Efficient Generation Research Articles

Efficient Generation of Protein Pockets with PocketGen.

Designing small-molecule-binding proteins, such as enzymes and biosensors, is crucial in protein biology and bioengineering. Generating high-fidelity protein pockets areas where proteins interact with ligand molecules, is challenging due to complex interactions between ligand molecules and proteins, flexibility of ligand molecules and amino acid side chains, and complex sequence-structure dependencies. Here, we introduce PocketGen, a deep generative method for generating the residue sequence and the full-atom structure within the protein pocket region that leverages sequence structure consistency. PocketGen consists of a bilevel graph transformer for structural encoding and a sequence refinement module that uses a protein language model (pLM) for sequence prediction. The bilevel graph transformer captures interactions at multiple granularities (atom-level and residue/ligand-level) and aspects (intra-protein and protein-ligand) with bilevel attention mechanisms. For sequence refinement, a structural adapter using cross-attention is integrated into a pLM to ensure structure-sequence consistency. During training, only the adapter is fine-tuned, while the other layers of the pLM remain unchanged. Experiments show that PocketGen can efficiently generate protein pockets with higher binding affinity and validity than state-of-the-art methods. PocketGen is ten times faster than physics-based methods and achieves a 95% success rate (percentage of generated pockets with higher binding affinity than reference pockets) with over 64% amino acid recovery rate.

AI-guided few-shot inverse design of HDP-mimicking polymers against drug-resistant bacteria

Host defense peptide (HDP)-mimicking polymers are promising therapeutic alternatives to antibiotics and have large-scale untapped potential. Artificial intelligence (AI) exhibits promising performance on large-scale chemical-content design, however, existing AI methods face difficulties on scarcity data in each family of HDP-mimicking polymers (<102), much smaller than public polymer datasets (>105), and multi-constraints on properties and structures when exploring high-dimensional polymer space. Herein, we develop a universal AI-guided few-shot inverse design framework by designing multi-modal representations to enrich polymer information for predictions and creating a graph grammar distillation for chemical space restriction to improve the efficiency of multi-constrained polymer generation with reinforcement learning. Exampled with HDP-mimicking β-amino acid polymers, we successfully simulate predictions of over 105 polymers and identify 83 optimal polymers. Furthermore, we synthesize an optimal polymer DM0.8iPen0.2 and find that this polymer exhibits broad-spectrum and potent antibacterial activity against multiple clinically isolated antibiotic-resistant pathogens, validating the effectiveness of AI-guided design strategy.

Research on Photovoltaic Power Generation Characteristics of Small Ocean Observation Unmanned Surface Vehicles

Under the action of waves, a small unmanned surface vehicle (USV) will experience continuous oscillation, significantly impacting its photovoltaic power generation system. This paper proposes a USV photovoltaic power generation simulation model, and the efficiency of photovoltaic MPPT control under wave action is studied. A simulation model for solar irradiance on solar panels of USV under wave action is established based on CFD and solar irradiation models. The dynamic changes in irradiance of USV solar panels under typical wave conditions are analyzed. The MPPT efficiency of USV photovoltaic power generation devices under continuously changing irradiance conditions is studied on this basis. The simulation research results indicate that waves and solar altitude angles significantly impact the instantaneous irradiation energy of USV photovoltaic devices. However, the impact of waves on the average irradiance is relatively tiny. The sustained oscillation of irradiance poses certain requirements for the Maximum Power Point Tracking (MPPT) control frequency of USV photovoltaic systems; a disturbance control frequency of no less than 50 Hz is proposed.

Alkaline Phosphatase Activated Near-Infrared Frequency Upconversion Photosensitizers for Tumor Photodynamic Therapy.

Photodynamic therapy (PDT) is a promising anticancer method due to its noninvasive features, high efficiency, and superior accuracy. The activated near-infrared upconversion photosensitizer has a high tissue penetration depth and could be explicitly released with minimal side effects. Therefore, we designed and synthesized a series of Br-substituted compounds (NFh-Br) based on the near-infrared upconversion hemicyanine dye. The heavy atomic effect improves the generation of 1O2 and upconversion luminous efficiency. Especially, NFh-Br11 exhibited an excellent 1O2 generation rate under 808 nm excitation and effectively killed tumor cells in vitro, and the alkaline phosphatase (ALP)-activatable photosensitizer (NFh-ALP) was obtained by modifying the NFh-Br11. NFh-ALP could be activated by ALP and release NFh-Br11, which induces apoptosis of tumor cells and has outstanding anticancer effects in vitro and in vivo. This work could provide a strategy for designing activatable upconversion photosensitizers.

