Physical Properties Research Articles

Development and Evaluation of Celecoxib Emulgel by Using Natural Oil.

Emulgel combines the qualities of an emulsion with those of a gel. In order to create an emulgel w/o or o/w, emulsions have to be formulated, which are then combined with a gelling agent, resulting in a dual-control drug release. Celecoxib exhibits analgesic, antipyretic and anti-inflammatory activities and is used to treat osteoarthritis, severe pain, rheumatoid arthritis, and other medical conditions. Celecoxib Emulgel was developed and evaluated by using natural oil and carbopol- 940 as a gelling agent in different concentrations. The screening of various oils, co-surfactants and surfactants was performed to determine the solubility. The essential oils (eucalyptus oil and turpentine oil) were used as penetration modifiers. Studies on compatibility with polymers have been conducted, and the results indicate that there should be no physical or chemical interactions between the polymers and the drug substance. For the preparation of emulgel, various emulsions were prepared with Smix (cosurfactant and surfactant) ratios (1:1, 2:1 and 3:1). The selection of a gelling agent was done by incorporating the selected emulsion system ratio of 1:1 with the combinations of polymers carbapol 940, carbapol 934, and HPMC (0:1:0, 0:0.5:1, 0:0:3, 0.5:0:1, 1:0:0) gel base to make a homogenous emulgel. The emulgel was examined visually to see if it had any phase behaviour, feel, spreadability, and grittiness by applying its thin layer to a slide. Then, all six formulations of emulgel were prepared with the selected gelling agent. All emulgels were evaluated for pH, physical properties (consistency, homogeneity, colour, texture), drug content, spreadability, extrudability, swelling index, viscosity, stability and centrifugation. A Franz diffusion cell and an egg membrane were used to perform in-vitro drug release. Among all prepared formulations, EG1 had a better release, higher viscosity, higher drug content, and a higher swelling index than the others. The formulation EG1 showed higher drug release (91.25%) within 8 hours.

Research Progress of Chitosan-based Multifunctional Nanoparticles in Cancer Targeted Therapy.

Conventional tumor therapeutic modalities, such as radiotherapy, chemotherapy, and surgery, involve low tumor inhibition efficiency, non-targeted drug delivery, and side effects. The development of novel and practical nano-drug delivery systems (DDSs) for targeted tumor therapy has become particularly important. Among various bioactive nanoparticles, chitosan is considered a suitable candidate for drug delivery due to its nontoxicity, good biocompatibility, and biodegradability. The amino and hydroxyl groups of chitosan endow it with the diverse function of chemical modification, thereby improving its physical and biological properties to meet the requirements of advanced biomedical applications. Therefore, it is necessary to review the property and applications of chitosan- based materials in biomedicine. In this review, the characteristics of chitosan related to its applications are first introduced, and then the preparation and modification of chitosan-based nanoparticles, including the function tailoring of chitosan-modified nanoparticles, are demonstrated and discussed. Finally, the opportunities and challenges of chitosan- based nanomaterials in this emerging field are proposed from the perspective of the rational and systematic design for the biomedicine field.

Tactile Transfer Learning and Object Recognition With a Multifingered Hand Using Morphology Specific Convolutional Neural Networks.

Multifingered robot hands can be extremely effective in physically exploring and recognizing objects, especially if they are extensively covered with distributed tactile sensors. Convolutional neural networks (CNNs) have been proven successful in processing high dimensional data, such as camera images, and are, therefore, very well suited to analyze distributed tactile information as well. However, a major challenge is to organize tactile inputs coming from different locations on the hand in a coherent structure that could leverage the computational properties of the CNN. Therefore, we introduce a morphology-specific CNN (MS-CNN), in which hierarchical convolutional layers are formed following the physical configuration of the tactile sensors on the robot. We equipped a four-fingered Allegro robot hand with several uSkin tactile sensors; overall, the hand is covered with 240 sensitive elements, each one measuring three-axis contact force. The MS-CNN layers process the tactile data hierarchically: at the level of small local clusters first, then each finger, and then the entire hand. We show experimentally that, after training, the robot hand can successfully recognize objects by a single touch, with a recognition rate of over 95%. Interestingly, the learned MS-CNN representation transfers well to novel tasks: by adding a limited amount of data about new objects, the network can recognize nine types of physical properties.

