3D Diffusion Research Articles

The Impact of Temperature on the Adiabaticity and Coverage of a Single Shallow Cumulus Cloud

AbstractThe uncertainty of climate projection is significantly related to warm cloud feedback, which involves a complex interplay of various mechanisms. However, it is hard to unentangle temperature's impact on a single cloud with experiments, since the cloud dynamics always covary with environmental thermodynamical conditions. In this study, we investigate a simulated single shallow cumulus cloud's response to temperature using two perturbation methods, namely “uniform” and “buoyancy‐fixed”, the latter of which keeps the buoyancy profile unchanged in temperature perturbation. High‐resolution large eddy simulations show that uniform warming significantly increases cloud buoyancy, reducing cloud adiabaticity. If buoyancy is fixed, warming only reduces cloud area, leaving adiabatic fraction almost unchanged. Such a response can be explained by the Clausius‐Clapeyron effect with an idealized 1D diffusion model, showing that warming increases the cloud‐environment absolute humidity difference more than the increase in cloud liquid water content, resulting in a faster loss in both cloud coverage and total liquid water solely by lateral mixing. The responses of cloud coverage and total liquid water counteract, making adiabatic fraction insensitive to temperature change. Our work shows that the cloud adiabatic fraction's response to temperature is sensitive to the perturbed structure of the boundary layer, and the cloud coverage reduction by diffusion acts as a positive cloud feedback mechanism in addition to the adjustment processes of the boundary layer.

A Comparison Between the Reduction Behavior of DRI and BF Pellets in H2 and CO Atmospheres

AbstractThe reduction behavior of two different iron ore pellets that are used in blast furnace (BF) and direct reduction (DRI) was investigated in this research. Single pellets reduction experiments were conducted isothermally using pure CO and H2 as reducing agent in the temperature range 700 °C to 1100 °C. Reduction by H2 was significantly faster than reduction by CO for both pellets and reduction rate increased with increasing the temperature. When CO was used as the reducing agent, the BF pellet achieved a reduction degree of 32% at 700 °C and 67% at 800 °C, while the DRI pellet reached 28% and 59% at the same temperatures. This difference is due to the lower magnetite content in BF pellets (1.93%) compared to DRI pellets (9.11%). However, at 1000 °C and 1100 °C, the DRI pellet achieved 93% and 100% reduction, and the BF pellet 88% and 94%, respectively, due to the higher porosity in the DRI pellet (38%) compared to BF (32%). Kinetics controlling model for hydrogen reduction of both pellets suggested as D2 (2D Diffusion through the solid ash), however, A1 (1D Nucleation and growth) and R3 (3D Chemical reaction) were found as the most compatible models for CO reduction of DRI and BF pellets, respectively. Graphical Abstract

Single-molecule visualization of sequence-specific RNA binding by a designer PPR protein.

Pentatricopeptide repeat proteins (PPR) are a large family of modular RNA-binding proteins, whereby each module can be modified to bind to a specific ssRNA nucleobase. As such, there is interest in developing 'designer' PPRs (dPPRs) for a range of biotechnology applications, including diagnostics or in vivo localization of ssRNA species; however, the mechanistic details regarding how PPRs search for and bind to target sequences is unclear. To address this, we determined the structure of a dPPR bound to its target sequence and used two- and three-color single-molecule fluorescence resonance energy transfer to interrogate the mechanism of ssRNA binding to individual dPPRs in real time. We demonstrate that dPPRs are slower to bind longer ssRNA sequences (or could not bind at all) and that this is, in part, due to their propensity to form stable secondary structures that sequester the target sequence from dPPR. Importantly, dPPR binds only to its target sequence (i.e. it does not associate with non-target ssRNA sequences) and does not 'scan' longer ssRNA oligonucleotides for the target sequence. The kinetic constraints imposed by random 3D diffusion may explain the long-standing conundrum of why PPR proteins are abundant in organelles, but almost unknown outside them (i.e. in the cytosol and nucleus).

