Results 211 to 220 of about 1,491,227 (305)

Technoeconomic and sustainability analysis of batch and continuous crystallization for pharmaceutical manufacturing

AIChE Journal, EarlyView.
Abstract In pharmaceutical industries, continuous manufacturing methods have already been well established to improve productivity and process intensification. However, to better understand the trade‐offs of continuous crystallizers over the existing batch production systems, a robust technoeconomic cost and sustainability analysis is necessary to ...
Jungsoo Rhim, Zoltan K. Nagy
wiley   +1 more source

Diabetes-Technology and Waste: The Future is Now. [PDF]

J Diabetes Sci Technol
Heinemann L, Seid DA, Klonoff DC.
europepmc   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Mapping and quantifying the spatial and temporal composition of waste piles in informal settlements of urban Malawi. [PDF]

Environ Sci Pollut Res Int
Mwapasa T, Robertson T, Kazembe D, Mnkhwamba A, Kalonde PK, Feasey N, Quilliam RS, Morse T, Chidziwisano K.   +8 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Toward a More Sustainable Paper Industry: The Contribution of the Hydrothermal Carbonization for Solid Residues. [PDF]

ACS Omega
Taglieri L, Gallifuoco A, Gallucci K, Fratocchi L.   +3 more
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Customized Hemp Pulp Extraction via Laccase-Pectinase Pretreatment for Improved Waste Pulp Papermaking. [PDF]

ACS Omega
Dong X, Shi C, Wang Y, Hu F, Mondal AK, Tang Z.   +5 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Research Trends and Gaps in Construction Insulation Materials from Textile Waste and End-of-Life Wind Turbine Blades with Bio-Binders. [PDF]

Materials (Basel)
Vela G, Figueiredo A, Costa V, Vicente R.   +3 more
europepmc   +1 more source