An Exceptional Valorization of CuO Nanoparticles in Ionic Liquids as an Efficient Medium for the Electrophilic Substitution of Indole Towards the Formation of Bis(indolyl)methanes

Aim: Ionic liquids are promising green solvents with simple but unique structure-related physical properties such as negligible vapour pressure, exceptional thermal conductivity, remarkable thermal stability and their suitability and inertness towards a broad range of catalytic applications. CuO NPs have been addressed as a cost-effective and a reagent of a choice that necessitates only mild reaction conditions to offer a high yield of the desired products with exceptional selectivity in a short duration of time. Therefore, in the present work, attempts have been made to explore the catalytic potentials of CuO NPs in an ionic liquid medium to synthesize biologically important bis(indolyl)methanes. Background: Catalytic explorations of metal oxide nanoparticles in ionic liquids offers a cooperative effect that has a significant impact on the kinetics as well as on the outcome of the reaction. Therefore, such catalytic systems in the present times have seized the scientific community's interest from the perspectives of sustainable development in synthetic organic chemistry. The combination of metal oxide nanoparticles with highly tunable ionic liquids is not only used to synthesize simple organic molecules but also explored in the synthesis of complex organic molecules of high commercial and biological relevance. Objectives: The current work offers a rapid and robust protocol for synthesizing bis(indolyl)methanes via electrophilic substitution reaction between indole and various aldehydes in the presence of a CuO nanoparticles-ionic liquid system. The discussion focuses on the high tolerance of different functionalities by the catalytic system leading to the synthesis of bis(indolyl)methanes. Methods: CuO NPs have been synthesized via the co-precipitation method using ionic liquid. The applicability of metal oxide nanoparticles-IL matrix was further investigated in synthesizing bis(indolyl)methanes. Results: The FT-IR absorption below 600 cm-1 and the XRD pattern showing all the peaks in the diffraction diagram revealed the formation of CuO NPs. FESEM images show the flake-shaped morphology of CuO NPs and are found to be separated from the agglomerated clusters Conclusion: Ionic liquid-CuO NPs matrix reveals good to exceptional catalytic properties, and their advancements as a catalytic system at room temperature open new avenues for synthetic organic chemists.

The change of physical properties of calcium carbonate nanomaterials cured soil in road substrates

The utilization of appropriate materials to enhance road subgrade’s physical characteristics is crucial for current transportation construction and maintenance. This study proposes a curing method that employs calcium carbonate nanomaterials to address the problem of soil displacement and settlement in roadway subgrades. A method was developed during the study to explore the optimal curing material ratio. Additionally, this study developed a method for testing and analyzing the mechanical properties of soils cured with nanomaterials, including measures of tensile stress, triaxial shear stress, and Moore’s damage envelope. The study demonstrated that the unconfined compressive strength of the soil treated with calcium carbonate nanomaterials was 0.40 MPa after 7 days of curing with a 6% doping of the curing agent. Increasing the doping to 18% resulted in a breaking load of the soil reaching 0.100 kN. Furthermore, the triaxial shear stress–strain curve of the soil exhibited a slope of 264.47 during the linear phase when the curing agent was dosed at 6%. The slope of the linear phase of the stress–strain curve for triaxial shear at 6% curing agent doping was found to be 264.47. The cured soil molar pack line exhibited an internal friction angle of 22.66 degrees at the same curing agent dosage. The displacement analysis of the replacement roadbed with cured soil revealed a maximum observed displacement of only 377 mm after filling the embankment using the study method. The experimental results provide support for the hypothesis of the study, which suggests that the application of calcium carbonate nanoparticles can significantly enhance the physical characteristics of road subgrade.

Introducing the TNG-Cluster simulation: Overview and the physical properties of the gaseous intracluster medium

We introduce the new TNG-Cluster project, an addition to the IllustrisTNG suite of cosmological magnetohydrodynamical simulations of galaxy formation. Our objective is to significantly increase the statistical sampling of the most massive and rare objects in the Universe: galaxy clusters with log(M200c/M⊙) ≳ 14.3 − 15.4 at z = 0. To do so, we re-simulate 352 cluster regions drawn from a 1 Gpc volume that is 36 times larger than TNG300, keeping the IllustrisTNG physical model entirely fixed as well as the numerical resolution. This new sample of hundreds of massive galaxy clusters enables studies of the assembly of high-mass ellipticals and their supermassive black holes (SMBHs), brightest cluster galaxies (BCGs), satellite galaxy evolution and environmental processes, jellyfish galaxies, intracluster medium (ICM) properties, cooling and active galactic nuclei (AGN) feedback, mergers and relaxedness, magnetic field amplification, chemical enrichment, and the galaxy-halo connection at the high-mass end, with observables from the optical to radio synchrotron and the Sunyaev-Zeldovich (SZ) effect, to X-ray emission, as well as their cosmological applications. We present an overview of the simulation, the cluster sample, select comparisons to data, and a first look at the diversity and physical properties of our simulated clusters and their hot ICM.

