Influence of the TiN diffusion barrier on the leakage current and ferroelectricity in an Al-doped HfOx ferroelectric memristor and its application to neuromorphic computing.

The HfOx-based ferroelectric memristor is in the spotlight due to its complementary metal-oxide-semiconductor compatibility and scaling compared to existing perovskite-based ferroelectric memory. However, ferroelectric properties vary depending on the coefficient of thermal expansion of the top electrode, which is caused by strain engineering. When tungsten (W) with a small coefficient of thermal expansion is used as an electrode, the ferroelectric properties are improved, although the reliability is poor due to the diffusion of W atoms. Here, TiN can be used to prevent the diffusion of W. This metal nitride successfully suppresses the leakage current and induces a larger remanent polarization of 19.7 µC cm-2, a smaller coercive voltage of 9.26 V, and a faster switching speed. W/TiN/HAO/n+ Si can also exhibit multi-level characteristics and achieve a 10% read margin in 320 × 320 arrays. Ferroelectrics can also be applied to neuromorphic computing by imitating synaptic properties such as potentiation, depression, paired-pulse facilitation, and excitatory postsynaptic current. Using short-term plasticity, successful implementation in reservoir computing is also realized, achieving 95% classification accuracy. This paper shows promise for the use of memristors in artificial neural networks.

Enhanced analog switching and neuromorphic performance of ZnO-based memristors with indium tin oxide electrodes for high-accuracy pattern recognition.

This study systematically investigates analog switching and neuromorphic characteristics in a ZnO-based memristor by varying the anodic top electrode (TE) materials [indium tin oxide (ITO), Ti, and Ta]. Compared with the TE materials (Ti and Ta), memristive devices with TEs made of ITO exhibit dual volatile and nonvolatile switching behavior and multistate switching characteristics assessed based on reset-stop voltage and current compliance (ICC) responses. The polycrystalline structure of the ZnO functional layer sandwiched between ITO electrodes was confirmed by high-resolution transmission electron microscopy analysis. The current transport mechanism in the ZnO-based memristor was dominated by Schottky emission, with the Schottky barrier height modulated from 0.26 to 0.4 V by varying the reset-stop voltage under different ICC conditions. The long-term potentiation and long-term depression synaptic characteristics were successfully mimicked by modulating the pulse amplitudes. Furthermore, a 90.84% accuracy was achieved using a convolutional neural network architecture for Modified National Institute of Standards and Technology pattern categorization, as demonstrated by the confusion matrix. The results demonstrated that the ITO/ZnO/ITO/Si memristor device holds promise for high-performance electronic applications and effective ITO electrode modeling.

Oxygen-Plasma-Treated Al/TaOX/Al Resistive Memory for Enhanced Synaptic Characteristics.

In this study, we investigate the impact of O2 plasma treatment on the performance of Al/TaOX/Al-based resistive random-access memory (RRAM) devices, focusing on applications in neuromorphic systems. Comparative analysis using scanning electron microscopy and X-ray photoelectron spectroscopy confirmed the differences in chemical composition between O2-plasma-treated and untreated RRAM cells. Direct-current measurements showed that O2-plasma-treated RRAM cells exhibited significant improvements over untreated RRAM cells, including higher on/off ratios, improved uniformity and distribution, longer retention times, and enhanced durability. The conduction mechanism is investigated by current-voltage (I-V) curve fitting. In addition, paired-pulse facilitation (PPF) is observed using partial short-term memory. Furthermore, 3- and 4-bit weight tuning with auto-pulse-tuning algorithms was achieved to improve the controllability of the synapse weight for the neuromorphic system, maintaining retention times exceeding 103 s in the multiple states. Neuromorphic simulation with an MNIST dataset is conducted to evaluate the synaptic device.

Optimal measurement method for anterior instability on stress radiographs in anterior cruciate ligament tear: Considering the effect of static anterior tibial subluxation.

