Representative 2D Research Articles

Coexistence of Redox-Active Metal and Ligand Sites in Copper-Based Two-Dimensional Conjugated Metal-Organic Frameworks as Active Materials for Battery-Supercapacitor Hybrid Systems.

Two-dimensional (2D) conjugated metal-organic frameworks (c-MOFs) are promising materials for supercapacitor (SC) electrodes due to their high electrochemically accessible surface area coupled with superior electrical conductivity compared to traditional MOFs. In this work, porous and non-porous HHB-Cu (HHB=hexahydroxybenzene), derived through surfactant-assisted synthesis are studied as representative 2D c-MOF models with different characteristics, showing diverse reversible redox reactions with Na+ and Li+ in aqueous (10 M NaNO3) and organic (1.0 M LiPF6 in ethylene carbonate and dimethyl carbonate) electrolytes, respectively. These redox activities were here deployed to design negative electrodes for hybrid SCs (HSCs), combining the battery-like property of HHB-Cu at the negative electrode and the high capacitance and robust cyclic stability of activated carbon (AC) at the positive electrodes. In the organic electrolyte, porous HHB-Cu-based HSC achieves a maximum cell specific capacity (Cs) of 22.1 mAh g-1 at 0.1 A g-1, specific energy (Es) of 15.55 Wh kg-1 at specific power (Ps) of 70.49 W kg-1, and 77 % cyclic stability after 3000 gravimetric charge-discharge (GCD) cycles at 1 A g-1 (specific metrics calculated on the mass of both electrode materials). In the aqueous electrolyte, porous HHB-Cu-based HSC displays a Cs of 13.9 mAh g-1 at 0.1 A g-1, Es of 6.13 Wh kg-1 at 44.05 W kg-1, and 72.3 % Cs retention after 3000 GCD cycles. The non-porous sample, interesting for its superior electrical conductivity despite its limited surface area compared to its porous counterpart, shows lower Es performance but better rate capability compared to the porous one. This study indicates the potential of assembling a battery-SC hybrid system by rationally exploiting the battery-like behavior of 2D c-MOFs and the electrochemical double-layer capacitance of AC.

Two-Dimensional Organic-Inorganic van der Waals Hybrids.

Two-dimensional organic-inorganic (2DOI) van der Waals hybrids (vdWhs) have emerged as a groundbreaking subclass of layer-stacked (opto-)electronic materials. The development of 2DOI-vdWhs via systematically integrating inorganic 2D layers with organic 2D crystals at the molecular/atomic scale extends the capabilities of traditional 2D inorganic vdWhs, thanks to their high synthetic flexibility and structural tunability. Constructing an organic-inorganic hybrid interface with atomic precision will unlock new opportunities for generating unique interfacial (opto-)electronic transport properties by combining the strengths of organic and inorganic layers, thus allowing us to satisfy the growing demand for multifunctional applications. Here, this review provides a comprehensive overview of the latest advancements in the chemical synthesis, structural characterization, and numerous applications of 2DOI-vdWhs. Firstly, we introduce the chemistry and the physical properties of the recently rising organic 2D crystals (O2DCs), which feature crystalline 2D nanostructures comprising carbon-rich repeated units linked by covalent/noncovalent bonds and exhibit strong in-plane extended π-conjugation and weak interlayer vdWs interaction. Simultaneously, representative inorganic 2D crystals (I2DCs) are briefly summarized. After that, the synthetic strategies will be systematically summarized, including synthesizing single-component O2DCs with dimensional control and their vdWhs with I2DCs. With these synthetic approaches, the control in the dimension, the stacking modes, and the composition of the 2DOI-vdWhs will be highlighted. Subsequently, a special focus will be given on the discussion of the optical and electronic properties of the single-component 2D materials and their vdWhs, which will be closely relevant to their structures, so that we can establish a general structure-property relationship of 2DOI-vdWhs. In addition to these physical properties, the (opto-)electronic devices such as transistors, photodetectors, sensors, spintronics, and neuromorphic devices as well as energy devices will be discussed. Finally, we provide an outlook to discuss the key challenges for the 2DOI-vdWhs and their future development. This review aims to provide a foundational understanding and inspire further innovation in the development of next-generation 2DOI-vdWhs with transformative technological potential.

