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@article{WOS:001586940700001,
title = {Nanoconfined MXene/Cellulose Membranes for Selective Lithium Extraction
from Brines and Black Mass},
author = {Kou Yang and Qinyue Wang and Konstantin G Nikolaev and Qian Wang and Ivan V Moskalenko and Shanqing Zhang and Xueqing Qiu and Eduard O Timashev and Ekaterina V Skorb and Kostya S Novoselov and Daria V Andreeva},
doi = {10.1021/acsnano.5c08653},
times_cited = {4},
issn = {1936-0851},
year = {2025},
date = {2025-10-01},
journal = {ACS NANO},
volume = {19},
number = {40},
pages = {35483-35492},
publisher = {AMER CHEMICAL SOC},
address = {1155 16TH ST, NW, WASHINGTON, DC 20036 USA},
abstract = {A nanoconfined thermoresponsive membrane composed of Ti3C2T x MXene and
hydroxypropyl cellulose (HPC) was developed for selective Li+
extraction. By integrating the electrothermal conductivity of MXenes and
hydration-responsive gating of HPC, the membrane forms heterochannels
with tunable spacing that regulate ion transport through
nanoconfinement-enhanced mechanisms based on interaction energy and
hydration radius. While density functional theory calculations predicted
stronger sorption for Mg2+, experimental data revealed a clear
preference for Li+ uptake from both simulated brine and battery black
mass. This selectivity is attributed to favorable interactions of Li+
within the nanoconfined composite channels, where the subnanometer
interlayer spacings promote partial dehydration and size-sieving
effects. Li+ retention is governed not only by thermodynamic affinity
but also by kinetic acceleration in nanoconfined pathways and
hydration-based steric control. The membrane exhibits a reversible
thermal response and maintains stable performance under Joule heating.
It achieves >90% extraction efficiency from simulated Atacama brine and
up to 98% Li+ recovery from black mass supplied by VGM Sustainability
Solutions (SG3R, Pte. Ltd.).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{WOS:001030381000001,
title = {A nanofluidic sensing platform based on robust and flexible graphene
oxide/chitosan nanochannel membranes for glucose and urea detection},
author = {Kou Yang and Qinyue Wang and Kostya S Novoselov and Daria V Andreeva},
doi = {10.1039/d3nh00203a},
times_cited = {18},
issn = {2055-6756},
year = {2023},
date = {2023-08-01},
journal = {NANOSCALE HORIZONS},
volume = {8},
number = {9},
pages = {1243-1252},
publisher = {ROYAL SOC CHEMISTRY},
address = {THOMAS GRAHAM HOUSE, SCIENCE PARK, MILTON RD, CAMBRIDGE CB4 0WF, CAMBS,
ENGLAND},
abstract = {We present the development of a health-monitoring nanofluidic membrane
utilizing biocompatible and biodegradable graphene oxide, chitosan, and
graphene quantum dots. The nanoconfinement provided by graphene oxide
nanolayers encapsulates chitosan molecules, allowing for their
conformational changes and switchable hydrophobic-hydrophilic behavior
in response to pH variations. This low-dimensional membrane operates as
an array of nanofluidic channels that can release quantum dots upon pH
change. The photoluminescence emission from quantum dots enables rapid
and reliable optical visualization of pH changes, facilitating efficient
human health monitoring. To ensure fouling prevention and enable
multiple usages, we adopt a design approach that avoids direct contact
between biomarkers and the nanochannels. This design strategy, coupled
with good mechanical properties (Young's modulus of 5.5 & PLUSMN; 0.7
GPa), preserves the integrity and functionality of the sensors for
repeated sensing cycles. Furthermore, leveraging the memory effect, our
sensors can be reloaded with graphene quantum dots multiple times
without significant loss of selectivity, achieving reusability. The
wide-ranging capabilities of 2D materials and stimuli-responsive
polymers empower our sustainable approach to designing low-dimensional,
robust, and flexible sensing materials. This approach allows for the
integration of various biorecognition elements and signal transduction
modes, expanding the versatility and applications of the designed
materials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}