INTRODUCTION: Accurate assessment of anterior cruciate ligament (ACL) function is vital for guiding treatment. Nevertheless, the presence of tibial subluxation in the neutral position of a patient with an ACL injury may potentially introduce a confounding factor. This study aims to investigate whether tibial subluxation in the neutral position affects the diagnosis of anterior instability in patients with ACL injuries, potentially impacting the reliability and diagnostic accuracy of stress radiography. METHODS: This study included 88 patients: 30 with acute complete ACL tears (acute group), 28 with chronic complete ACL tears (chronic group), and 30 patients who underwent knee arthroscopic surgery other than ACL reconstruction (control group). Side-to-side differences (SSD) in stress radiography were measured using the Telos load status and the SSD of the gap between the Telos load and unload statuses. Diagnostic accuracy of the two methods was assessed using areas under the receiver operating characteristic curves (AUCs). RESULTS: The load SSD (5.92 ± 5.28 mm) was higher than the load-unload SSD (4.27 ± 5.99 mm) in the chronic group (P = 0.017). The load SSD demonstrated a significantly higher diagnostic value than that of the load-unload SSD in the combined group (AUC = 0.920 vs. 0.830; P = 0.012) and chronic group (AUC = 0.913 vs. 0.754; P = 0.002). After adjusting the symptoms for radiographic duration from 6 to 3 months in the chronic group, the load SSD exhibited a significantly higher diagnostic value (AUC = 0.902) than that of the load-unload SSD (AUC = 0.740; P < 0.001). CONCLUSION: The load SSD provides superior diagnostic accuracy compared to the load-unload SSD in ACL tear cases, where static anterior tibial subluxation may result in false negatives. Although load-unload SSD may have diagnostic value within the first 3 months post-injury, the load SSD method provides a reliable assessment of ACL function for patients beyond this timeframe.

Configurable Synaptic and Stochastic Neuronal Functions in ZnTe-Based Memristor for an RBM Neural Network.

This study presents findings that demonstrate the possibility of simplifying neural networks by inducing multifunctionality through separate manipulation within a single material. Herein, two-terminal memristor W/ZnTe/W devices implemented a multifunctional memristor comprising a selector, synapse, and a neuron using an ovonic threshold switching material. By setting the low-current level (µA) in the forming process, a stable memory-switching operation is achieved, and the capacity to implement a synapse is demonstrated based on paired-pulse facilitation/depression, potentiation/depression, spike-amplitude-dependent plasticity, and spike-number-dependent plasticity outcomes. Based on synaptic behavior, the Modified National Institute of Standards and Technology database image classification accuracy is up to 90%. Conversely, by setting the high-current level (mA) in the forming process, the stable bipolar threshold switching operation and good selector characteristics (300 ns switching speed, free-drift, recovery properties) are demonstrated. In addition, a stochastic neuron is implemented using the stochastic switching response in the positive voltage region. Utilizing stochastic neurons, it is possible to create a generative restricted Boltzmann machine model.

HfAlOx-based ferroelectric memristor for nociceptor and synapse functions.

Efficient data processing is heavily reliant on prioritizing specific stimuli and categorizing incoming information. Within human biological systems, dorsal root ganglions (particularly nociceptors situated in the skin) perform a pivotal role in detecting external stimuli. These neurons send warnings to our brain, priming it to anticipate potential harm and prevent injury. In this study, we explore the potential of using a ferroelectric memristor device structured as a metal-ferroelectric-insulator-semiconductor as an artificial nociceptor. The aim of this device is to electrically receive external damage and interpret signals of danger. The TiN/HfAlOx (HAO)/HfSiOx (HSO)/n+ Si configuration of this device replicates the key functions of a biological nociceptor. The emulation includes crucial aspects, such as threshold reactivity, relaxation, no adaptation, and sensitization phenomena known as "allodynia" and "hyperalgesia." Moreover, we propose establishing a connection between nociceptors and synapses by training the Hebbian learning rule. This involves exposing the device to injurious stimuli and using this experience to enhance its responsiveness, replicating synaptic plasticity.

