3D Architecture Research Articles

Damage-Tolerant and Self-Repairing Web-Like Borate Type Binder Enable Stable Operation of Efficient Si-Based Anodes.

Novel binder designs are shown to be fruitful in improving the electrochemical performance of silicon (Si)-based anodes. However, issues with mechanical damage from dramatic volume change and poor lithium-ion (Li+) diffusion kinetics in Si-based materials still need to be addressed. Herein, an aqueous self-repairing borate-type binder (SBG) with a web-like architecture and high ionic conductivity is designed for Si and SiO electrodes. The 3D web-like architecture of the SBG binder enables uniform stress distribution, while its self-repairing ability promotes effective stress dissipation and mechanical damage repair, thereby enhancing the damage tolerance of the electrode. The tetracoordinate boron ions ( ) in the SBG binder boosts the Li transportation kinetics of Si-based electrodes. Based on dynamic covalent and ionic conductive boronic ester bonds, the diverse requirements of the binder, including uniform stress distribution, self-repairing ability, and high ionic conductivity, can be met by simple components. Consequently, the proposed straightforward multifunction design strategy for binders based on dynamic boron chemistry provides valuable insights into fabricating high-performance Si-based anodes.

A Gelatin-Based Biomimetic Scaffold Promoting Osteogenic Differentiation of Adipose-Derived Mesenchymal Stem Cells.

In bone tissue engineering segment, numerous approaches have been investigated to address critically sized bone defects via 3D scaffolds, as the amount of autologous bone grafts are limited, accompanied with complications on harvesting. Moreover, the use of bone-marrow-derived stem cells is also a limiting factor owing to the invasive procedures involved and the low yield of stem cells. Hence, research is ongoing on the search for an ideal bone graft system promoting bone growth and regeneration. This study aims to develop a unique platform for tissue development via stem cell differentiation towards an osteogenic phenotype providing optimum biological cues for cell adhesion, differentiation and proliferation using biomimetic gelatin-based scaffolds. The use of adipose-derived mesenchymal stem cells in this study also offers an ideal approach for the development of an autologous bone graft. A gelatin-vinyl acetate-based 3D scaffold system incorporating Bioglass was developed and the osteogenic differentiation of adipose-derived mesenchymal stem cells (ADMSCs) on the highly porous freeze-dried gelatin-vinyl acetate/ Bioglass scaffold (GB) systemwas analyzed. The physicochemical properties, cell proliferation and viability were investigated by seeding rat adipose tissue-derived mesenchymal stem cells (ADSCs) onto the scaffolds. The osteogenic differentiation potential of the ADMSC seeded GeVAc/bioglass system was assessed using calcium deposition assay and bone-related protein and genes and comparing with the 3D Gelatin vinyl acetate coppolymer (GeVAc) constructs. According to the findings, the 3D porous GeVAc/bioglass scaffold can be considered as a promising matrix for bone tissue regeneration and the 3D architecture supports the differentiation of the ADMSCs into osteoblast cells and enhances the production of mineralized bone matrix.

Multiscale Modeling of Physical Properties of Nanoporous Frameworks: Predicting Mechanical, Thermal, and Adsorption Behavior.

ConspectusNanoporous frameworks are a large and diverse family of supramolecular materials, whose chemical building units (organic, inorganic, or both) are assembled into a 3D architecture with well-defined connectivity and topology, featuring intrinsic porosity. These materials play a key role in various industrial processes and applications, such as energy production and conversion, fluid separation, gas storage, water harvesting, and many more. The performance and suitability of nanoporous materials for each specific application are directly related to both their physical and chemical properties, and their determination is crucial for process engineering and optimization of performances. In this Account, we focus on some recent developments in the multiscale modeling of physical properties of nanoporous frameworks, highlighting the latest advances in three specific areas: mechanical properties, thermal properties, and adsorption.In the study of the mechanical behavior of nanoporous materials, the past few years have seen a rapid acceleration of research. For example, computational resources have been pooled to create a public large-scale database of elastic constants as part of the Materials Project initiative to accelerate innovation in materials research: those can serve as a basis for data-based discovery of materials with targeted properties, as well as the training of machine learning predictor models.The large-scale prediction of thermal behavior, in comparison, is not yet routinely performed at such a large scale. Tentative databases have been assembled at the DFT level on specific families of materials, such as zeolites, but prediction at larger scale currently requires the use of transferable classical force fields, whose accuracy can be limited.Finally, adsorption is naturally one of the most studied physical properties of nanoporous frameworks, as fluid separation or storage is often the primary target for these materials. We highlight the recent achievements and open challenges for adsorption prediction at a large scale, focusing in particular on the accuracy of computational models and the reliability of comparisons with experimental data available. We detail some recent methodological improvements in the prediction of adsorption-related properties: in particular, we describe the recent research efforts to go beyond the study of thermodynamic quantities (uptake, adsorption enthalpy, and thermodynamic selectivity) and predict transport properties using data-based methods and high-throughput computational schemes. Finally, we stress the importance of data-based methods of addressing all sources of uncertainty.The Account concludes with some perspectives about the latest developments and open questions in data-based approaches and the integration of computational and experimental data together in the materials discovery loop.