Pyrolysis features of Dracaena draco lignocellulosic fibers: Kinetic and thermodynamic analysis at various heating rates through coats-redfern method

This study evaluated the thermokinetic and thermodynamic properties of Dracaena draco fibers (DDFs) through thermogravimetric analysis (TGA). The DDFs underwent non-isothermal heating in a nitrogen atmosphere, with 5, 10, and 20 °C/min heating rates starting at 20 °C and reaching 800 °C. TGA analysis demonstrated that the pyrolysis of DDFs took place in three clearly defined phases: dehydration, devolatilization, and solid biochar. The thermokinetic and thermodynamic properties were computed for the devolatilization phase of mass reduction. The Coats-Redfern technique employed twenty-one separate kinetic equations derived from four fundamental solid-state reaction processes. Out of all the diffusivity models (DMs), the Ginstlinge-Brounshtein (DM5), Jander (3D diffusion) (DM7), and Ginstling models (DM8) had the best fit, as indicated by their highest coefficient of regression values (R2 > 0.990) across all the three heating rates. The activation energy values found by the DM5, DM7, and DM8 models are 76.5, 82.32, and 76.47 kJ/mol, respectively, for the 5 °C/min heating rate. The thermodynamic variables, including the entropy, free energy, and enthalpy change, were calculated based on the kinetic data. The study’s findings are significant for evaluating the DDFs' potential as an energy source, constructing reactors, producing chemicals, and understanding the DDFs’s features for composite synthesis.

ReMiND: Recovery of missing neuroimaging using diffusion models with application to Alzheimer’s disease

Abstract Missing data is a significant challenge in medical research. In longitudinal studies of Alzheimer’s disease (AD) where structural magnetic resonance imaging (MRI) is collected from individuals at multiple time points, participants may miss a study visit or drop out. Additionally, technical issues such as participant motion in the scanner may result in unusable imaging data at designated visits. Such missing data may hinder the development of high-quality imaging-based biomarkers. To address the problem of missing MRI data in studies of AD, we introduced a novel 3D diffusion model specifically designed for imputing missing structural MRI (Recovery of Missing Neuroimaging using Diffusion models (ReMiND)). The model generates a whole-brain image conditional on a single structural MRI observed at a past visit or conditional on one past and one future observed structural MRI relative to the missing observation. The performance of models was compared with two alternative imputation approaches: forward filling and image generation using variational autoencoders. Experimental results show that our method can generate 3D structural MRI with high similarity to ground-truth images at designated visits. Furthermore, images generated using ReMiND show relatively lower differences in volume estimation between the imputed and observed images compared to images generated by forward filling or autoencoders. Additionally, ReMiND provides more accurate estimated rates of atrophy over time in important anatomical brain regions than the two comparator methods. Our 3D diffusion model can impute missing structural MRI data at a single designated visit and outperforms alternative methods for imputing whole-brain images that are missing from longitudinal trajectories.

High-throughput screening of halide solid-state electrolytes for all-solid-state Li-ion batteries through structural descriptor

All-solid-state Li-ion batteries (ASSLIBs) have attracted great attention due to their intrinsic safety and high potential energy density. To realize ASSLIBs, the development of solid-state electrolytes (SSEs) with favorable electrochemical stability and high Li-ion conductivity is of utmost significance. Compared to trial-and-error searches, theoretical computation-based methods are recognized as a powerful tool for accelerating the exploration of SSEs. However, the development of appropriate descriptors is often the first hurdle toward implementing accurate and meaningful screening process. Here we quantified the structural properties pertaining to low Li-ion migration barriers and performed a high-throughput screening of 3119 Li-containing halides obtained from the Materials Project (MP) database to search for promising SSEs. After excluding previously reported SSEs, three candidate materials, Li4ZrF8, Li3ErBr6, and Li2ZnI4 with crystal structure exhibiting 3D diffusion pathway were obtained. Subsequent theoretical calculations of these materials were performed to evaluate their thermodynamic stability, chemical/electrochemical stability, and ionic conductivity. The three halide materials appeared to be promising SSE candidates due to their robust thermodynamical stability against cathodes, and high ionic conductivity. This research provides a new insight and a systematic quantitative understanding of the relationship between the structural properties and Li-ion migration barriers, which can motivate future computational studies on new fast-ion conductors and accelerate the discovery of high ionic conductivity SSEs for the use in ASSLIBs.

Probing the mechanism of nick searching by LIG1 at the single-molecule level.