Memristive Architectures Exploiting Self-Compliance Multilevel Implementation on 1 kb Crossbar Arrays for Online and Offline Learning Neuromorphic Applications.

This paper suggests the practical implications of utilizing a high-density crossbar array with self-compliance (SC) at the conductive filament (CF) formation stage. By limiting the excessive growth of CF, SC functions enable the operation of a crossbar array without access transistors. An AlOx/TiOy, internal overshoot limitation structure, allows the SC to have resistive random-access memory. In addition, an overshoot-limited memristor crossbar array makes it possible to implement vector-matrix multiplication (VMM) capability in neuromorphic systems. Furthermore, AlOx/TiOy structure optimization was conducted to reduce overshoot and operation current, verifying uniform bipolar resistive switching behavior and analog switching properties. Additionally, extensive electric pulse stimuli are confirmed, evaluating long-term potentiation (LTP), long-term depression (LTD), and other forms of synaptic plasticity. We found that LTP and LTD characteristics for training an online learning neural network enable MNIST classification accuracies of 92.36%. The SC mode quantized multilevel in offline learning neural networks achieved 95.87%. Finally, the 32 × 32 crossbar array demonstrated spiking neural network-based VMM operations to classify the MNIST image. Consequently, weight programming errors make only a 1.2% point of accuracy drop to software-based neural networks.

On-receptor computing with classical associative learning in semiconductor oxide memristors.

The increasing demand for energy-efficient data processing leads to a growing interest in neuromorphic computing that aims to emulate cerebral functions. This approach offers cost-effective and rapid parallel data processing, surpassing the limitations of the conventional von Neumann architecture. Key to this emulation is the development of memristors that mimic biological synapses. Recently, research efforts have focused on the incorporation of nociceptors-sensory neurons capable of detecting external stimuli-into memristors for applications in robotics and artificial intelligence. This integration enables memristors to adapt to various circumstances while remaining cost-effective. A nonfilamentary gradual resistive switching memristor is utilized to implement artificial nociceptor and synaptic behaviors. The fabricated Pt/indium gallium zinc oxide (IGZO)/SnOx/TiN device exhibits essential properties of biological nociceptors, including threshold response, no-adaptation, relaxation, sensitization, and recovery. Furthermore, the device leverages short-term memory principles to emulate learning behaviors observed in the brain by showcasing "forgetting" paradigms. Additionally, control of the input spikes yields different synaptic plasticity responses, thus emulating the key functions of our synapse. Computational simulations demonstrate the device's ability to perform both computing and sensing tasks effectively, thus enabling on-receptor computing with associative learning capabilities.

Volatile tin oxide memristor for neuromorphic computing.

The rise of neuromorphic systems has addressed the shortcomings of current computing architectures, especially regarding energy efficiency and scalability. These systems use cutting-edge technologies such as Pt/SnOx/TiN memristors, which efficiently mimic synaptic behavior and provide potential solutions to modern computing challenges. Moreover, their unipolar resistive switching ability enables precise modulation of the synaptic weights, facilitating energy-efficient parallel processing that is similar to biological synapses. Additionally, memristors' spike-rate-dependent plasticity enhances the adaptability of neural circuits, offering promising applications in intelligent computing. Integrating memristors into edge computing architectures further highlights their importance in tackling the security and efficiency issues associated with conventional cloud computing models.

The optimal measurement method considering reliability and validity in the anterior knee laxity of anterior cruciate ligament tears.