ProLesA-Net: A multi-channel 3D architecture for prostate MRI lesion segmentation with multi-scale channel and spatial attentions

Prostate cancer diagnosis and treatment relies on precise MRI lesion segmentation, a challenge notably for small (<15mm) and intermediate (15-30mm) lesions. Our study introduces ProLesA-Net, a multi-channel 3D deep-learning architecture with multi-scale squeeze and excitation and attention gate mechanisms. Tested against six models across two datasets, ProLesA-Net significantly outperformed in key metrics: Dice score increased by 2.2%, and Hausdorff distance and average surface distance improved by 0.5mm, with recall and precision also undergoing enhancements. Specifically, for lesions under 15mm, our model showed a notable increase in five key metrics. In summary, ProLesA-Net consistently ranked at the top, demonstrating enhanced performance and stability. This advancement addresses crucial challenges in prostate lesion segmentation, enhancing clinical decision making and expediting treatment processes.

GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells.

The organization of mammalian genomes features a complex, multiscale three-dimensional (3D) architecture, whose functional significance remains elusive because of limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we introduce genome architecture and gene expression by sequencing (GAGE-seq), a scalable, robust single-cell co-assay measuring 3D genome structure and transcriptome simultaneously within the same cell. Applied to mouse brain cortex and human bone marrow CD34+ cells, GAGE-seq characterized the intricate relationships between 3D genome and gene expression, showing that multiscale 3D genome features inform cell-type-specific gene expression and link regulatory elements to target genes. Integration with spatial transcriptomic data revealed in situ 3D genome variations in mouse cortex. Observations in human hematopoiesis unveiled discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level. GAGE-seq provides a powerful, cost-effective approach for exploring genome structure and gene expression relationships at the single-cell level across diverse biological contexts.

Diamondoid Ni(II) Coordination Polymer as an Electrocatalyst for Hydrogen and Oxygen Evolution Reactions and Overall Water Splitting.

We have successfully synthesized a new Ni(II)-based coordination polymer (CP) [Ni2(cis-1,4-chdc)2(4,4'-bpy)3(H2O)2] (1); (cis-1,4- H2chdc=cis-1,4-cyclohexanedicarboxylic acid and 4,4'-bpy=4,4'-bipyridine) employing slow diffusion method in a single pot technique. The connectivity of Ni(II) ions and bridging cis-1,4-chdc ligand gives rise to a three-dimensional (3D) framework with 2-fold interpenetrated diamondoid topology. Interestingly, the synthesized CP acts as efficient catalyst for electrocatalytic water splitting. The water oxidation activity of compound 1 exhibits Tafel slope equivalent to 361.48 mV.dec-1 for hydrogen evolution reaction (HER) and 353.53 mV.dec-1 for oxygen evolution reaction (OER) in an alkaline medium while almost similar values of Tafel slope for HER and OER equivalent to 287.33 mV.dec-1 and 289.93 mV.dec-1 respectively in acidic medium. Thus, the compound 1 has excellent efficacy in catalyzing HER and OER in acidic as well as alkaline medium, which is ascribed to its distinctive 3D architecture.

The effect of head motion on brain age prediction using deep convolutional neural networks

Deep learning can be used effectively to predict participants' age from brain magnetic resonance imaging (MRI) data, and a growing body of evidence suggests that the difference between predicted and chronological age—referred to as brain-predicted age difference (brain-PAD)—is related to various neurological and neuropsychiatric disease states. A crucial aspect of the applicability of brain-PAD as a biomarker of individual brain health is whether and how brain-predicted age is affected by MR image artifacts commonly encountered in clinical settings. To investigate this issue, we trained and validated two different 3D convolutional neural network architectures (CNNs) from scratch and tested the models on a separate dataset consisting of motion-free and motion-corrupted T1-weighted MRI scans from the same participants, the quality of which were rated by neuroradiologists from a clinical diagnostic point of view. Our results revealed a systematic increase in brain-PAD with worsening image quality for both models. This effect was also observed for images that were deemed usable from a clinical perspective, with brains appearing older in medium than in good quality images. These findings were also supported by significant associations found between the brain-PAD and standard image quality metrics indicating larger brain-PAD for lower-quality images. Our results demonstrate a spurious effect of advanced brain aging as a result of head motion and underline the importance of controlling for image quality when using brain-predicted age based on structural neuroimaging data as a proxy measure for brain health.