A novel approach to integrate CCHP systems with desalination for sustainable energy and water solutions in educational buildings

ABSTRACT This study presents a novel approach to integrating combined cooling, heating, and power (CCHP) systems with water desalination for enhanced energy and water management in educational buildings. Two distinct layouts for CCHP and desalination systems are introduced: one prioritizing efficient power generation to meet electricity demands while providing waste heat for desalination, and the other focusing on balancing cooling and heating loads alongside water desalination. Both layouts are tailored to meet the building's energy and water demands while considering operational efficiency. Optimization of these layouts against traditional systems using the bat search algorithm emphasizes economic viability and the gas engine's operational flexibility, which are crucial for partial load operation. In addition, an environmental assessment compares the proposed CCHP-desalination systems with conventional setups, assessing CO2 emission reductions and overall sustainability. The evaluation encompasses key environmental metrics, such as resource consumption and the integration of renewable energy sources. Results highlight significant CO2 emission reductions across various gas engine capacities, with notable enhancements in economic and environmental performance achieved by selecting a 3,250 kW gas engine within the CCHP-desalination system. This choice not only maximizes the annual profit but also reduces CO2 emissions by 57% compared to conventional systems, underscoring the system's sustainability benefits.

Functional ventilation building envelope integrated photovoltaic modules and phrase change material in subtropical climate: An in-depth numerical investigation

Most of existing solar ventilation envelope systems adopt a single structure including a glass cover a massive wall, which possesses the drawbacks of low thermal efficiency and poor stability. In recent decades, auxiliary power generation devices, led by photovoltaic (PV), have made epochal achievements in integrated building applications, while the superior thermal regulation capability of thermal storage materials, represented by phrase change materials (PCM), has further helped to improve the thermal environment of buildings, and the above two technologies have demonstrated great energy conservation potential. In order to explore the application and synergistic effect of the above two energy-conservation technologies in passive ventilation envelopes, a novel functional ventilation building envelope (FVBE) integrated with PV panel and PCM is proposed in this paper. A comprehensive exploration of the influence of various key parameters on the thermal performance of the FVBE-PV/PCM system. The electrical and thermal performance of the system is explored based on different seasonal climates. Specifically, effects of thickness as well as the melting temperature of PCM and the air channel width has been provided in this study. Taking the inner wall surface temperature (Tinner_wall), equivalent indoor load (Qload) and electrical efficiency (ηe) as evaluation indexes, the thermal efficiency, electrical performance and the coupling mechanism was assessed. Specifically, the coupling mechanism between the thermal performance and electrical performance of the FVBE-PV/PCM system was analyzed from the perspective of combined heat and power, revealing the functional characteristics of the system. Meanwhile, the article conducted a comparative study on the thermal and electrical performance of a typical building integrated PV (BIPV), FVBE-PV system FVBE-PV/PCM system. In particular, energy and exergy analysis is carried out to characterize the energy utilization of the FVBE-PV/PCM system in different structural systems. The research found that increasing the thickness of both the PCM and air channel leads to lower indoor temperature and heat flux, with different optimal phase transition temperatures for summer and winter. Although the FVBE-PV system exhibited a maximum 3.12 % reduction in power generation efficiency compared to the BIPV system due to increased PV temperature caused by air layer insulation, incorporating PCM can reduce exergy losses by an average of 31.731 % to mitigate this drawback and improve energy efficiency. Additionally, the analysis revealed varying coupling correlations between thermal performance and power generation based on two key parameters. This study could contribute to the functional improvement of the building envelope and simultaneous indoor thermal regulation.

Engineering IscB to develop highly efficient miniature editing tools in mammalian cells and embryos.

The IscB proteins, as the ancestors of Cas9 endonuclease, hold great promise due to their small size and potential for diverse genome editing. However, their activity in mammalian cells is unsatisfactory. By introducing three residual substitutions in IscB, we observed an average 7.5-fold increase in activity. Through fusing a sequence-non-specific DNA-binding protein domain, the eIscB-D variant achieved higher editing efficiency, with a maximum of 91.3%. Moreover, engineered ωRNA was generated with a 20% reduction in length and slightly increased efficiency. The engineered eIscB-D/eωRNA system showed an average 20.2-fold increase in activity compared with the original IscB. Furthermore, we successfully adapted eIscB-D for highly efficient cytosine and adenine base editing. Notably, eIscB-D is highly active in mouse cell lines and embryos, enabling the efficient generation of disease models through mRNA/ωRNA injection. Our study suggests that these miniature genome-editing tools have great potential for diverse applications.