DNA ligase 1 (LIG1) joins Okazaki fragments during the nuclear replication and completes DNA repair pathways by joining 3'-OH and 5'-PO4 ends of nick at the final step. Yet, the mechanism of how LIG1 searches for a nick at single-molecule level is unknown. Here, we combine single-molecule fluorescence microscopy approaches, C-Trap and total internal reflection fluorescence (TIRF), to investigate the dynamics of LIG1-nick DNA binding. Our C-Trap data reveal that DNA binding by LIG1 full-length is enriched near the nick sites and the protein exhibits diffusive behavior to form a long-lived ligase/nick complex after binding to a non-nick region. However, LIG1 C-terminal mutant, containing the catalytic core and DNA-binding domain, predominantly binds throughout DNA non-specifically to the regions lacking nick site for shorter time. These results are further supported by TIRF data for LIG1 binding to DNA with a single nick site and demonstrate that a fraction of LIG1 full-length binds significantly longer period compared to the C-terminal mutant. Overall comparison of DNA binding modes provides a mechanistic model where the N-terminal domain promotes 1D diffusion and the enrichment of LIG1 binding at nick sites with longer binding lifetime, thereby facilitating an efficient nick search process.

Anion Exchange and Lateral Heterostructure Formation in Ferromagnetic PEA2Cr(Cl,Br)4 Two-Dimensional Perovskites.

Postsynthetic vapor-phase anion exchange in the ferromagnetic two-dimensional (2D) hybrid metal-halide perovskite, PEA2CrCl4 (PEA+ = phenethylammonium), is reported. Anion exchange using vaporous trimethylsilyl bromide (TMS-Br) is shown to drive complete conversion of solution-processed PEA2CrCl4 polycrystalline thin films to PEA2CrBr4. Low-temperature magnetic circular dichroism spectroscopy indicates ferromagnetic ordering in these PEA2CrCl4 and PEA2CrBr4 films. Via partial anion exchange of exfoliated flakes of PEA2CrCl4 single crystals, we demonstrate that it is possible to generate abrupt lateral PEA2CrCl4/PEA2CrBr4 magneto-heterointerfaces. Kinetic studies reveal that lateral heterostructure formation is dictated by rapid edge-site halide exchange followed by slower intralayer bromide diffusion, and there is negligible interlayer (3D) bromide or TMS-Br diffusion. The importance of the bulky PEA+ interlayer cation in suppressing 3D diffusion is highlighted by parallel anion-exchange experiments on MA2CrCl4 (MA+ = methylammonium), which instead show 3D exchange. Comparison of anion-exchange reactions in PEA2CrCl4, PEA2MnCl4, and PEA2PbCl4 shows that 2D bromide diffusion is slowest in PEA2CrCl4, attributed to the antiferrodistortive ordering found in this composition. In addition to demonstrating both postsynthetic composition control and heterostructure formation in ferromagnetic Cr-based 2D perovskites for the first time, these results also advance our fundamental understanding of ion-exchange processes in this relatively unexplored family of 2D perovskites, broadening opportunities for investigation and control of novel spin effects in low-dimensional metal-halide perovskites.

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

AbstractEarth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low‐cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low‐cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio‐temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

Controlled single step synthesis, structural and electrode response of honeycomb layered Li3Co2SbO6

We report, for the first time, a single step synthesis process of Li3Co2SbO6 in air medium using the solid state reaction route. The structural analysis confirmed single phase layered crystal structure comprising 2D diffusion path along a-axis and b-axis. The Rietveld refinement of Li3Co2SbO6 yielded monoclinic crystal structure with C2/m space group having cell parameters, a = 5.216 A°, b = 8.989 A° and c = 5.171 A° with Li/Co mixed occupancy. The TEM analysis corroborated the layered structure which is consistent with x-ray analysis. Raman and FTIR analysis confirmed the presence of -CoO6 and -SbO6 octahedra in Li3Co2SbO6 with edge shared arrangement to form a layered stack comprising tunnel type pathway for Li+ ion transport. The estimated electrical conductivity of Li3Co2SbO6 is found to be ∼6.9 × 10−8 Scm−1 with a band gap ∼ 3.5 eV that suggests poor electronic transport for storage cells. This was observed in the electrochemical response of the Li || LiPF6(EC/EMC) || Li3Co2SbO6 cell. The 1st discharge capacity of Li3Co2SbO6 has been found to be a meagre 45 mAhg−1. Despite lower reversible capacity due to poor electrical transport, stable coulombic efficency observed up to 100 cycles suggest the feasibility of improvements in the electrical and charge transport properties.

