adsorption of biomolecules on the surface of nanomaterials (NMs) is a critical determinant of their behavior, toxicity, and efficacy in biological systems. Experimental testing of these phenomena is often costly or complicated. Computational appr...