Decentralized Retrofit Model Predictive Control of Inverter-Interfaced Small-Scale Microgrids

In recent years, small-scale microgrids have become popular in the power system industry because they provide an efficient electrical power generation platform to guarantee autonomy and independence from the power grid, which is a critical feature in cases of catastrophic events or remote areas. On the other hand, due to the short distances among multiple distribution generation systems in small-scale microgrids, the interconnection couplings among them increase significantly, which jeopardizes the stability of the entire system. Therefore, this work proposes a novel method to design decentralized robust controllers based on a retrofit model predictive control scheme to tackle the issue of instability due to the short distances among generation systems. In this approach, the retrofit model predictive controller receives the measured feedback signal from the interconnection current and generates a control command signal to limit the interconnection current to prevent instability. To design a retrofit controller, only the model of a robust closed-loop system, as well as an interconnection line, is required. The model predictive control signal is added in parallel to the control signal from the existing robust voltage source inverter controller. Simulation results demonstrate the superior performance of the proposed technique as compared with the virtual impedance and retrofit linear quadratic regulator techniques (benchmarks) with respect to peak-load demand, plug-and-play capability, nonlinear load, and inverter efficiency.

The Delayed Box: Biphenyl Bisimide Cyclophane, a Supramolecular Nano-environment for the Efficient Generation of Delayed Fluorescence.

Activating delayed fluorescence emission in a dilute solution via a non-covalent approach is a formidable challenge. In this report, we propose a strategy for efficient delayed fluorescence generation in dilute solution using a non-covalent approach via supramolecularly engineered cyclophane-based nanoenvironments that provide sufficient binding strength to π-conjugated guests and that can stabilize triplet excitons by reducing vibrational dissipation and lowering the singlet-triplet energy gap for efficient delayed fluorescence emission. Toward this goal, a novel biphenyl bisimide-derived cyclophane is introduced as an electron-deficient and efficient triplet-generating host. Upon encapsulation of various carbazole-derived guests inside the nanocavity of this cyclophane, emissive charge transfer (CT) states close to the triplet energy level of the biphenyl bisimide are generated. The experimental results of host-guest studies manifest high association constants up to 104 M-1 as the prerequisite for inclusion complex formation, the generation of emissive CT states, and triplet-state stabilization in a diluted solution state. By means of different carbazole guest molecules, we could realize tunable delayed fluorescence emission in this carbazole-encapsulated biphenyl bisimide cyclophane in methylcyclohexane/carbon tetrachloride solutions with a quantum yield (QY) of up to 15.6%. Crystal structure analyses and solid-state photophysical studies validate the conclusions from our solution studies and provide insights into the delayed fluorescence emission mechanism.

Energy transfer and conversion in the Allam cycle with a multi-stream heat exchanger

The Allam cycle is renowned for its high efficiency and low emissions in power generation, utilizing supercritical carbon dioxide as the working fluid. The regenerator, one of the key heat exchangers, plays a crucial role in the system. However, modeling the regenerator is challenging due to the presence of multiple pinch points. This study proposes a regenerator model that employs three multi-stream heat exchanger modules in Aspen Plus. A thermodynamic and economic analysis of the system was conducted and compared with a conventional system utilizing the two multi-stream heat exchanger modules. Simulation results show that the combustion chamber has the highest exergy loss in the system, accounting for 46.9 % of the total exergy loss. The turbine is identified as the most capital-intensive component, representing 44.9 % of the total equipment investment. Furthermore, a sensitivity analysis was conducted on key parameters. The results indicate that under certain operating conditions, the heat provided by the air separation unit is insufficient to reduce the temperature difference at the hot outlet of the regenerator. Compared to the conventional Allam cycle system using the 2R model, the 2R model predicts deviations of up to 28.9 %. This proposed model provides a new approach for the efficient allocation of energy utilization in the multi-stream heat exchange process within the Allam cycle system.