Superconducting quantum memory with a suspended coaxial resonator

A promising way to store quantum information is by encoding it in the bosonic excitations of microwave resonators. This provides for long coherence times, low dephasing rates, as well as a hardware-efficient approach to quantum error correction. There are two main methods used to make superconducting microwave resonators: by traditionally machining them out of bulk material and by lithographically fabricating them on a chip in thin film. 3D resonators have few loss channels and larger mode volumes, and therefore smaller participations in the lossy parts, but it can be challenging to achieve high material quality. On-chip resonators can use low-loss thin films, but they confine the field more tightly, resulting in higher participations and additional loss channels from the dielectric substrate. In this work, we present a design in which a dielectric scaffold supports a thin-film conductor within a 3D package, thus combining the low surface participations of bulk-machined cavities with high quality and control over materials of thin-film circuits. By incorporating a separate chip containing a transmon qubit, we realize a quantum memory and measure single-photon lifetimes in excess of a millisecond. This hybrid 3D architecture has several advantages for scaling as it relaxes the importance of the package and permits modular construction with separately replaceable qubit and resonator devices.

Criteria for melanocytic lesions in LC-OCT.

Line-field confocal optical coherence tomography (LC-OCT) is an emerging diagnostic tool with imaging depth reaching ~400 μm and a novel three-dimensional (3D) cube providing cellular resolution. As far as we are aware, there are only a limited number of papers that have reported diagnostic criteria for melanocytic lesions using this technique, and none of them have been multicentric. Our aim was to establish the diagnostic criteria for melanocytic lesions using LC-OCT and identify the most significant architectural and cytologic features associated with malignancy. A retrospective evaluation of 80 consecutive melanocytic lesions from a prospective multicentric data set spanning three European centres was conducted. We excluded facial, acral and mucosal lesions from the study. Dermoscopic and LC-OCT images were evaluated by a consensus of four observers. Multivariate logistic regression with backward elimination was employed. The main melanoma diagnostic criteria include detecting >10 pagetoid cells in 3D acquisition, irregular 3D epidermal architecture, disrupted dermoepidermal junction (DEJ) and clefting. Significant risk factors were irregular 3D epidermal architecture, >10 pagetoid cells, dendritic cells at DEJ without underlying inflammation. Novel malignancy criteria in vertical view were DEJ disruption and clefting around atypical melanocyte nests. Exclusive melanoma features were epidermal nests, epidermal consumption, dense dermal nests with atypia. Protective features in the absence of any malignancy indicators were DEJ ring pattern, cobblestone, elongated rete ridges (vertical), well-defined DEJ and wave pattern (vertical). A series of diagnostic criteria for the identification of melanocytic lesions with LC-OCT have been established. Validation of these criteria in clinical practice through future studies is essential to further establish their utility.

Surfactant-assisted photo-crosslinked silk fibroin sponges: A versatile platform for the design of bone scaffolds

Critical size bone defects cannot heal without aid and current clinical approaches exhibit some limitations, underling the need for novel solutions. Silk fibroin, derived from silkworms, is widely utilized in tissue engineering and regenerative medicine due to its remarkable properties, making it a promising candidate for bone tissue regeneration in vitro and in vivo. However, the clinical translation of silk-based materials requires refinements in 3D architecture, stability, and biomechanical properties.In earlier research, improved mechanical resistance and stability of chemically crosslinked methacrylate silk fibroin (Sil-Ma) sponges over physically crosslinked counterparts were highlighted. Furthermore, the influence of photo-initiator and surfactant concentrations on silk properties was investigated. However, the characterization of sponges with Sil-Ma solution concentrations above 10 % (w/V) was hindered by production optimization challenges, with only cell viability assessed.This study focuses on the evaluation of methacrylate sponges' suitability as temporal bone tissue regeneration scaffolds. Sil-Ma sponge fabrication at a fixed concentration of 20 % (w/V) was optimized and the impact of photo-initiator (LAP) concentrations and surfactant (Tween 80) presence/absence was studied. Their effects on pore formation, silk secondary structure, mechanical properties, and osteogenic differentiation of hBM-MSCs were investigated. We demonstrated that, by tuning silk sponges' composition, the optimal combination boosted osteogenic gene expression, offering a strategy to tailor biomechanical properties for effective bone regeneration. Utilizing Design of Experiment (DoE), correlations between sponge composition, porosity, and mechanical properties are established, guiding tailored material outcomes. Additionally, correlation matrices elucidate the microstructure's influence on gene expressions, providing insights for personalized approaches in bone tissue regeneration.