CT-based multimodal deep learning for non-invasive overall survival prediction in advanced hepatocellular carcinoma patients treated with immunotherapy

ObjectivesTo develop a deep learning model combining CT scans and clinical information to predict overall survival in advanced hepatocellular carcinoma (HCC).MethodsThis retrospective study included immunotherapy-treated advanced HCC patients from 52 multi-national in-house centers between 2018 and 2022. A multi-modal prognostic model using baseline and the first follow-up CT images and 7 clinical variables was proposed. A convolutional-recurrent neural network (CRNN) was developed to extract spatial-temporal information from automatically selected representative 2D CT slices to provide a radiological score, then fused with a Cox-based clinical score to provide the survival risk. The model’s effectiveness was assessed using a time-dependent area under the receiver operating curve (AUC), and risk group stratification using the log-rank test. Prognostic performances of multi-modal inputs were compared to models of missing modality, and the size-based RECIST criteria.ResultsTwo-hundred seven patients (mean age, 61 years ± 12 [SD], 180 men) were included. The multi-modal CRNN model reached the AUC of 0.777 and 0.704 of 1-year overall survival predictions in the validation and test sets. The model achieved significant risk stratification in validation (hazard ratio [HR] = 3.330, p = 0.008), and test sets (HR = 2.024, p = 0.047) based on the median risk score of the training set. Models with missing modalities (the single-modal imaging-based model and the model incorporating only baseline scans) can still achieve favorable risk stratification performance (all p < 0.05, except for one, p = 0.053). Moreover, results proved the superiority of the deep learning-based model to the RECIST criteria.ConclusionDeep learning analysis of CT scans and clinical data can offer significant prognostic insights for patients with advanced HCC.Critical relevance statementThe established model can help monitor patients’ disease statuses and identify those with poor prognosis at the time of first follow-up, helping clinicians make informed treatment decisions, as well as early and timely interventions.Key PointsAn AI-based prognostic model was developed for advanced HCC using multi-national patients.The model extracts spatial-temporal information from CT scans and integrates it with clinical variables to prognosticate.The model demonstrated superior prognostic ability compared to the conventional size-based RECIST method.Graphical

Extracting subleading corrections in entanglement entropy at quantum phase transitions

We systematically investigate the finite size scaling behavior of the Rényi entanglement entropy (EE) of several representative 2d quantum many-body systems between a subregion and its complement, with smooth boundaries as well as boundaries with corners. In order to reveal the subleading correction, we investigate the quantity “subtracted EE” S^s(l) = S(2l) - 2S(l)Ss(l)=S(2l)−2S(l) for each model, which is designed to cancel out the leading perimeter law. We find that (1) for a spin-1/2 model on a 2d square lattice whose ground state is the Neel order, the coefficient of the logarithmic correction to the perimeter law is consistent with the prediction based on the Goldstone modes; (2) for the (2+1)d(2+1)d O(3) Wilson-Fisher quantum critical point (QCP), realized with the bilayer antiferromagnetic Heisenberg model, a logarithmic subleading correction exists when there is sharp corner of the subregion, but for subregion with a smooth boundary our data suggests the absence of the logarithmic correction to the best of our efforts; (3) for the (2+1)d(2+1)d SU(2) J-Q_22 and J-Q_33 model for the deconfined quantum critical point (DQCP), we find a logarithmic correction for the EE even with smooth boundary.

The origins of dual-peak emission and anomalous exciton decay in 2D Sn-based perovskites.

Two-dimensional (2D) Sn-based perovskites exhibit significant potential in diverse optoelectronic applications, such as on-chip lasers and photodetectors. Yet, the underlying mechanism behind the frequently observed dual-peak emission in 2D Sn-based perovskites remains a subject of intense debate, and there is a lack of research on the carrier dynamics in these materials. In this study, we investigate these issues in a representative 2D Sn-based perovskite, namely, PEA2SnI4, through temperature-, excitation intensity-, angle-, and time-dependent photoluminescence studies. The results indicate that the high- and low-energy peaks originate from in-face and out-of-face dipole transitions, respectively. In addition, we observe an anomalous increase in the non-radiative recombination rate as temperature decreases. After ruling out enhanced electron-phonon coupling and Auger recombination as potential causes of the anomalous carrier dynamics, we propose that the significantly increased exciton binding energy (Eb) plays a decisive role. The increased Eb arises from enhanced electronic localization, a consequence of weakened lattice distortion at low temperatures, as confirmed by first-principles calculations and temperature-dependent x-ray diffraction measurements. These findings offer valuable insights into the electronic processes in the unique 2D Sn-based perovskites.

