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Themed collection MSDE most-read Q1 2019

10 items
Review Article

Cellulose nanocrystals in nanoarchitectonics – towards photonic functional materials

This review summarizes the recent achievements in the development of photonic functional materials based on cellulose nanocrystals (CNCs) and CNC templating. The unique self-assembly of CNCs into chiral nematic structures introduces photonic properties for the development of functional materials with application potential in photonic sensing, tunable reflectors or optoelectronics.

Graphical abstract: Cellulose nanocrystals in nanoarchitectonics – towards photonic functional materials
From the themed collection: Soft Materials Nanoarchitectonics
Review Article

Li- and Mn-rich layered oxide cathode materials for lithium-ion batteries: a review from fundamentals to research progress and applications

Li- and Mn-rich layered oxides (LMRO) have drawn much attention for application as cathode materials for lithium-ion batteries due to their high-energy density of over 1000 W h kg−1.

Graphical abstract: Li- and Mn-rich layered oxide cathode materials for lithium-ion batteries: a review from fundamentals to research progress and applications
From the themed collection: MSDE most-read Q1 2019
Review Article

Molecular engineering of perovskite photodetectors: recent advances in materials and devices

We present an overview of the recent advances in perovskite photodetectors from both the materials and device perspectives.

Graphical abstract: Molecular engineering of perovskite photodetectors: recent advances in materials and devices
From the themed collection: MSDE most-read Q1 2019
Open Access Communication

Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery

Traditional machine learning (ML) metrics overestimate model performance for materials discovery.

Graphical abstract: Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery
From the themed collection: MSDE most-read Q1 2019
Paper

Energy-based descriptors to rapidly predict hydrogen storage in metal–organic frameworks

A new, energy-based descriptor for porous materials is highly predictive for hydrogen adsorption using an interpretable regression model.

Graphical abstract: Energy-based descriptors to rapidly predict hydrogen storage in metal–organic frameworks
From the themed collection: MSDE most-read Q1 2019
Open Access Paper

Electric field induced rotation of halogenated organic linkers in isoreticular metal–organic frameworks for nanofluidic applications

Electric field induced rotation of IRMOF linkers provides opportunities for controlling the diffusion of molecules for nanofluidic applications.

Graphical abstract: Electric field induced rotation of halogenated organic linkers in isoreticular metal–organic frameworks for nanofluidic applications
From the themed collection: MSDE most-read Q1 2019
Open Access Paper

Catalytic single-chain polymeric nanoparticles at work: from ensemble towards single-particle kinetics

In this work, we present the design and preparation of catalytic single chain polymeric nanoparticles (SCPNs), their characterization at the ensemble level as well as our progress toward analyzing individual SCPNs with single-molecule fluorescence microscopy.

Graphical abstract: Catalytic single-chain polymeric nanoparticles at work: from ensemble towards single-particle kinetics
From the themed collection: MSDE most-read Q1 2019
Open Access Paper

Stable and efficient generation of poly(β-amino ester)s for RNAi delivery

Cationic polymers are promising delivery systems for RNAi due to their ease of manipulation, scale-up conditions and transfection efficiency.

Graphical abstract: Stable and efficient generation of poly(β-amino ester)s for RNAi delivery
From the themed collection: MSDE most-read Q1 2019
Open Access Paper

Enabling precision manufacturing of active pharmaceutical ingredients: workflow for seeded cooling continuous crystallisations

Presentation and applied case study of a system-wide workflow which supports rapid, systematic and efficient continuous seeded cooling crystallisation process design, with the aim to deliver a robust, consistent process with tight control of particle attributes.

Graphical abstract: Enabling precision manufacturing of active pharmaceutical ingredients: workflow for seeded cooling continuous crystallisations
From the themed collection: MSDE most-read Q1 2019
Paper

Deep learning for chemical reaction prediction

We describe a deep learning-based system for predicting chemical reactions and identifying experimentally-observed masses.

Graphical abstract: Deep learning for chemical reaction prediction
From the themed collection: MSDE most-read Q1 2019
10 items

About this collection

From MSDE 

Showcasing the top ten most-read articles in MSDE during January–March 2019

Find previous most-read collections on the MSDE blog

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