Stencil-Based Selective Surface Functionalization of Silicon Nanowires in 3D Device Architectures for Next-Generation Biochemical Sensors

Stencil-Based Selective Surface Functionalization of Silicon Nanowires in 3D Device Architectures for Next-Generation Biochemical Sensors

Three-dimensional chromatin landscapes in somatotroph tumour.

The three-dimensional (3D) genome architecture plays a critical role inregulating gene expression. However, the specific alterations in thisarchitecture within somatotroph tumors and their implications for gene expression remain largely unexplored. We employed Hi-C and RNA-seq analyses to compare the 3D genomic structures of somatotroph tumors with normal pituitary tissue. This comprehensive approachenabled the characterization of A/B compartments, topologically associateddomains (TADs), and chromatin loops, integrating these with gene expression patterns. We observed a decrease in both the frequency of chromosomal interactions andthe size of TADs in tumor tissue compared to normal tissue. Conversely, the number of TADs and chromatin loops was found to be increased in tumors. Integrated analysis of Hi-C and RNA-seq data demonstrated that changes inhigher-order chromat in structure were associated with alterations in gene expression. Specifically, genes in A compartments showed higher density and increased expression relative to those in B compartments. Moreover, the weakand enhanced insulation boundaries were identified, and the associated genes were enriched in the Wnt/β-Catenin signaling pathway. We identified the gainedand lost loops in tumor and integrated these differences with transcriptional changes to examine the functional relevance of the identified loops. Notably, we observed an enhanced insulation boundary and a greater number of loops in the TCF7L2 gene region within tumors, which was accompanied by an upregulation of TCF7L2 expression. Subsequently, TCF7L2 expression was confirmed through qRT-PCR, and upregulated TCF7L2 prompted cell proliferation and growth hormone (GH) secretion in vitro. Our results provide comprehensive 3D chromatin architecture maps of somatotroph tumors and offer a valuable resource for furthering the understanding of the underlying biology and mechanisms of gene expression regulation.

Physically‐Based Lighting for 3D Generative Models of Cars

AbstractRecent work has demonstrated that Generative Adversarial Networks (GANs) can be trained to generate 3D content from 2D image collections, by synthesizing features for neural radiance field rendering. However, most such solutions generate radiance, with lighting entangled with materials. This results in unrealistic appearance, since lighting cannot be changed and view‐dependent effects such as reflections do not move correctly with the viewpoint. In addition, many methods have difficulty for full, 360° rotations, since they are often designed for mainly front‐facing scenes such as faces. We introduce a new 3D GAN framework that addresses these shortcomings, allowing multi‐view coherent 360° viewing and at the same time relighting for objects with shiny reflections, which we exemplify using a car dataset. The success of our solution stems from three main contributions. First, we estimate initial camera poses for a dataset of car images, and then learn to refine the distribution of camera parameters while training the GAN. Second, we propose an efficient Image‐Based Lighting model, that we use in a 3D GAN to generate disentangled reflectance, as opposed to the radiance synthesized in most previous work. The material is used for physically‐based rendering with a dataset of environment maps. Third, we improve the 3D GAN architecture compared to previous work and design a careful training strategy that allows effective disentanglement. Our model is the first that generate a variety of 3D cars that are multi‐view consistent and that can be relit interactively with any environment map.