Design, synthesis, and biological evaluation of pyrido[2,3-d]pyrimidin-7(8H)-one derivatives as potent USP1 inhibitors

USP1 has emerged as a novel and potential target for drug discovery in single therapeutic agents or combination with chemotherapy and molecular targeted therapy. In this study, based on the disclosed structure of ML323 and KSQ-4279, we designed and synthesized a series of pyrido[2,3-d]pyrimidin-7(8H)-one derivatives as potent USP1 inhibitors by cyclization strategy and the systematic structure−activity relationship exploration was conducted. The representative compounds 1k, 1m and 2d displayed excellent USP1/UAF inhibition and exhibited strong antiproliferation effect in NCI–H1299 cells. Further flow cytometry analysis revealed that they could arrest breast cancer cells MDA-MB-436 in the S phase. Inhibition mechanism study of compound 1m indicated these derivatives acted as reversible and noncompetitive USP1 inhibitors. Of note, the combination of compound 1m with PARP inhibitor olaparib generated enhanced cell killing in olaparib-resistant MDA-MB-436/OP cells, and compound 1m exhibited excellent oral pharmacokinetic properties in mice. Overall, our efforts may provide a reliable basis for the development of novel USP1 inhibitor as a single therapeutic agent and in combination with PARP inhibitors.

Ultrathin LiF Insertion and Ensued Contact Resistance Reduction in MoS2 Channel Transistors

Molybdenum disulfide (MoS2) is a representative 2D n‐type semiconductor for various electron devices, but its lateral conduction performances are still restricted, which are mainly attributed to the contact resistance (Rc) in field‐effect transistors (FETs). Low‐enough Rc value must be realized toward practical device fabrications. Herein, 2D MoS2 FETs using chemical vapor deposited (CVD) MoS2 channels with and without the ultrathin LiF interlayer are fabricated, to demonstrate the practical benefits of LiF. In addition, LiF is also applied to Al metal which is known to be more Earth abundant than Au, expecting the similar positive effects of the inserted LiF. When 35 CVD‐grown MoS2 channel FETs with Au are characterized on an identical gate dielectric substrate, the higher value of mobility ranging 55–60 cm2 V s−1 is achieved with the inserted LiF than that without LiF (≈20 cm2 V s−1). In the case of another MoS2 FET with exfoliated flake channel and Al contact, its field‐effect mobility with LiF insertion appears to be ≈35 cm2 V s−1, approaching to an almost Rc‐free mobility (42 cm2 V s−1).

Electron-Phonon Interaction Mediated Gigantic Enhancement of Thermoelectric Power Factor Induced by Topological Phase Transition.

We propose an effective strategy to significantly enhance the thermoelectric power factor (PF) of a series of 2D semimetals and semiconductors by driving them toward a topological phase transition (TPT). Employing first-principles calculations with an explicit consideration of electron-phonon interactions, we analyze the electronic transport properties of germanene across the TPT by applying hydrogenation and biaxial strain. We reveal that the nontrivial semimetal phase, hydrogenated germanene with 8% biaxial strain, achieves a considerable 4-fold PF enhancement, attributed to the highly asymmetric electronic structure and semimetallic nature of the nontrivial phase. We extend the strategy to another two representative 2D materials (stanene and HgSe) and observe a similar trend, with a marked 7-fold and 5-fold increase in PF, respectively. The wide selection of functional groups, universal applicability of biaxial strain, and broad spectrum of 2D semimetals and semiconductors render our approach highly promising for designing novel 2D materials with superior thermoelectric performance.

Analytic representative element rate decline models for naturally fractured reservoir depletion

Representative single anisotropic matrix block 2D Green’s function models for depletion through fully-penetrating, vertical fractures through different numbers of fracture faces are constructed that analytically capture both fracture and block depletion with fracture-matrix mass transfer. The 1D Green’s function for a fracture system is likewise solved in terms of the time evolution of average fracture pressure. While transient average pressure values are not inherently measurable, they are transformed into cumulative production or instantaneous flowrate values, thus producing new rate decline model functional forms. Primary variables in assembling the interacting systems model are the volume ratio, Vf /Vm, permeability ratio, kf /kx, and geometry, (a/b)(ky/kx), with the last term accounting for both block shape and permeability anisotropy. We construct interacting systems models in terms of various ratios of Vf /Vm, and kf /kx for three fracture architecture prototypes: representative matrix blocks depleted by 4, 2, or 1 contacting fractures. The single matrix block models can be migrated to ones for heterogeneous systems using superposition and matrix block distributions, as demonstrated with a binary distribution of block sizes with variable fractions. Analytic solutions for rate decline problems can be used to understand the production signatures of naturally fractured reservoirs and interpretation of fracture volume fraction, permeability ratio, average matrix block size, and measures of heterogeneity.