INTRODUCTION: To seek an optimal measurement method with high reliability and high validity for evaluation of the anterior knee laxity on stress radiographs and comparing the translation values to those of KT-2000 arthrometer. METHODS: Anterior knee laxity in 77 patients was measured preoperatively using the TelosTM and the KT-2000 arthrometer. Side-to-side difference measurements were taken using three conventional measuring methods and one proposed method (Modified Lateral). The knee position on the stress radiograph was evaluated and scored based on the stress radiograph qualifying criteria depending on stress film correctiveness. Intraclass correlation coefficients were analyzed to evaluate the reliability of the measurement methods and were compared between high (Group H) and low (Group L) radiograph quality score groups for each method. Validity was assessed by comparing the KT-2000 and the TelosTM using Pearson correlation (r value). RESULTS: The Modified Lateral method showed the best Intraclass Correlation Coefficients (ICCs), followed by Center to Center, and Medial to Medial and Lateral to Lateral methods without considering the quality of Telos. In the comparison between groups based on Telos quality for intra-rater reliability, the Medial to Medial (MM) method demonstrated the best reliability in both groups (MM: ICCs, Group H = 0.942, Group L = 0.917, P = 0.693). As for inter-rater reliability, the Modified Lateral (ML) method exhibited the best reliability in both groups (ML: ICCs, Group H = 0.923, Group L = 0.882, P = 0.547). The value measured using the ML method in Telos showed the highest correlation coefficient with the KT-2000 measured value in both groups H and L. There were no statistically significant differences among the correlation coefficient values. CONCLUSION: The Modified Lateral method is recommended for its high reliability, taking into account the differences in bilateral knee positions and anatomical discriminability on stress radiographs when evaluating anterior knee translation with Telos. It also best reflected the KT-2000 arthrometer. LEVEL OF EVIDENCE: Case Series, Level IV.

Delivery of piperlongumine via hyaluronic acid/phenylboronic acid-mediated dual targetable polymersome for enhanced anticancer functionality against pancreatic tumor.

Pancreatic cancer cells highly resistance to conventional chemo drugs, resulting low survival rates. The aim of the study was to design and develop dual targeting polymersomes (DTPS) loaded with phyto alkaloid agent i.e., piperlongumine (PL) for effective pancreatic cancer treatment. Here, hyaluronic acid (HA) was functionalized with 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[amino(polyethylene glycol)-2000] (DSPEPEG-NH2), poly(ethylene glycol) bis (amine) (PEG), and phenylboronic acid (PBA) moieties. The designed DTPS could selectively recognize CD44/sialic acid (SA) and deliver PL to MIA PaCa-2 pancreatic cancer cells, facilitated via HA-CD44 and PBA-SA interactions. Drug release and stability results implied sustained PL release profile and pH sensitivity. DTPS could be more efficiently bound with SA than other sugars based on fluorescence spectroscopy. The anticancer efficacy of designed polymersomes was tested with H6C7 normal pancreas cells and SA/CD44-overexpressed MIA PaCa-2 pancreatic cancer cells. DTPS showed both SA and CD44-mediated higher cellular uptake while single-targeted polymersomes showed CD44-mediated cellular uptake. The PL-loaded DTPS efficiently uptake by MIA PaCa-2 cancer cells, causing up to 80 % cell growth inhibition, reduced cell spheroids volume and increased dead cells by 58.3 %. These results indicate that the newly developed DTPS can effectively serve as a pH-responsive drug delivery system for efficient treatment of cancer.

Improvement of volatile switching in scaled silicon nanofin memristor for high performance and efficient reservoir computing.

Conductive-bridge random access memory can be used as a physical reservoir for temporal learning in reservoir computing owing to its volatile nature. Herein, a scaled Cu/HfOx/n+-Si memristor was fabricated and characterized for reservoir computing. The scaled, silicon nanofin bottom electrode formation is verified by scanning electron and transmission electron microscopy. The scaled device shows better cycle-to-cycle switching variability characteristics compared with those of large-sized cells. In addition, synaptic characteristics such as conductance changes due to pulses, paired-pulse facilitation, and excitatory postsynaptic currents are confirmed in the scaled memristor. High-pattern accuracy is demonstrated by deep neural networks applied in neuromorphic systems in conjunction with the use of the Modified National Institute of Standards and Technology database. Furthermore, a reservoir computing system is introduced with six different states attained by adjusting the amplitude of the input pulse. Finally, high-performance and efficient volatile reservoir computing in the scaled device is demonstrated by conductance control and system-level reservoir computing simulations.