Atomistic insights into argon clusters and nucleation dynamics

Accurate predictions of nucleation and atomic-level estimates of cluster properties in gas-phase chemical physics have proven challenging. These challenges arise from two primary sources: finite-size effects associated with nanoscopic particles and the emergence of non-standard thermodynamics, particularly at elevated temperatures. This study reexamines the formation of argon clusters using established methodologies such as atomistic simulations, configurational sampling, and statistical thermochemistry. To enhance the representation of condensed-phase argon, we employ an ab initio-based two-body potential, complemented by a three-body Axilrod–Teller potential. Additionally, we address the impact of anharmonicities on cluster stabilities using a recently developed extension to the standard statistical cluster model. The employed anharmonic model is rigorously benchmarked against molecular dynamics simulations. The subsequent analysis demonstrates a robust and consistent agreement between our model and experimental data. Our analysis covers nearly every experimental data point collected between 1971 and 2010, offering valuable insights into the predictive capabilities of the model. Moreover, in contrast to previous studies, our findings indicate that individual measurements are consistently in alignment with each other.

SN 2020pvb: A Type IIn-P supernova with a precursor outburst

We present photometric and spectroscopic datasets for SN 2020pvb, a Type IIn-P supernova (SN) that is similar to SNe 1994W, 2005cl, 2009kn, and 2011ht, with a precursor outburst detected (PS1 w band ∼–13.8 mag) around four months before the B-band maximum light. SN 2020pvb presents a relatively bright light curve that peaked at MB = −17.95 ± 0.30 mag and a plateau that lasted at least 40 days before going into solar conjunction. After this, the object was no longer visible at phases > 150 days above –12.5 mag in the B band, suggesting that the SN 2020pvb ejecta interact with a dense, spatially confined circumstellar envelope. SN 2020pvb shows strong Balmer lines and a forest of Fe II lines with narrow P Cygni profiles in its spectra. Using archival images from the Hubble Space Telescope, we constrained the progenitor of SN 2020pvb to have a luminosity of log(L/L⊙)≲5.4, ruling out any single star progenitor over 50 M⊙. SN 2020pvb is a Type IIn-P whose progenitor star had an outburst ∼0.5 yr before the final explosion; the material lost during this outburst probably plays a role in shaping the physical properties of the SN.

Biomimetic grafts from ultrafine fibers for collagenous tissues.

The ligament is the soft tissue that connects bone to bone and, in case of severe injury or rupture, it cannot heal itself mainly because of its poor vascularity and dynamic nature. Tissue engineering carries the potential to restore the injured tissue functions by utilization of scaffolds mimicking the structure of native ligament. Collagen fibrils in the anterior cruciate ligament (ACL) have a diameter ranging from 20 to 300nm, which defines the physical and mechanical properties of the tissue. Also, the ACL tissue exhibited a bimodal distribution of collagen fibrils. Currently, the ability to fabricate scaffolds replicating this structure is a significant challenge. This work aims at i) measuring the diameter of collagens of bovine ACL tissue, ii) investigating the fabrication of sub-100nm fibers, and iii) fabricating aligned scaffolds with bimodal diameter distribution (with two peaks) resembling the healthy ACL structure. It is hypothesized that such scaffolds can be produced by electrospinning polycaprolactone (PCL) solutions. To test the hypothesis, various PCL solutions were formulated in acetone and formic acid in combination with pyridine, and electrospun to generate sub-100nm fibers. Next, this formulation was adjusted to produce nanofibers with a diameter between 100nm and 200nm. Finally, these solutions were combined in the co-electrospinning process, i.e., two-spinneret electrospinning, to fabricate biomimetic scaffolds with a bimodal distribution. Electrospinning of 8% and 15% PCL solutions, respectively, resulted in the production of fibers with diameters below and above 100nm. The combined scaffold exhibited a bimodal distribution of aligned fibers with peaks around 80 and 180nm, thus mimicking the collagen fibrils of healthy ACL tissue. This research is expected to have a society-wide impact because it aims to enhance the health condition and life quality of a wide range of patients.