Growth of Noncentrosymmetric Two-Dimensional Single Crystals.

Among the various two-dimensional (2D) materials, more than 99% of them are noncentrosymmetric. However, since the commonly used substrates are generally centrosymmetric, antiparallel islands are usually inevitable in the growth of noncentrosymmetric 2D materials because of the energetic equivalency of these two kinds of antiparallel islands on centrosymmetric substrates. Therefore, achieving the growth of noncentrosymmetric 2D single crystals has long been a great challenge compared with the centrosymmetric ones like graphene. In this review, we presented the remarkable efforts and progress in the past decade, through precise chemical processes. We first discussed the great challenge and possible strategies in the growth of noncentrosymmetric 2D single crystals. Then, we focused on the advancements made in producing representative noncentrosymmetric 2D single crystals, including hexagonal boron nitride (hBN), transition metal dichalcogenides (TMDs), and other noncentrosymmetric 2D materials. At last, we summarized and looked forward to future research on the growth of layer-, stacking-, and twist-controlled noncentrosymmetric 2D single crystals and their heterostructures.

Fabrication of Two-Dimensional Material Membranes

Membrane separation is an energy-efficient separation process. Two-dimensional (2D) materials have shown potential as a new generation of membrane materials due to their unique structures and physicochemical properties. The separation performance of 2D material membranes crucially depends on how 2D nanosheets are assembled in membranes, such as interlayer spacing between stacked nanosheets, chemical properties of nanosheet surfaces, alignment of nanosheets and thickness of membranes, which are closely related to their fabrication methods. This short review concisely overviews commonly used membrane fabrication methods for different types of 2D materials, including graphene-based materials, 2D covalent organic frameworks, 2D metal-organic frameworks, MXenes and other 2D materials. The representative 2D material membranes resulting from their essential fabrication methods are discussed. The advantages and shortcomings of different fabrication methods are compared. The critical challenges to realising large-scale production of 2D material membranes for practical applications are highlighted.

A combined cyclic viscoplasticity and entropy generation approach for modelling fatigue crack growth behavior of a nickel-based superalloy at high temperature

This paper developed an entropy-based approach to estimate the fatigue crack growth (FCG) behavior of GH4169 at high temperature. Firstly, systematic FCG experiments of GH4169 at 650 °C were conducted to obtain the experimental data. Then, a finite element analysis combined with Chaboche viscoplasticity and node release technology was developed to obtain cyclic stress–strain responses and entropy generation fields. Based on thermodynamic analysis, numerous discrete material elements as sub-systems were divided along the crack growth direction in simplified representative 2D middle section. Fracture process zone (FPZ) was defined equal to the size of discrete material elements (ρ) which can be determined by distribution of normal stress perpendicular to the crack plane. Subsequently, an effective cyclic entropy generation related to ρ was defined as the crack driving force. Effective cumulative entropy generation was calculated when crack increment was ρ and the results indicated that effective cumulative entropy generation float within a certain range. The average of all effective cumulative entropy generation values was defined as crack growth entropy. Finally, an entropy-based FCG rate model was established to estimate the FCG behavior of GH4169, and a good correlation between experimental results and model predictions are achieved for all the high temperature FCG tests.

Bifunctional 2D structured catalysts for air electrodes in rechargeable metal-air batteries

The inherent technical challenges of metal-air batteries (MABs), arising from the sluggish redox electrochemical reactions on the air electrode, significantly affect their efficiency and life cycle. Two-dimensional (2D) nanomaterials with near-atomic thickness have potential as bifunctional catalysts in MABs because of their distinct structures, exceptional physical properties, and tunable surface chemistries. In this study, the chemistry of representative 2D materials was elucidated, and the comprehensive analysis of the primary modification techniques, including geometric structure manipulation, defect engineering, crystal facet selection, heteroatom doping, single-atom catalyst construction, and composite material synthesis, was conducted. The correlation between material structure and activity is illustrated by examples, with the aim of leading the development of advanced catalysts in MABs. We also focus on the future of MABs from the perspective of bifunctional catalysts, definite mechanisms, and standard measurement. We expect this work to serve as a guide for the design of air electrode materials that can be used in MABs.