Engineered inulin-based hybrid biomaterials for augmented immunomodulatory responses.

Modified biopolymers that are based on prebiotics have been found to significantly contribute to immunomodulatory events. In recent years, there has been a growing use of modified biomaterials and polymer-functionalized nanomaterials in the treatment of various tumors by activating immune cells. However, the effectiveness of immune cells against tumors is hindered by several biological barriers, which highlights the importance of harnessing prebiotic-based biopolymers to enhance host defenses against cancer, thus advancing cancer prevention strategies. Inulin, in particular, plays a crucial role in activating immune cells and promoting the secretion of cytokines. Therefore, this mini-review aims to emphasize the importance of inulin in immunomodulatory responses, the development of inulin-based hybrid biopolymers, and the role of inulin in enhancing immunity and modifying cell surfaces. Furthermore, we discuss the various approaches of chemical modification for inulin and their potential use in cancer treatment, particularly in the field of cancer immunotherapy.

Seasonal patterns and bloom dynamics of phytoplankton based on satellite-derived chlorophyll-a in the eastern yellow sea.

Satellite-derived chlorophyll-a concentration (Chl-a) is essential for assessing environmental conditions, yet its application in the optically complex waters of the eastern Yellow Sea (EYS) is challenged. This study refines the Chl-a algorithm for the EYS employing a switching approach based on normalized water-leaving radiance at 555 nm wavelength according to turbidity conditions to investigate phytoplankton bloom patterns in the EYS. The refined Chl-a algorithm (EYS algorithm) outperforms prior algorithms, exhibiting a strong alignment with in situ Chl-a. Employing the EYS algorithm, seasonal and bloom patterns of Chl-a are detailed for the offshore and nearshore EYS areas. Distinct seasonal Chl-a patterns and factors influencing bloom initiation differed between the areas, and the peak Chl-a during the bloom period from 2018 to 2020 was significantly lower than the average year in both areas. Specifically, bimodal and unimodal peak patterns in Chl-a were observed in the offshore and nearshore areas, respectively. By investigating the relationships between environmental factors and bloom parameters, we identified that major controlling factors governing bloom initiation were mixed layer depth (MLD) and suspended particulate matter (SPM) in the offshore and nearshore areas, respectively. Additionally, this study proposed that the recent decrease in the peak Chl-a might be caused by rapid environmental changes such as the warming trend of sea surface temperature (SST) and the limitation of nutrients. For example, external forcing, phytoplankton growth, and nutrient dynamics can change due to increased SST and limitation of nutrients, which can lead to a decrease in Chl-a. This study contributes to understanding phytoplankton dynamics in the EYS, highlighting the importance of region-specific considerations in comprehending Chl-a patterns and bloom dynamics.

Optimizing the Synergistic Effect of Co and Fe for Efficient and Durable Oxygen Evolution under Alkaline Conditions.

Developing robust oxygen evolution reaction (OER) electrocatalysts is crucial for advancing anion exchange membrane water electrolysis (AEMWE). In this study, we present a catalyst optimizing the synergistic effect of Co and Fe by creating a CoFe-based layer on a Fe-based electrode (Fe@CoFe). The Fe@CoFe exhibits an overpotential of 168 mV at 10 mA cm-2 under half-cell conditions and a current density of 10 A cm-2 at 2 V in the AEMWE system with 1 M KOH. Moreover, it showcases a degradation rate of 76 µV h-1 for 2000 h at 500 mA cm-2 in the single-cell system. This study demonstrates the feasibility of achieving efficient and durable water electrolysis using a transition metal-based catalyst exclusively fabricated via electrodeposition.