Cellulose Nanofiber/Polyethylene Glycol Composite Phase Change Thermal Storage Gel Based on Solid-gel Phase Change

In this paper, cellulose nanofiber (CNF)/ polyethylene glycol (PEG) composite aerogel phase change materials (CNPCMs) were prepared utilizing porous carrier support and freeze-drying. The solid-liquid phase change to solid-gel phase change was realized, which solved the problems of PEG flow, leakage, and shape instability. The physical properties and chemical compatibility of CNPCMs were studied, and the results showed that CNPCMs ensured the overall structure stability through internal hydrogen bonding, and they were only a physical bond with each other without chemical reaction. With the increase in PEG content, the thermal conductivity of CNPCMs increased from 0.22 W/m·K to 0.33 W/m·K. The thermal exposure experiment and thermogravimetric analysis (TGA) experiment have shown that CNPCMs have good shape stability at 75 ℃ and good thermal stability below 320 ℃. In summary, the experimental results indicated that the maximum content of PEG in CNPCMs was 78 % with an optimal content of 66.7 %. The sample corresponding to the optimal content was CNPCM2 with an enthalpy of 167.9 J/g for melting and 146.1 J/g for solidification. As a thermal storage material with good thermodynamic performance, CNPCM2 has enormous potential in the storage of solar collectors.

Experimental study on the influence of cyclic loading frequency on liquefaction characteristics of saturated sand

A series of undrained cyclic torsional shear tests was conducted to investigate the effect of cyclic loading frequency on the liquefaction characteristics of saturated sand using a hollow cylinder apparatus. The test results show that the dilative and contractive tendencies of various saturated sands are not only related to the physical properties of the sand, but are also affected by loading frequency. Under low-frequency loading, the saturated sand has a dilative behaviour, excess pore water pressure fluctuates after initial liquefaction and the soil maintains the ability to resist liquefaction to some extent after the initial liquefaction. The liquefaction mode in terms of the stress–strain relationship generally performs as the ‘cyclic mobility’. However, under high-frequency loading, the saturated sand has a contractive behaviour, and excess pore water pressure generally remains stable after the initial liquefaction. The liquefaction mode in terms of stress–strain relationship generally exhibits as ‘cyclic instability’. The deformation caused by low-frequency loading is significantly larger compared with that caused by high-frequency loading. At higher loading frequencies, the phase transformation stress ratio increases with the increase of loading frequency, and gradually approaches the failure stress ratio.

3D cell culture of nanofiber hydrogel promotes the growth and osteogenesis of bone marrow mesenchymal stem cells (BMSC)

Hydrogels, as a type of polymer network material with high water content, find wide application in various tissue repair procedures. In addition, a three-dimension (3D) cell culture platform similar to natural extracellular matrix can be constructed in vitro by modifying natural polymer chains. Therefore, this study based on natural polymer hydrogel, the introduction of inorganic nanoparticles POSS to prepare GelMA-POSS nanohydrogel. The physical and chemical properties of the hydrogel were evaluated through SEM, swelling test and degradation analysis. Subsequently, the GelMA-POSS nano-hydrogel was used as matrix material to culture rBMSCs in vitro. CCK-8 and flow cytometry were used to detect the proliferation ability and apoptosis rate of rBMSCs. The expression of osteogenic markers in rBMSCs was detected by qPCR, Western Blotting and ELISA assay, and the osteogenic differentiation of rBMSCs was detected by ALP staining and alizarin red staining. The results indicate that compared with pure gelatin (Gel) hydrogel, GelMA-POSS nanohydrogel has slower degradation rate and better water retention capacity. Furthermore, in vitro cell culture experiments showed that GelMA-POSS nano-hydrogel had good biocompatibility, and could promote the proliferation of rBMSCs and increase the expression level of osteogenic markers in cells, and induce osteogenic differentiation of rBMSCs. GelMA-POSS nano-hydrogel based on POSS significantly improves the physical and chemical properties of Gel hydrogel, and has good biocompatibility and the ability to induce osteogenic differentiation of rBMSCs, Thus, it holds great promise as a potential material for repairing bone defects.