A UAV-Based Single-Lens Stereoscopic Photography Method for Phenotyping the Architecture Traits of Orchard Trees

This article addresses the challenges of measuring the 3D architecture traits, such as height and volume, of fruit tree canopies, constituting information that is essential for assessing tree growth and informing orchard management. The traditional methods are time-consuming, prompting the need for efficient alternatives. Recent advancements in unmanned aerial vehicle (UAV) technology, particularly using Light Detection and Ranging (LiDAR) and RGB cameras, have emerged as promising solutions. LiDAR offers precise 3D data but is costly and computationally intensive. RGB and photogrammetry techniques like Structure from Motion and Multi-View Stereo (SfM-MVS) can be a cost-effective alternative to LiDAR, but the computational demands still exist. This paper introduces an innovative approach using UAV-based single-lens stereoscopic photography to overcome these limitations. This method utilizes color variations in canopies and a dual-image-input network to generate a detailed canopy height map (CHM). Additionally, a block structure similarity method is presented to enhance height estimation accuracy in single-lens UAV photography. As a result, the average rates of growth in canopy height (CH), canopy volume (CV), canopy width (CW), and canopy project area (CPA) were 3.296%, 9.067%, 2.772%, and 5.541%, respectively. The r2 values of CH, CV, CW, and CPA were 0.9039, 0.9081, 0.9228, and 0.9303, respectively. In addition, compared to the commonly used SFM-MVS approach, the proposed method reduces the time cost of canopy reconstruction by 95.2% and of the cost of images needed for canopy reconstruction by 88.2%. This approach allows growers and researchers to utilize UAV-based approaches in actual orchard environments without incurring high computation costs.

Formation of SiO2 thin films through plasma- enhanced chemical vapor deposition using SiH4/Ar/N2O

SiO2 films and their formation technologies are critical for the fabrication of Si-based integrated circuits (ICs). SiO2 films fabricated using plasma-enhanced chemical vapor deposition (PECVD) have become increasingly important because of the increasing trend of three-dimensional (3D) architectures in ICs. SiO2 films formed by PECVD have been widely studied for over 40 years; however, owing to the complex plasma reactions and the differences in system conditions, the relationship between the experimental parameters and film characteristics are disputed. In this study, focusing on the two important characteristics (surface morphology and deposition rate) of SiO2 films for 3 D ICs manufacturing, SiO2 film growth was systematically investigated via SiH4/Ar/N2O in PECVD; a theoretical reaction process model (including gas-phase reaction, chemical adsorption, and surface reaction) bridging the experimental parameters (chamber pressure, gas ratio, radio frequency power, and substrate temperature) and characteristics (surface morphology and deposition rate) of SiO2 films was established. This study contributes to the precise formation of sub-100 nanometer SiO2 films using PECVD for manufacturing 3 D ICs.

Exclusion of HDAC1/2 complexes by oncogenic nuclear condensates

Nuclear condensates have been shown to regulate cell fate control, but its role in oncogenic transformation remains largely unknown. Here we show acquisition of oncogenic potential by nuclear condensate remodeling. The proto-oncogene SS18 and its oncogenic fusion SS18-SSX1 can both form condensates, but with drastically different properties and impact on 3D genome architecture. The oncogenic condensates, not wild type ones, readily exclude HDAC1 and 2 complexes, thus, allowing aberrant accumulation of H3K27ac on chromatin loci, leading to oncogenic expression of key target genes. These results provide the first case for condensate remodeling as a transforming event to generate oncogene and such condensates can be targeted for therapy. One sentence summary: Expulsion of HDACs complexes leads to oncogenic transformation.

Performance Analysis of Nanowire ISFET Biosensor Towards Bovine Serum Albumin and Liposome

Proteins are necessary to all living organisms for both structural and functional reasons. However, due to their breakdown, some proteins, including Bovine Serum Albumin (BSA) and Liposome, could cause detrimental effects on cells and tissues. Due to its high detection sensitivity, the potential for mass production, and affordable manufacture, the ion-sensitive field-effect transistor (ISFET) biosensor has become increasingly prominent in clinical research for the detection of biomolecules. BSA and Liposome are the target proteins, while collagen is the bioreceptor. ISFET biosensor with a structure of cylindrical nanowire was simulated and examined. The settling time and sensitivity of the biosensor were modeled using Nanohub BioSensorLab software. The cylindrical nanowire ISFET biosensor can be enhanced by reducing the buffer ion concentration, increasing the radius, and increasing the oxide thickness. Compared to liposomes, BSA provides a lower settling time. This is because the diffusion coefficient of liposomes is 3.6 times lower than BSA. Furthermore, settling time is reduced when the analyte concentration is increased. The results are compared with planar ISFET, considered one-dimensional (1D) architecture. The planar ISFET exhibited a quicker settling time than the cylindrical nanowire biosensor. Furthermore, as the amounts of protein and analyte increased, the settling time reduced. The cylindrical nanowire biosensor needs to be in radius of 100nm and 10nm of oxide thickness with 0.1M buffer concentration for it to achieved the highest sensitivity. These results could facilitate researchers to produce the desirable ISFET sensor for different types of proteins.