Programmable Retention Characteristics in MoS2-Based Atomristors for Neuromorphic and Reservoir Computing Systems.

In this study, we investigate the coexistence of short- and long-term memory effects owing to the programmable retention characteristics of a two-dimensional Au/MoS2/Au atomristor device and determine the impact of these effects on synaptic properties. This device is constructed using bilayer MoS2 in a crossbar structure. The presence of both short- and long-term memory characteristics is proposed by using a filament model within the bilayer transition-metal dichalcogenide. Short- and long-term properties are validated based on programmable multilevel retention tests. Moreover, we confirm various synaptic characteristics of the device, demonstrating its potential use as a synaptic device in a neuromorphic system. Excitatory postsynaptic current, paired-pulse facilitation, spike-rate-dependent plasticity, and spike-number-dependent plasticity synaptic applications are implemented by operating the device at a low-conductance level. Furthermore, long-term potentiation and depression exhibit symmetrical properties at high-conductance levels. Synaptic learning and forgetting characteristics are emulated using programmable retention properties and composite synaptic plasticity. The learning process of artificial neural networks is used to achieve high pattern recognition accuracy, thereby demonstrating the suitability of the use of the device in a neuromorphic system. Finally, the device is used as a physical reservoir with time-dependent inputs to realize reservoir computing by using short-term memory properties. Our study reveals that the proposed device can be applied in artificial intelligence-based computing applications by utilizing its programmable retention properties.

Realization of Multiple Synapse Plasticity by Coexistence of Volatile and Nonvolatile Characteristics of Interface Type Memristor.

Studies on neuromorphic computing systems are becoming increasingly important in the big-data-processing era as these systems are capable of energy-efficient parallel data processing and can overcome the present limitations owing to the von Neumann bottleneck. The Pt/WOx/ITO resistive random-access memory device can be used to implement versatile synapse functions because it possesses both volatile and nonvolatile characteristics. The gradual increase and decrease in the current of the Pt/WOx/ITO device with its uniform resistance state for endurance and retention enables additional synaptic applications that can be controlled using electric pulses. If the volatile and nonvolatile device properties are set through rehearsal and forgetting processes, the device can emulate various synaptic behaviors, such as potentiation and depression, paired-pulse facilitation, post-tetanic potentiation, image training, Hebbian learning rules, excitatory postsynaptic current, and Pavlov's test. Furthermore, reservoir computing can be implemented for applications such as pattern generation and recognition. This emphasizes the various applications of future neuromorphic devices, demonstrating the various favorable characteristics of pulse-enhanced Pt/WOx/ITO devices.

Factors Causing Unintended Sagittal and Axial Alignment Changes in High Tibial Osteotomy: Comparative 3-Dimensional Analysis of Simulation and Actual Surgery.

