Advanced Materials Technologies最新文献

Stimuli-responsive materials often react to changes in environmental conditions by altering their shape. Here, it is shown that even changes in materials that are not directly observable, such as local stiffening, can be exploited to introduce the concept of trainable materials. A fully 3D-printable filament based on thermoplastic polyurethane (TPU) functionalized with a bivalent crosslinker capable of undergoing a C,H insertion reaction under UV irradiation was developed. Specimens printed from this filament demonstrate a gradual increase in stiffness, reaching almost 300% of their initial stiffness after 50 hours of irradiation. To exploit this tunability, mechanical metamaterials incorporating the developed material are engineered. By utilizing an instability-driven transformation under compression, it is demonstrated how local stiffening can be amplified through rational design. Moreover, by exploiting the unusual mechanical behavior of metamaterials arising from their internal architecture, a closed-loop system is presented in which, under compressive load, the metamaterial closes an electric circuit that activates UV light, which in turn modifies the properties of the base material. Through this approach, two trainable systems are realized: one that progressively conforms its shape to mechanical compression, and another that gradually increases its resistance to an applied force, mimicking the physical training of biological tissues.

Frequent monitoring of body fluids such as blood, sweat, saliva, and urine is essential for the early detection of various diseases. Ion-selective organic electrochemical transistors (IS-OECTs) offer a low-cost, highly sensitive, and easily fabricated platform for detecting ion concentration changes. Their inherent flexibility and biocompatibility make them well-suited for integration into wearable systems for continuous, point-of-care health monitoring. However, optimizing IS-OECT design and circuit performance requires accurate modeling of their concentration-dependent behavior, which is complicated by complex electrochemical interactions and charge transport dynamics. In this work, it introduces an empirical model that extends the Friedlein framework to incorporate ion concentration effects, enabling accurate prediction of steady-state device characteristics in the presence of both target and interfering ions. Validation of this model with IS-OECTs fabricated to detect ammonium (NH₄⁺) and sodium (Na⁺) ions shows an excellent agreement with experimental measurements, underscoring its reliability for electrochemical sensing applications.

Artificial electric skin with multi-intensity pain-evaluating capabilities offers promising opportunities for the construction of friendly human-robot interaction. However, realizing a stepwise sensing system generally requires lateral integration of diverse materials, which is prone to delamination and thus operation failure. Here, a fully soft, monolithic hydrogel-based artificial fingertip (HBAF), fabricated via digital light processing (DLP) 3D printing, enabling robotic fingertips to distinguish objects in varying sizes is proposed. To enhance the mechanical and conductive properties of a printed hydrogel, a two-step post-processing method is developed to introduce a secondary functional network into a high-resolution soft model. This modification can increase stretchability by three-fold and conductivity by 1.78-fold compared to the original printed hydrogel. Notably, the integration challenge between the hydrogel-based sensor and the robotic body part is addressed by growing a polydopamine gel layer at the interface of the 3D model's base to enhance contact. Furthermore, the HBAF's size parameters can be programmed to achieve distinct pain thresholds, demonstrating its potential for personalized bionic sensors in artificial limbs and enhancing safety in collaborative robotics.

Artificial electric skin with multi-intensity pain-evaluating capabilities offers promising opportunities for the construction of friendly human-robot interaction. However, realizing a stepwise sensing system generally requires lateral integration of diverse materials, which is prone to delamination and thus operation failure. Here, a fully soft, monolithic hydrogel-based artificial fingertip (HBAF), fabricated via digital light processing (DLP) 3D printing, enabling robotic fingertips to distinguish objects in varying sizes is proposed. To enhance the mechanical and conductive properties of a printed hydrogel, a two-step post-processing method is developed to introduce a secondary functional network into a high-resolution soft model. This modification can increase stretchability by three-fold and conductivity by 1.78-fold compared to the original printed hydrogel. Notably, the integration challenge between the hydrogel-based sensor and the robotic body part is addressed by growing a polydopamine gel layer at the interface of the 3D model's base to enhance contact. Furthermore, the HBAF's size parameters can be programmed to achieve distinct pain thresholds, demonstrating its potential for personalized bionic sensors in artificial limbs and enhancing safety in collaborative robotics.

Protein materials have vital functions in living organisms and in the production of biomedical devices. Silk and collagen are established components of tissue regeneration scaffolds with electrical or bioactive functional properties, while fluorescent proteins are markers of cell activity and toxicity. Ultrabithorax (Ubx) is a protein material with excellent biocompatibility, elasticity, and functionalization pathways with fluorescent reporters, growth factors, and DNA aptamers. In this work, the optical and electrical properties of Ubx protein fusions are measured using techniques relevant for biosensing. Fluorescence spectra and lifetimes of Ubx fusions are measured. Förster resonance energy transfer (FRET) between Ubx and fluorescent fusion partners is reported for the first time. The stability of fluorescence of Ubx protein fusions with fluorescent proteins EGFP and mCherry is confirmed in a range of illumination powers. Impedance spectroscopy measurements show that increased relative humidity causes a rise in the electrical conductivity of Ubx fusion fibers by two orders of magnitude. Nyquist and broadband dielectric analyses indicate that charge transfer is dominated by ions, and the increase in conductivity is driven by increased ion mobility. This paper informs the choice of Ubx functionalization strategies for applications in biosensing using fluorescence lifetime imaging microscopy, FRET, and impedimetric spectroscopy.