Biogas-to-Power Systems Based on Solid Oxide Fuel Cells: Thermodynamic Analysis of Stack Integration Strategies

Biogas presents a renewable fuel source with substantial potential for reducing carbon emissions in the energy sector. Exploring this potential in the farming sector is crucial for fostering the development of small-scale distributed biogas facilities, leveraging indigenous resources while enhancing energy efficiency. The establishment of distributed biogas plants bolsters the proportion of renewable energy in the energy matrix, necessitating efficient power generation technologies. Given their proximity to bio-waste production sites like farms and digesters, optimising combined heat and power generation systems is imperative for energy self-sufficiency. Small-scale biogas facilities demand specific power generation technologies capable of achieving notable efficiencies, ranging from 40% to 55%. This study focuses on employing Solid Oxide Fuel Cells (SOFCs) in biogas-to-power systems and investigates the theoretical operation of SOFCs with fuel mixtures resulting from different biogas lean upgrading pathways. Therefore, starting from ten mixtures including CH4, CO2, H2, H2O, N2, and O2, the study proposes a method to assess their impact on the electrochemical performance, degradation, and energy equilibrium of SOFC units. The model embeds thermodynamic equilibrium, the Nernst potential, and energy balance, enabling a comprehensive comparison across these three analytical domains. The findings underscore the unsuitability of dry biogas and dry biomethane due to the potential risk of carbon deposition. Moreover, mixtures incorporating CO2, with or without H2, present significant thermal balance challenges.

Second harmonic generation of focused beams on the LFEX laser facility

There is a strong demand for efficient second harmonic generation (SHG) in ultra-intense short-pulse lasers. This paper demonstrates the generation of an unconverted fundamental (1ω)+second harmonics (2ω) mixed laser on the LFEX laser system. The experimental setup utilizes 0.5 mm-thick LBO crystal plates in a focusing beams implemented after an off-axis parabola, the design reduces the size and cost of the SHG system. The LFEX laser beams with four-beams combined energy of 222 J and a pulse duration of 1.5 ps, is successfully converted to 102 J of 2ω light and 100 J of unconverted 1ω light, 20 J is lost through surface reflections, and they are mixed at the focal point. Verification of successful SHG is confirmed through X-ray pinhole imaging and electron spectrometry. This novel technique is not limited to LFEX lasers and holds applicability for various ultra-intense lasers. Consequently, this accomplishment significantly contributes to expanding the capability for high-energy density laser-plasma experiments.

Influence of surface roughness on vibration response characteristics of flexible structures on offshore floating platforms

The expanding interest in floating offshore renewable energy technologies, including floating wind turbines and solar platforms, is attributed to their multifarious benefits. One pivotal factor influencing the power generation efficiency of these technologies is the vibration response of the flexible structures connected to the platforms, such as mooring systems, dynamic power cables, and flexible pipelines. In this research, a numerical investigation is conducted on the response characteristics of vortex-induced vibration (VIV) of cylinders with varying surface roughness in oscillatory flow. The unsteady Reynolds-averaged Navier-Stokes (URANS) equations and dynamic equation are used for fluid-structure interaction. The results reveal that for rough cylinders, multiple frequencies are involved in the vibration. For most simulated cases, the vibration frequency in the cross-flow (CF) direction is an integer multiple of the frequency of the oscillatory flow and associated with the quantity of shedding vortex pairs during a single period of the oscillatory flow. For rough cylinders, the CF vibration frequency differs by one from the number of shedding vortex pairs within one period of the oscillatory flow. With the increase of surface roughness, the maximum vibration amplitude shows an increasing trend (12%), then a decreasing trend (21%). Furthermore, the vortex shedding flow pattern presents C + S mode or S mode. This study offers valuable insights for analyzing the vibration response characteristics of authentic flexible structures.

A novel higher rotational speed maintaining control for wind power generation systems under unstable wind conditions

This study proposes Higher Rotational Speed Maintaining (HRSM) control as a novel control algorithm that is suitable for large wind speed fluctuations. One of the challenges for wind generators is operating with significant wind speed oscillations. A wind generator with a large moment of inertia increases the time constant in rotational speed control and delays the tracking of the optimal operating point. It could reduce generated power by up to 40% or more. There are numerous regions in Japan’s inland areas where average wind speeds exceed 6.5 m/s. However, frequent fluctuations in wind speeds make wind power generation challenging. Therefore, this paper proposes a control algorithm suitable for wind turbines under unstable wind conditions. Higher rotational speeds are required to convert sudden high wind speeds into higher power when wind speed oscillations are large. Hence, the proposed algorithm focuses on maintaining the rotational speed throughout periods of unstable wind conditions for improving generation efficiency. The effectiveness of the proposed control method for wind turbines is verified via numerical simulation results. The novel control algorithm promotes the spread of wind turbines in unstable wind conditions area by overcoming the disadvantages.