BACKGROUND: Unintended secondary changes in the posterior tibial slope (PTS) and tibial torsion angle (TTA) may occur after medial open-wedge high tibial osteotomy (MOWHTO). In surgical procedures using patient-specific instruments (PSIs), it is essential to reproduce the PTS and TTA that were planned in simulations. PURPOSE: To analyze the factors causing unintended sagittal and axial alignment changes after MOWHTO. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: Overall, 63 patients (70 knees) who underwent MOWHTO using a PSI between June 2020 and June 2023 were retrospectively reviewed. Preoperative and postoperative computed tomography scans were 3-dimensionally reconstructed. Simulated osteotomy was performed so that the weightbearing line could pass through the target point. A PSI gapper was 3-dimensionally printed to fit the posteromedial corner of the osteotomy gap in the simulated HTO model. After MOWHTO using the PSI gapper, the actual postoperative model was compared with the preoperative or simulation model. This assessment included PTS, TTA, hinge axis, and osteotomy-related parameters. Cortical breakage around the lateral hinge was evaluated to assess stability. RESULTS: The mean PTS and TTA did not change in the simulation. However, significant changes were observed in the actual postoperative PTS and TTA (change, -2.4°± 2.2° and -3.9°± 4.7°, respectively). The PTS was reduced, while the TTA decreased with internal rotation of the distal fragment. The difference in the axial hinge axis angle (AHA) between the simulation and actual surgery was the factor most correlated with the difference in the PTS (r = 0.625; P < .001). In regression analysis, the difference in the AHA was the only factor associated with the difference in the PTS (ß = 0.558; P = .001), and there were no factors that showed any significant associations with the difference in the TTA. In subgroup analyses for the change in the TTA, the correction angle and anterior osteotomy angle were significantly higher in the more internal rotation group (P = .023 and P = .010, respectively). The TTA change was significantly higher in the unstable group with lateral cortical breakage (P = .018). The unstable group was more likely to show an internal rotation of ≥5° (odds ratio, 5.0; P = .007). CONCLUSION: The AHA was associated with a difference in the PTS between the simulation and actual surgery. The change in the TTA was caused by a combination of multiple factors, such as a large correction angle and anterior osteotomy angle, but mainly by instability of the lateral cortical hinge.

Injectable composite hydrogels embedded with gallium-based liquid metal particles for solid breast cancer treatment via chemo-photothermal combination.

Photothermal therapy (PTT) holds great promise as a cancer treatment modality by generating localized heat at the tumor site. Among various photothermal agents, gallium-based liquid metal (LM) has been widely used as a new photothermal-inducible metallic compound due to its structural transformability. To overcome limitations of random aggregation and dissipation of administrated LM particles into a human body, we developed LM-containing injectable composite hydrogel platforms capable of achieving spatiotemporal PTT and chemotherapy. Eutectic gallium-indium LM particles were first stabilized with 1,2-Distearoyl-sn­glycero-3-phosphoethanolamine (DSPE) lipids. They were then incorporated into an interpenetrating hydrogel network composed of thiolated gelatin conjugated with 6-mercaptopurine (MP) chemodrug and poly(ethylene glycol)-diacrylate. The resulted composite hydrogel exhibited sufficient capability to induce MDA-MB-231 breast cancer cell death through a multi-step mechanism: (1) hyperthermic cancer cell death due to temperature elevation by near-infrared laser irradiation via LM particles, (2) leakage of glutathione (GSH) and cleavage of disulfide bonds due to destruction of cancer cells. As a consequence, additional chemotherapy was facilitated by GSH, leading to accelerated release of MP within the tumor microenvironment. The effectiveness of our composite hydrogel system was evaluated both in vitro and in vivo, demonstrating significant tumor suppression and killing. These results demonstrate the potential of this injectable composite hydrogel for spatiotemporal cancer treatment. In conclusion, integration of PTT and chemotherapy within our hydrogel platform offers enhanced therapeutic efficacy, suggesting promising prospects for future clinical applications. STATEMENT OF SIGNIFICANCE: Our research pioneers a breakthrough in cancer treatments by developing an injectable hydrogel platform incorporating liquid metal (LM) particle-mediated photothermal therapy and 6-mercaptopurine (MP)-based chemotherapy. The combination of gallium-based LM and MP achieves synergistic anticancer effects, and our injectable composite hydrogel acts as a localized reservoir for specific delivery of both therapeutic agents. This platform induces a multi-step anticancer mechanism, combining NIR-mediated hyperthermic tumor death and drug release triggered by released glutathione from damaged cancer populations. The synergistic efficacy validated in vitro and in vivo studies highlights significant tumor suppression. This injectable composite hydrogel with synergistic therapeutic efficacy holds immense promise for biomaterial-mediated spatiotemporal treatment of solid tumors, offering a potent targeted therapy for triple negative breast cancers.