Advanced Science is an open access interdisciplinary science journal publishing the best-in-class fundamental and applied research in materials science, physics, chemistry, medical and life sciences, and engineering. Our mission is to give top science the maximum accessibility through open access publishing.
Advanced Materials publishes the most important discoveries on any and all materials from materials scientists, chemists, physicists, engineers as well as health and life scientists and bringing you the latest results and trends in modern materials-related research every week.
Advanced Functional Materials publishes outstanding research related to improving chemical and physical properties of materials. Our readers range from materials scientists, chemists, physicists, and engineers, together with biologists and medical researchers.
Advanced Energy Materials is your prime applied energy journal for research providing solutions to today’s global energy challenges. Your paper will make an impact in our journal which has been at the forefront of publishing research on all forms of energy harvesting, conversion and storage for more than a decade.
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Articles
MPI‐Guided Photothermal Therapy of Prostate Cancer Using Stem Cell Delivery of Magnetotheranostic Nanoflowers
- Advanced Functional Materials
- 19 January 2026
Graphical Abstract
Tumor-tropic human mesenchymal stem cells (hMSCs) were used as delivery vehicles for magnetotheranostic gold–iron oxide nanoflowers. Magnetic particle imaging of the iron component demonstrated widespread intratumoral distribution and sustained retention in contrast to injection of naked nanoflowers. The gold component enabled effective photothermal therapy resulting in complete tumor ablation without recurrence up to 90 days post-treatment.
True Random Number Generator for Robust Data Security via Intrinsic Stochasticity in a 2D hBN Threshold Switching Memristor
- Advanced Functional Materials
- 19 January 2026
Graphical Abstract
We demonstrate true random number generator (TRNG) circuits based on a 2D hBN threshold switching memristor integrated with passive components. Leveraging its intrinsic stochastic behavior, the spike generator produces output fluctuations directly converted into random bits via a comparator. The generated bitstreams successfully pass NIST randomness tests without postprocessing, highlighting the robustness and effectiveness of the proposed TRNG architecture.
Large Segment Bandgap, Steric Hindrance Structure and Organic Semiconductor Filler Collaborative Designs for Superior High‐Temperature Energy Storage of Aromatic Polymers
- Advanced Functional Materials
- 19 January 2026
Graphical Abstract
A molecular strategy that combines the advantages of a large segment bandgap, high steric hindrance, and organic semiconductor is realized through chain structural design and PCBM doping. The design inhibits intramolecular, intermolecular, and alongside molecular charge transfer processes, and charge injection processes, resulting in a superior energy storage density of 7.93 J/cm3 when charging-discharging efficiency exceeds 85% at 150°C for the designed aromatic polymer.
Electronic Nose for Indoor Mold Detection and Identification
- Advanced Sensor Research
- 17 December 2025
Graphical Abstract
This study explores the potential of a SnO2 nanowire-based chemiresistive electronic nose not only to detect but also to identify two common indoor mold species, Stachybotrys chartarum and Chaetomium globosum on two different growth substrates. In a laboratory setup, the electronic nose displays high classification performance using optimized linear discriminant analysis.
Progress and Prospect of Industrialization of Sodium‐Ion Battery in China
- Advanced Energy Materials
- 23 October 2025
Graphical Abstract
This paper introduces the composition, development, and current application status of China's sodium-ion battery supply chain (including cathode, anode, electrolyte, cell, etc.), analyzes the challenges and prospects of the industrialization of sodium-ion battery technology, and provides suggestions for the future research and development of sodium-ion batteries.
Synergistic Coupling of Host and Electrolyte Achieving 1270 Wh L−1 in Anode-Free Lithium Metal Batteries
- Advanced Materials
- 2 November 2025
Graphical Abstract
A synergistic combination of a highly reversible host and a commercially viable carbonate-rich electrolyte enables simultaneous stabilization of both anode and cathode interfaces in anode-free lithium metal batteries. This integrated strategy delivers exceptional reversibility and a record volumetric energy density of 1270 Wh L−1 (including package) in multi-stacked pouch-type full cells under practical conditions.
Self‐Assembled Interlayer Enables High‐Performance Organic Photovoltaics with Power Conversion Efficiency Exceeding 20%
- Advanced Materials
- 21 March 2024
Graphical Abstract
High-performance organic photovoltaic (OVP) with efficiency exceeding 20% is achieved via the self-assembled interlayer (SAI) strategy. The use of 2PACz-SAI advances the surface/interface optoelectronic properties, including mitigated parasitic absorption, improved optical field distribution and the carrier dynamics. Moreover, the efficacy of SAI strategy is widely proved. Additionally, the 2PACz-SAI based ST-OPV exhibits a record light utilization efficiency of 5.34%.
Excellent Low‐Frequency Microwave Absorption and High Thermal Conductivity in Polydimethylsiloxane Composites Endowed by Hydrangea‐Like CoNi@BN Heterostructure Fillers
- Advanced Materials
- 9 October 2024
Graphical Abstract
1D chain-like CoNi is encapsulated by the 2D flake BN to form hydrangea-like CoNi@BN heterostructure fillers by the spray-drying-sintering process. Hydrangea-like CoNi@BN morphology utilizes full advantage for natural resonance of CoNi and high thermal conductivity of BN, and integrating low-frequency microwave absorption & thermal conductive in CoNi@BN/PDMS composites.
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
- Advanced Intelligent Systems
- 27 June 2024
Graphical Abstract
SHapley Additive exPlanations and Local Interpretable Model Agnostic Explanation are two widely used eXplainable artificial intelligence methods. However, they have limitations related to model-dependency and the presence of collinearity among the features which result in unrealistic explanations. This perspective discusses these two issues through two case studies and provides possible solutions to overcome and eliminate their impacts
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