Local parallel free generation and dynamic affine transformation method for soil three-dimensional pore structure information model

The soil three-dimensional (3D) pore structure information model has become a new hotspot in the research of cross-scale disposal of information such as ecology, engineering, and geology. It can solve problems such as the intelligent evaluation of ecological water–soil–air–plant feedback, intelligent risk control of foundation compression deformation, and multiscale intelligent disaster prediction and prevention. However, the current soil 3D pore structure model primarily draws on the global one-time static generation in simulation software, leading to low reliability, low stability of multiple generations, poor variability, difficulty in real-time transformation, high consumption of computing resources, and long generation time, making it challenging to meet the requirements of the rapid processing of information models. Therefore, this study adopts the 3D Drawing Protocol (WebGL) technology and implements the scaling, rotation, and translation transformation of 3D pore structures based on the principle of dynamic affine transformation. The random generation and distribution of pores are realized using the improved Monte Carlo method, and the loading response efficiency of the system is optimized. The dynamic interactive operation of arbitrary increasing and decreasing of pore model is realized using the ray and plane intersection detection principle. Finally, this information system established a visual correlation between the content and reaction time of water-retaining agents and soil porosity and pore distribution through tests on the impact of water-retaining agents on soil pore changes. The information system achieved the real-time tracking of soil pore changes under the action of water-retaining agents. This research solves the problems of static and low generation efficiency of the soil mesopore structure in traditional models and realizes the real-time characterization and visualization of dynamic changes and the distribution of the soil pore structure under the influence of external conditions, which can provide an intuitive visualization platform for mesogeological structure research.

Integrating Multipolar Structures and Carboxyl Groups in sp2-Carbon Conjugated Covalent Organic Frameworks for OverallPhotocatalytic Hydrogen Peroxide Production.

The direct production of hydrogen peroxide (H2O2) through photocatalytic reaction via H2O and O2 is considered as an ideal approach. However, the efficiency of H2O2 generation is generally limited by insufficient charge and mass transfer. Covalent organic framework (COFs) offer a promising platform as metal-free photocatalyst for H2O2production due to their potential for rational design at the molecular level. Herein, we integrated the multipolar structures and carboxyl groups into COFs to enhance the efficiency of photocatalytic H2O2 production in pure water without any sacrificial agents. The introduction of octupolar and quadrupolar structures, along with an increase of molecular planarity, created efficient oxygen reduction reaction (ORR) sites. Meanwhile, carboxyl groups could not only boost O2 and H2O2 movement via enhancement of pore hydrophilicity, but also promote proton conduction, enabling the conversion to H2O2 from ·O2-, which is the crucial intermediate product in H2O2 photocatalysis. Overall, we demonstrate that TACOF-1-COOH, consisting of optimal octupolar and quadrupolar structures, along with enrichment sites (carboxyl groups), exhibited a H2O2 yield rate of 3542 μmol h-1 g-1 and a solar-to-chemical (SCC) efficiency of 0.55%. This work provides valuable insights for designing metal-free photocatalysts for efficient H2O2 production.

Numerical Simulation Method of Hydraulic Power Take-Off of Point-Absorbing Wave Energy Device Based on Simulink

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been the focus of research by scholars from various countries. The energy conversion mechanism in wave energy devices is called PTO (power take-off). According to different working principles, PTOs can be classified into the linear motor type, hydraulic type, and mechanical type. Hydraulic PTOs are characterized by their high efficiency, low cost, and simple installation. They are widely used in the energy conversion links of various wave energy devices. However, apart from experimental methods, there is currently almost no concise numerical method to predict and evaluate the power generation performance of hydraulic PTO. Therefore, based on the working principle of hydraulic PTO, this paper proposes a numerical method to simulate the performance of a hydraulic PTO using MATLAB(2018b) Simulink®. Using a point-absorption wave energy device as a carrier, a float hydraulic system power-generation numerical model is built. The method is validated by comparison with previous experimental results. The predicted power generation and conversion efficiency of the point-absorption wave energy device under different regular and irregular wave conditions are compared. Key factors affecting the power generation performance of the device were investigated, providing insight for the subsequent optimal design of the device, which is of great significance to the development and utilization of wave energy resources.