One-dimensional photonic crystal enhancing spin-to-orbital angular momentum conversion for single-particle tracking

Single-particle tracking (SPT) is an immensely valuable technique for studying a variety of processes in the life sciences and physics. It can help researchers better understand the positions, paths, and interactions of single objects in systems that are highly dynamic or require imaging over an extended time. Here, we propose an all-dielectric one-dimensional photonic crystal (1D PC) that enhances spin-to-orbital angular momentum conversion for three-dimensional (3D) SPTs. This well-designed 1D PC can work as a substrate for optical microscopy. We introduce this effect into the interferometric scattering (iSCAT) technique, resulting in a double-helix point spread function (DH-PSF). DH-PSF provides more uniform Fisher information for 3D position estimation than the PSFs of conventional microscopy, such as encoding the axial position of a single particle in the angular orientation of DH-PSF lobes, thus providing a means for 3D SPT. This approach can address the challenge of iSCAT in 3D SPT because DH-PSF iSCAT will not experience multiple contrast inversions when a single particle travels along the axial direction. DH-PSF iSCAT microscopy was used to record the 3D trajectory of a single microbead attached to the flagellum, facilitating precise analysis of fluctuations in motor dynamics. Its ability to track single nanoparticles, such as 3D diffusion trajectories of 20 nm gold nanoparticles in glycerol solution, was also demonstrated. The DH-PSF iSCAT technique enabled by a 1D PC holds potential promise for future applications in physical, biological, and chemical science.

An interfacial dual-regulation strategy for ultra-stable 3D Zn metal anodes

The development of Zn metal-batteries, which are viewed as one of the most potential alternatives to lithium ion batteries, is severely hindered by sluggish ion diffusion kinetics and uncontrollable dendritic growth for anodes. Herein, we propose an interfacial dual-regulation strategy for the fabrication of 3D Zn anode through the direct in-situ treatment of benchmark Zn foil. Both rapid ion migration dynamics and homogeneous bottom-up Zn2+ deposition are achieved due to the unique open nanoarray structure with superhydrophilic and zincophilic interface to the electrolyte. Theoretical calculations and finite element simulations reveal this design can effectively redistribute Zn2+ and increase ion flux with a long-lasting 3D diffusion mode, enabling exceptional reversibility during Zn plating/stripping. The as-prepared anode therefore achieves an ultralong lifespan over 3000 h along with high rate capability even at 40 mA cm−2 (depth of discharge ≈ 68.4%). Furthermore, its practical feasibility is validated by a superior capacity retention of 92.5% after 1000 cycles for full cell and high capacity of 112.2 mAh g−1 for pouch cell. This study opens up new opportunities for the development of dendrite-free anodes for aqueous metal batteries.

Electric Field Regulator Constructed by Magnetron Sputtering for Dendrite‐Free and Stable Zinc Metal Anode

AbstractRechargeable aqueous zinc‐ion batteries (AZIBs) are considered to be one of the most promising devices in the next generation of energy storage systems. However, the uncontrolled growth of Zn dendrites during electroplating leads to rapid battery failure, which hinders the wide application of AZIBs. In this work, an Fe metal interface (FMI) with electric field regulation is designed on the Zn metal anode using a magnetron sputtering technology. The FMI layer with nanosheet array not only uniforms the surface electric field, but also adjusts the surface Zn2+ ion distribution to inhibit 2D diffusion. The strong orientation relationships of the FMI layer enhance the reversibility of Zn plating/stripping, improving the structural stability of the interface layer. Consequently, FMI@Zn symmetric cell exhibits ultra‐stable lifespan for over 6000 h (Cumulative plated capacity, CPC = 15 Ah cm−2) with a low voltage hysteresis of 46.4 mV and high Coulombic efficiency of 99.8% at 5 mA cm−2. Even at the large current density of 40 mA cm−2, the CPC reaches 19.7 Ah cm−2. The proposed electric field regulation strategy reveals a promising prospect for designing highly stable Zn anode, which also applies to other metal anodes in energy storage systems.