The thermoelastic properties of monolayer covalent organic frameworks studied by machine-learning molecular dynamics.

Two-dimensional (2D) covalent organic frameworks (COFs) are emerging as promising 2D polymeric materials with broad applications owing to their unique properties, among which the mechanical properties are quite important for various applications. However, the mechanical properties of 2D COFs have not been systematically studied yet. Herein, a machine-learned neuroevolution potential (NEP) was developed to study the elastic properties of two representative monolayer 2D COFs, namely COF-1 and COF-5. The trained NEP enables one to study the elastic properties of 2D COFs in realistic situations (e.g., finite size and temperature) and possesses greatly improved computational efficiency when compared with density functional theory calculations. With the aid of the obtained NEP, molecular dynamics (MD) simulations together with a strain-fluctuation method were employed to evaluate the elastic constants of the considered 2D COFs at different temperatures. The elastic constants of COF-1 and COF-5 monolayers were found to decrease with an increase in the temperature, though they were almost isotropic irrespective of the temperature. The thermally induced softening of 2D COFs below a critical temperature was observed, which is mainly attributed to their inherent ripple configurations at finite temperatures, while above the critical temperature, the damping effect of anharmonic vibrations became the dominant factor. Based on the proposed mechanisms, analytical models were developed for capturing the temperature dependence of elastic constants, which were found to agree with the MD simulation results well. This work provides an in-depth insight into the thermoelastic properties of monolayer COFs, which can guide the development of 2D COF materials with tailored mechanical behaviors for enhancing their performance in various applications.

Layer-by-layer thinning of two-dimensional materials.

Etching technology - one of the representative modern semiconductor device makers - serves as a broad descriptor for the process of removing material from the surfaces of various materials, whether partially or entirely. Meanwhile, thinning technology represents a novel and highly specialized approach within the realm of etching technology. It indicates the importance of achieving an exceptionally sophisticated and precise removal of material, layer-by-layer, at the nanoscale. Notably, thinning technology has gained substantial momentum, particularly in top-down strategies aimed at pushing the frontiers of nano-worlds. This rapid development in thinning technology has generated substantial interest among researchers from diverse backgrounds, including those in the fields of chemistry, physics, and engineering. Precisely and expertly controlling the layer numbers of 2D materials through the thinning procedure has been considered as a crucial step. This is because the thinning processes lead to variations in the electrical and optical characteristics. In this comprehensive review, the strategies for top-down thinning of representative 2D materials (e.g., graphene, black phosphorus, MoS2, h-BN, WS2, MoSe2, and WSe2) based on conventional plasma-assisted thinning, integrated cyclic plasma-assisted thinning, laser-assisted thinning, metal-assisted splitting, and layer-resolved splitting are covered in detail, along with their mechanisms and benefits. Additionally, this review further explores the latest advancements in terms of the potential advantages of semiconductor devices achieved by top-down 2D material thinning procedures.

Engineering of the perovskite/electron-transporting layer interface with transition metal chalcogenides for improving the performance of inverted perovskite solar cells

Representative 2D transition metal chalcogenides (InSe, SnS2, MoSe2) were placed at the perovskite/ETL interface in inverted perovskite solar cells to improve performance and stability.

Crustal and tectonic structure of Northern Mozambique inferred by 2D gravity modeling

The northern region of Mozambique has a complex geological history, with an evolution that spans from the Precambrian Era to the Phanerozoic Era. In this work, we have integrated gravity and geothermal data to delineate the geotectonic evolution of the region, by estimating the thickness of the crust and the lithosphere through which was essential to generate a representative crustal model. It was necessary to complement the knowledge of structural geometry and tectonic evolution of the region. The data used in this study are the Bouguer and geoid anomalies, topography data, and radiogenic heat. These data were pre-processed, topography and geoid anomaly data were filtered by low-pass filter in the frequency and harmonic domains to remove undesirable effects associated with the sources. The data were used to estimate the thickness of the crust and lithosphere, as well as to determine the mean density distribution within the mantle. This was achieved by using a one-dimensional approach, considering the principle of local isostatic compensation, associated with equations governing the distribution of temperature in the crust. The Bouguer anomaly was used to generate a representative crustal 2D model of this region. The results showed that the crust is thinner in Nampula and Cabo Delgado provinces, with thickness ranging from 27 to 31 km, whereas in Niassa varies between 33 and 39 km. The analysis of lithospheric thickness indicates that the provinces of Nampula and Cabo Delgado present a thinning of the lithosphere, with values ranging from 150 to 165 km. Rather than Niassa province which exhibits a thicker lithosphere, ranging from 165 to 195 km. The obtained results underwent a comparative analysis with prior investigations, unveiling a noteworthy concurrence among these findings.