Three-dimensional polymer phenylethnylcopper/nitrogen doped graphene aerogel electrode coupled with Fe3O4 NPs nanozyme: Toward sensitive and robust photoelectrochemical detection of glyphosate in agricultural matrix

BackgroundPresently, glyphosate (Gly) is the most extensively used herbicide globally, Nevertheless, its excessive usage has increased its accumulation in off-target locations, and aroused concerns for food and environmental safety. Commonly used detection methods, such as high-performance liquid chromatography and gas chromatography, have limitations due to expensive instruments, complex pre-processing steps, and inadequate sensitivity. Therefore, a facile, sensitive, and reliable Gly detection method should be developed. ResultsA photoelectrochemical (PEC) sensor consisting of a three-dimensional polymer phenylethnylcopper/nitrogen-doped graphene aerogel (PPhECu/3DNGA) electrode coupled with Fe3O4 NPs nanozyme was constructed for sensitive detection of Gly. The microscopic 3D network of electrodes offered fast transfer routes for photo-generated electrons and a large surface area for nanozyme loading, allowing high signal output and analytical sensitivity. Furthermore, the use of peroxidase-mimicking Fe3O4 NPs instead of natural enzyme improved the stability of the sensor against ambient temperature changes. Based on the inhibitory effect of Gly on the catalytic activity Fe3O4 NPs, the protocol achieved Gly detection in the range of 5 × 10−10 to 1 × 10−4 mol L−1. Additionally, feasibility of the detection was confirmed in real agricultural matrix including tea, maize seedlings, maize seeds and soil. SignificanceThis work achieved facile, sensitive and reliable analysis towards Gly, and it was expected to inspire the design and utilization of 3D architectures in monitoring agricultural chemicals in food and environmental matrix.

Additive Manufacturing of Zn‐Doped ZrO2Architectures

Tailoring the properties of microfabricated ceramics through doping can unlock new avenues for the additive manufacturing (AM) of advanced 3D architectures. The first step to achieving optical functionality is to control material morphology, crystallinity, and defects associated with the composition of the produced AM architecture and dopants. For this purpose, AM of zinc‐doped zirconia (ZrO2:Zn) 3D microarchitectures is proposed using two‐photon lithography and tailor‐made resin. It is found that Zn doping modulates ZrO2:Zn architecture crystallinity and optical properties. The modification of optical properties through Zn doping is confirmed by micro‐photoluminescence, where higher energy photon emission is observed due to the promotion of oxygen vacancies and surface defects. It is also shown that Zn 2.5% and 5 wt% stabilizes the monoclinic ZrO2at a lower temperature than in the case of undoped ZrO2. Furthermore, there is evidence that Zn tends to form ZnO wurtzite, which is later sublimated. The findings provide a promising route to understand the role of defects ZrO2:Zn optically upon annealing.

Multi-responsive luminescent complex for Fe3+, Cr2O72− and CrO42− species in aqueous solution based on aromatic polycarboxylic acid and imidazole-containing ligand: synthesis, crystal structure and selective detection

One Cadmium(II)-based complex, [Cd(LBIX)(HEA)]n (1), was synthesized using 4,4′-bis((1H-imidazol-1-yl)methyl)-1,1′-biphenyl (LBIX) and 1,2-phenylenediacetic acid (H2HEA) as ligands. The analysis of the single crystal structure reveals that 1 possesses a ladder-like chain structure, which extends into a 3D architecture through π···π interactions. 1 was identified through powder X-ray diffraction analysis (PXRD), elemental analysis (EA), infrared spectroscopy (IR) and thermogravimetric analysis (TGA). It can be seen from the luminescence experiment that 1 has high Ksv value (Cr2O72−: 1.51 × 104 M−1, CrO42−: 1.16 × 104 M−1 and Fe3+: 1.26 × 104 M−1) and lower detection limit (Cr2O72−: 1.14 μM, CrO42−: 1.88 μM and Fe3+: 1.14 μM), it is utilized as a multi-response sensor to recognition Fe3+, CrO42− and Cr2O72− in an aqueous solution. Mechanisms in which fluorescence quenching occurs have been examined using techniques such as PXRD, UV–vis absorption spectra, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Due to its excellent selectivity, high sensitivity and strong stability, it is suitable for detecting Fe3+, CrO42− and Cr2O72− ions as a fluorescent probe.