How much ICT literacy is required? The epistemic perceptual framework of Iranian university faculty members during the COVID-19 pandemic

Nowadays, information and communications technology literacy (ICT) means more than achieving isolated digital and technological skills. ICT literacy means the skills young people need in the digital world in which information and interaction are accessed through such digital technologies as social networks, virtual environments, and smartphones. To enhance the ICT literacy of these “digital natives”, university faculty are encouraged to implement digital technology in their classes and this will be fulfilled if they are highly competent in the area. This situation gained more prominence during the COVID-19 pandemic as the educational systems all around the world were reshaped requiring educators to embrace new educational technologies in instruction. This study is based on the premise that faculties play a key role in successful incorporation of digital technology in higher education. To explore the issue, the epistemic perceptual framework of 285 male and female university faculty members teaching different fields of study in both public and private universities in Iran was investigated considering their knowledge and perception of ICT literacy, its integration at academic levels, and how coronavirus pandemic has affected the incorporation of digital technology in teaching. Exploring the results showed that there was a significant difference between the lecturers’ actual and perceived ICT literacy in Iran. It was revealed that some faculty had never used technological tools in their classes before the pandemic and the situation has forced them to adopt digital teaching. However, most faculty favored digital integration claiming the pandemic had caused them to improve their ICT literacy and teaching methods. The findings called for an urgent need for faculty’s continuous and effective ICT education upgrading which in turn results in training a more efficient young generation for the digital world.

Research on detection method of photovoltaic cell surface dirt based on image processing technology

In view of the reduced power generation efficiency caused by ash or dirt on the surface of photovoltaic panels, and the problems of heavy workload and low efficiency faced by manual detection, this study proposes a method to detect dust or dust on the surface of photovoltaic cells with the help of image processing technology to timely eliminate hidden dangers and improve power generation efficiency.This paper introduces image processing methods based on mathematical morphology, such as image enhancement, image sharpening, image filtering and image closing operation, which makes the image better highlight the target to be recognized. At the same time, it also solves the problem of uneven image binarization caused by uneven illumination in the process of image acquisition. By using the image histogram equalization, the gray level concentration area of the original image is opened or the gray level is evenly distributed, so that the dynamic range of the pixel gray level is increased, so that the image contrast or contrast is increased, the image details are clear, to achieve the purpose of enhancement. When identifying the target area, the method of calculating the proportion of the dirt area to the whole image area is adopted, and the ratio exceeding a certain threshold is judged as a fault. In addition, the improved A* path planning algorithm is adopted in this study, which greatly improves the efficiency of the unmanned aerial vehicle detection of photovoltaic cell dirt, saves time and resources, reduces operation and maintenance costs, and improves the operation and maintenance level of photovoltaic units.

Observation of Fast Low-Temperature Oxygen Ion Conduction in CeO2/β"-Al2O3 Heterostructure.

Semiconductor ion fuel cells (SIFCs) have demonstrated impressive ionic conductivity and efficient power generation at temperatures below 600°C. However, the lack of understanding of the ionic conduction mechanisms associated with composite electrolytes has impeded the advancement of SIFCs toward lower operating temperatures. In this study, a CeO2/β″-Al2O3 heterostructure electrolyte is introduced, incorporating β″-Al2O3 and leveraging the local electric field (LEF) as well as the manipulation of the melting point temperature of carbonate/hydroxide (C/H) by Na+ and Mg2+ from β″-Al2O3. This design successfully maintains swift interfacial conduction of oxygen ions at 350°C. Consequently, the fuel cell device achieved an exceptional ionic conductivity of 0.019S/cm and a power output of 85.9mW/cm2 at 350°C. The system attained a peak power density of 1W/cm2 with an ultra-high ionic conductivity of 0.197S/cm at 550°C. The results indicate that through engineering the LEF and incorporating the lower melting point C/H, there approach effectively observed oxygen ion transport at low temperatures (350°C), effectively overcoming the issue of cell failure at temperatures below 419°C. This study presents a promising methodology for further developing high-performance semiconductor ion fuel cells in the low temperature range of 300-600°C.