Aphasia outcome: the role of diffusion tensor tractography in patients with acute ischemic stroke

BackgroundsRecovery for poststroke aphasia has a decelerating trajectory, with the greatest improvement is within weeks and the slope of change decreasing over time. Therefore, it is essential to predict the prognosis of aphasia at an early stage as it could provide useful data in specific plans for management strategies. The aim of this work was to assess the arcuate fasciculus in stroke patients with aphasia and its impact on predicting the outcome. A prospective study was performed including 25 patients with acute ischemic stroke and aphasia and 10 healthy control subjects with no history of neurologic or psychiatric disease. All patients underwent language assessment using an Arabic version of the Comprehensive Aphasia Test (Arabic CAT), with the resultant mean T-score aphasia quotient (AQ). Early assessment of stroke and delayed assessment at three months. All patients had diffusion-weighted magnetic resonance imaging (DWI-MRI) of the brain to localize the lesion and 3D diffusion tensor imaging (DTI) of the arcuate fasciculus (AF) within 30 days of stroke.ResultsPatients in whom the AF could not be reconstructed had a poor score in early and late AQ and a poor prognosis compared to those in whom the AF could be reconstructed. Preservation of the left AF on DTI could mean the potential recovery of aphasia after stroke.ConclusionThe prognosis of aphasia in patients whose left AF could be reconstructed was better than those whose left AF could not be reconstructed, irrespective of the AF's integrity. That is why, we can assume that evaluation of the DTI of the left AF at early stages of stroke can help in predicting outcome of aphasia.

Noise suppression in pulsed IR thermographic NDT: Efficiency of data processing algorithms

Various types of noise, which accompany active TNDT procedures using optical heating, have been analyzed, both numerically and experimentally. An emphasis has been made on the suppression of surface clutter, which represents local areas of varying absorptivity/emissivity. The concept of signal-to-noise that is typically used in defect detection has been applied to fixed pattern noise in order to compare capabilities of data processing algorithms in reducing surface clutter. The experimental investigation has been fulfilled on a special sample containing both subsurface air-filled defects and areas with varying emissivity/absorptivity. The best suppression of the fixed pattern noise was provided by the complex wavelet transform and principle component analysis. Because of 3D heat diffusion, clutter spot boundaries are often underlined by particular data processing algorithms thus producing specific contours. The test situations where subsurface defects are located under localized clutter spots have been analyzed to demonstrate an overshadowing effect of such spots when detecting hidden defects.

Treatment of 3D diffusion problems with discontinuous coefficients and Dirac curvilinear sources

Three-dimensional diffusion problems with discontinuous coefficients and unidimensional Dirac sources arise in a number of fields. The statement we pursue is a singular-regular expansion where the singularity, capturing the stiff behavior of the potential, is expressed by a convolution formula using the Green kernel of the Laplace operator. The correction term, aimed at restoring the boundary conditions, fulfills a variational Poisson equation set in the Sobolev space H1, which can be approximated using finite element methods. The mathematical justification of the proposed expansion is the main focus, particularly when the variable diffusion coefficients are continuous, or have jumps. A computational study concludes the paper with some numerical examples. The potential is approximated by a combined method: (singularity, by integral formulas, correction, by linear finite elements). The convergence is discussed to highlight the practical benefits brought by different expansions, for continuous and discontinuous coefficients.

Sinc-Galerkin method and a higher-order method for a 1D and 2D time-fractional diffusion equations

In this article, a new numerical algorithm for solving a 1-dimensional (1D) and 2-dimensional (2D) time-fractional diffusion equation is proposed. The Sinc-Galerkin scheme is considered for spatial discretization, and a higher-order finite difference formula is considered for temporal discretization. The convergence behavior of the methods is analyzed, and the error bounds are provided. The main objective of this paper is to propose the error bounds for 2D problems by using the Sinc-Galerkin method. The proposed method in terms of convergence is studied by using the characteristics of the Sinc function in detail with optimal rates of exponential convergence for 2D problems. Some numerical experiments validate the theoretical results and present the efficiency of the proposed schemes.