Flexible sensors are distinguished from rigid electronic devices by their lightweight characteristics and excellent deformation repeatability. Nonetheless, the suboptimal performance of flexible sensors, such as sensitivity, sensing range, and response time, necessitates the development of advanced optimization strategies, including material composition design, microstructure engineering, and device architecture innovation. The remarkable mechanical properties and high electrical conductivity of MXenes position them as promising materials for flexible sensors. This review systematically summarizes the progress in innovative synthesis methods of MXenes. The tunable conductivity, mechanical flexibility, and multi-functionality of MXenes are discussed. Subsequently, flexible strain and pressure sensors (categorized as piezoresistive, piezoelectric, capacitive, and triboelectric), along with gas and humidity sensors, are systematically analyzed. Finally, key challenges pertaining to biocompatibility and environmental stability are highlighted. Collectively, this review delivers a comprehensive and up-to-date perspective on MXene-based flexible sensors, establishing a robust foundation for future explorations and technological innovations in the field.

Protein materials have vital functions in living organisms and in the production of biomedical devices. Silk and collagen are established components of tissue regeneration scaffolds with electrical or bioactive functional properties, while fluorescent proteins are markers of cell activity and toxicity. Ultrabithorax (Ubx) is a protein material with excellent biocompatibility, elasticity, and functionalization pathways with fluorescent reporters, growth factors, and DNA aptamers. In this work, the optical and electrical properties of Ubx protein fusions are measured using techniques relevant for biosensing. Fluorescence spectra and lifetimes of Ubx fusions are measured. Förster resonance energy transfer (FRET) between Ubx and fluorescent fusion partners is reported for the first time. The stability of fluorescence of Ubx protein fusions with fluorescent proteins EGFP and mCherry is confirmed in a range of illumination powers. Impedance spectroscopy measurements show that increased relative humidity causes a rise in the electrical conductivity of Ubx fusion fibers by two orders of magnitude. Nyquist and broadband dielectric analyses indicate that charge transfer is dominated by ions, and the increase in conductivity is driven by increased ion mobility. This paper informs the choice of Ubx functionalization strategies for applications in biosensing using fluorescence lifetime imaging microscopy, FRET, and impedimetric spectroscopy.

Direct Ink Writing (DIW) is a versatile additive manufacturing technique widely used for processing complex inks, particularly particle-loaded formulations. Despite its broad applicability, the field lacks standardized criteria for defining and assessing printability. Existing approaches, typically based on rheological thresholds such as yield stress and elastic modulus, often lead to system-specific, inconsistent results and rely heavily on subjective visual inspection. This work presents a systematic framework for analyzing DIW printability, grounded in the unpacking of the printing process into five subfunctions: extrudability, single filament accuracy, planar accuracy, buildability, and ability to produce suspended structures. Each subfunction is examined in detail through dimensional analysis to identify the parameters responsible for its success. This approach enables a deeper understanding of the interactions between material properties and process variables and highlights how certain parameters can have opposing effects in different subfunctions. To support an objective evaluation, a standardized printability test based on a serpentine pattern is introduced. By quantifying key geometric features (filament width, height, curvature, and deflection) the test enables a reproducible and scalable comparison of inks across a wide range of formulations. This method replaces qualitative assessments with measurable, normalized metrics, providing a robust tool for ink development and printer calibration.

Organic electrochemical transistors (OECTs) offer a compelling platform for hardware synapses, yet ion transport through the common semi-crystalline PVDF-HFP electrolyte suppresses switching speed and energy efficiency. Here, DPVDF-SZ, a soft zwitterionic fluoropolymer ion gel engineered by grafting sulfobetaine side chains onto a flexible PVDF-CTFE backbone, is introduced. Crystallinity drops to ≈3%, and fracture strain rises to 84%. Paired with PEDOT:PSS, DPVDF-SZ achieves a µC* of 127 F V⁻¹ s⁻¹ cm⁻¹—where µC* is the product of charge carrier mobility and volumetric capacitance—while tripling transconductance and reducing the threshold voltage by 0.3 V under sub −1.5 V operation. Soft zwitterionic interfaces deliver >90% current retention after 70 pulses, linear bidirectional weight updates across 60 write/erase cycles, and tunable paired-pulse plasticity. In a 4 × 4 OECT reservoir array, DPVDF-SZ classifies temporal pulse patterns and reconstructs 16 × 16 images with minimal energy. DPVDF-SZ-based OECTs address signal retention and ion migration challenges, enabling efficient neuromorphic systems and potentially bridging AI with biological neural processing.

All the known methods (e.g., mechanical exfoliation, liquid-phase exfoliation, ionic shearing, chemical vapor deposition, nano-precipitation, etc.) cannot be used to prepare uniformly distributed black phosphorus (BP) nanolayers on a large scale, while the vapor deposition method brings a huge cost burden (e.g., material costs, equipment and energy consumption, process efficiency and yield, scalability, and throughput). This unevenly distributed BP layer will cause significant performance differences among the same batch of memristors due to the differences in the film layers when preparing memristors, which will greatly limit its application in memristors and optoelectronic devices. To address this problem, a freezing-solidification-vacuum drying (FSVD) strategy has been successfully developed to prepare high-quality 2D BP films on a large scale. This approach is also used to transfer the EB-COF film prepared using the liquid-liquid interface assisted method to the BP film coated onto the ITO substrate. The as-fabricated bilayer heterojunction device, Al/EB-COF/BP/ITO, exhibits an excellent memristive performance at a small sweep voltage range of ±1V. By utilizing this outstanding performance, a convolutional neural network is constructed to achieve the encryption and recognition of image data.