An accurate and efficient multiphysics 3D model for the design and operation analysis of production-scale solid oxide cell stacks

A rapid and reliable numerical model to predict solid oxide cell (SOC) stack behaviors is essential for technology advancement. This work reports the development of an accurate and efficient multiphysics model for production-scale SOC stacks. An analytical model is constructed to consider the ohmic resistance of current conduction in thin electrodes, simplifying modeling process. The model demonstrates good agreement with experimental I–V curves. A detailed mesh optimization is performed for all components of SOC stacks to ensure grid independence in flow, electrochemistry, and thermal fields. Moreover, a well-designed simulation strategy is presented, contributing equally to the computational efficiency as mesh optimization. A multiphysics simulation of a 5 kW SOEC stack takes only 50 min on a 2-CPU/24-core workstation, demonstrating the applicability of the model. The fuel uniformity of a H2O-SOEC (H2-SOFC) stack is found to increase (decrease) with increased fuel utilization, with underlying mechanism revealed through a representative 2D flow model.

Machine learning interatomic potentials as efficient tools for obtaining reasonable phonon dispersions and accurate thermal conductivity: A case study of typical two-dimensional materials

The accurate description of phonon dispersion of two-dimensional (2D) materials demonstrates significance in many research fields of condensed matter physics. In this paper, we systematically calculate the phonon spectra and transport properties of six representative 2D materials (encompassing single-element and binary compounds with flat, buckled, and puckered backbone geometries) by means of density functional theory (DFT) and two machine learning interatomic potentials [MLIPs, on-the-fly machine learning potential (FMLP), and moment tensor potential (MTP)]. The results show that the acoustic out-of-plane flexural (ZA) dispersion of the 2D materials are always and easily exhibiting non-quadratic dispersion phenomena near the center of the Brillouin zone by using the pure DFT calculation method. This phenomenon contradicts physics and reflects intuitively from the non-zero group velocity at Γ point. However, no matter which MLIP (FMLP/MTP) the calculation is based on, it could solve such behavior perfectly, where the ZA mode conforms to the quadratic dispersion relationship in the long-wavelength limit. Our results further demonstrate that compared to the pure DFT calculation, the FMLP and MTP method could quickly and relatively accurately obtain the lattice thermal conductivities of graphene, silicene, phosphorene, SiC, MoS2, and GeS. The findings presented in this work provide a solution about the pseudophysical phenomenon of ZA dispersions in 2D materials with the pure DFT calculation, which will greatly facilitate research areas such as phonon thermal transport, flexural mechanics, and electron–acoustic coupling.

Efficient PbSe Quantum Dot Infrared Photovoltaic Applying MXene Modified ZnO Electron Transport Layer

AbstractInfrared (IR) solar cells are potential optoelectronic devices for boosting the power conversion efficiency (PCE) of conventional photovoltaics (such as pervoskite and silicon solar cells) by broadening the utilization range of the sunlight spectrum to short‐wavelength infrared region. PbSe colloidal quantum dots (QDs) are one of the optimal candidates for IR solar cells because of their tunable bandgap in the IR region and flexible solution processibility. At present, the best PbSe QD IR photovoltaics generally adopt ZnO as an electron transport layer (ETL). However, the intrinsic drawbacks and surface defects of ZnO can potentially deteriorate the PCE of devices. Herein, Ti3C2Tx, a representative 2D transition carbide, is combined with sol‐gel ZnO to develop a new hybrid ETL for fabricating high‐performance IR solar cells. This combination effectively suppresses the defects within ZnO by forming new bondings and simultaneously enhances the crystalline of ZnO film. Meanwhile, the introduction of Ti3C2Tx into ZnO film accelerates the transport and collection of photo‐generated carriers by constructing a new electron transport pathway. Consequently, compared to the bare devices, the infrared PCE of PbSe QD solar cells increases by 19.5% to 1.04%. These results demonstrate that this hybrid ETL can offer a bright approach for developing high‐performance optoelectronic devices.