A hybrid interpolating element-free Galerkin method for 3D steady-state convection diffusion problems

This study investigates a hybrid interpolating element-free Galerkin (HIEFG) method for solving 3D convection diffusion problems. The HIEFG approach divides a 3D solution domain into a sequence of interconnected 2D sub-domains, and in these 2D sub-domains, the interpolating element-free Galerkin (IEFG) method is applied to form the discretized equations. The improved interpolating moving least-squares (IMLS) method is used to obtain the shape function of the IEFG method for 2D problems. The finite difference method is employed to combine the discretized equations in 2D sub-domains in the splitting direction. Then, the HIEFG method's formulas are derived for steady-state convection diffusion problems in 3D solution domain. Three numerical examples are used to discuss the impacts of the number of nodes, the number of split layers, and the scaling parameters of the influence domain on the computational precision and CPU time of the HIEFG technique. Imposing boundary conditions directly and the dimension splitting technique in this method significantly improves the computational speed greatly.

Longitudinal Imaging of Injured Spinal Cord Myelin and White Matter with 3D Ultrashort Echo Time Magnetization Transfer (UTE-MT) and Diffusion MRI.

Quantitative MRI techniques could be helpful to noninvasively and longitudinally monitor dynamic changes in spinal cord white matter following injury, but imaging and postprocessing techniques in small animals remain lacking. Unilateral C5 hemisection lesions were created in a rat model, and ultrashort echo time magnetization transfer (UTE-MT) and diffusion-weighted sequences were used for imaging following injury. Magnetization transfer ratio (MTR) measurements and preferential diffusion along the longitudinal axis of the spinal cord were calculated as fractional anisotropy or an apparent diffusion coefficient ratio over transverse directions. The area of myelinated white matter was obtained by thresholding the spinal cord using mean MTR or diffusion ratio values from the contralesional side of the spinal cord. A decrease in white matter areas was observed on the ipsilesional side caudal to the lesions, which is consistent with known myelin and axonal changes following spinal cord injury. The myelinated white matter area obtained through the UTE-MT technique and the white matter area obtained through diffusion imaging techniques showed better performance to distinguish evolution after injury (AUCs > 0.94, p < 0.001) than the mean MTR (AUC = 0.74, p = 0.01) or ADC ratio (AUC = 0.68, p = 0.05) values themselves. Immunostaining for myelin basic protein (MBP) and neurofilament protein NF200 (NF200) showed atrophy and axonal degeneration, confirming the MRI results. These compositional and microstructural MRI techniques may be used to detect demyelination or remyelination in the spinal cord after spinal cord injury.

Creating High-quality 3D Content by Bridging the Gap Between Text-to-2D and Text-to-3D Generation

In recent times, automatic text-to-3D content creation has made significant progress, driven by the development of pretrained 2D diffusion models. Existing text-to-3D methods typically optimize the 3D representation to ensure that the rendered image aligns well with the given text, as evaluated by the pretrained 2D diffusion model. Nevertheless, a substantial domain gap exists between 2D images and 3D assets, primarily attributed to variations in camera-related attributes and the exclusive presence of foreground objects. Consequently, employing 2D diffusion models directly for optimizing 3D representations may lead to suboptimal outcomes. To address this issue, we present X-Dreamer, a novel approach for high-quality text-to-3D content creation that effectively bridges the gap between text-to-2D and text-to-3D synthesis. The key components of X-Dreamer are two innovative designs: Camera-Guided Low-Rank Adaptation (CG-LoRA) and Attention-Mask Alignment (AMA) Loss. CG-LoRA dynamically incorporates camera information into the pretrained diffusion models by employing camera-dependent generation for trainable parameters. This integration makes the 2D diffusion model camera-sensitive. AMA loss guides the attention map of the pretrained diffusion model using the binary mask of the 3D object, prioritizing the creation of the foreground object. This module ensures that the model focuses on generating accurate and detailed foreground objects. Extensive evaluations demonstrate the effectiveness of our proposed method compared to existing text-to-3D approaches. Our project webpage: https://anonymous-11111.github.io/ . Our code is available at https://github.com/xmu-xiaoma666/X-Dreamer .