Star-spot activity, orbital obliquity, transmission spectrum, physical properties, and transit time variations of the HATS-2 planetary system

Aims. Our aim in this paper is to refine the orbital and physical parameters of the HATS-2 planetary system and study transit timing variations and atmospheric composition thanks to transit observations that span more than 10 yr and that were collected using different instruments and pass-band filters. We also investigate the orbital alignment of the system by studying the anomalies in the transit light curves induced by starspots on the photosphere of the parent star. Methods. We analysed new transit events from both ground-based telescopes and NASA’s TESS mission. Anomalies were detected in most of the light curves and modelled as starspots occulted by the planet during transit events. We fitted the clean and symmetric light curves with the JKTEBOP code and those affected by anomalies with the PRISM+GEMC codes to simultaneously model the photometric parameters of the transits and the position, size, and contrast of each starspot. Results. We found consistency between the values we found for the physical and orbital parameters and those from the discovery paper and ATLAS9 stellar atmospherical models. We identified different sets of consecutive starspot-crossing events that temporally occurred in less than five days. Under the hypothesis that we are dealing with the same starspots, occulted twice by the planet during two consecutive transits, we estimated the rotational period of the parent star and, in turn the projected and the true orbital obliquity of the planet. We find that the system is well aligned. We identified the possible presence of transit timing variations in the system, which can be caused by tidal orbital decay, and we derived a low-resolution transmission spectrum.

Design of vibration sensors based on fibre Bragg grating type composites for earthquake detection and early warning application

Composite materials can be rapidly moulded using additive manufacturing processes due to their excellent mechanical and physical properties. Combining fibre Bragg gratings with composites results in high-performance fibre grating vibration sensors that address the limitations of electrical sensors and traditional materials. This study focused on developing a fibre optic acceleration sensor that utilizes a parabolic column made of silica gel. The sensor underwent fabrication, packaging, and calibration using a dedicated test system. Parametric calibrations and vibration detection tests were conducted to evaluate the performance of the system. The experimental results indicate that the sensor exhibits an intrinsic frequency of 70 Hz, a flat response range of 5 to 40 Hz, a linearity coefficient greater than 0.99, effective control of transverse interference, and exceptional low-frequency response, which improves the detection of vibration signals. Therefore, the sensor’s low intrinsic frequency and exceptional low-frequency response make it well-suited for detecting vibrations at low to medium frequencies.

Shadow Detection in Remote Sensing Images Based on Spectral Radiance Separability Enhancement.

Shadow detection is a basic task of remote sensing image analysis, but it is often seriously disturbed by vegetation, water bodies, and black objects. It is observed that vegetation and dark objects often show a dark look in visible bands but brighter in the near-infrared (NIR), and is also noticed that the reflection of inland water bodies in the green band is stronger than that in the blue band. Taking advantage of these physical properties and combining them with the bluish and dark appearance of shadows, we propose a simple but effective shadow detection method for multispectral remote sensing images. These physical properties are used to create transformation models that suppress features such as vegetation, water bodies, etc., but at the same time enhance shadows. Then, we transform the shadow representation into a color space to generate candidate shadows using dominant color components. To separate shadows from the others, we propose two indexes, the normalized Color Difference Composite Index (CDCI) and Color Purity Index (CPI), and fuse them to achieve shadows and their confidence. The experimental results indicate that the proposed method can effectively detect the shadows in multispectral images and outperforms the state-of-the-art approaches.

Evolution of coronal mass ejections with and without sheaths from the inner to the outer heliosphere: Statistical investigation for 1975 to 2022

Aims. This study covers a thorough statistical investigation of the evolution of interplanetary coronal mass ejections (ICMEs) with and without sheaths through a broad heliocentric distance and temporal range. The analysis treats the sheath and magnetic obstacle (MO) separately in order to gain more insight on their physical properties. In detail, we aim to unravel different characteristics of these structures occurring over the inner and outer heliosphere. Methods. The method is based on a large statistical sample of ICMEs probed over different distances in the heliosphere. For this, information about detection times for the sheath and MO from 13 individual ICME catalogs was collected and crosschecked. The time information was then combined into a main catalog that was used as the basis for the statistical investigation. The data analysis based on this catalog covers a large number of spacecraft missions, enabling in situ solar wind measurements from 1975 to 2022. This allowed us to study the differences between solar cycles. Results. All the structures under study (sheath, MO with and without sheath) show the biggest increase in size together with the largest decrease in density at a distance of ∼0.75 AU. At 1 AU, we found different sizes for MOs with and without a sheath, with the former being larger. Up to 1 AU, the upstream solar wind shows the strongest pileup close to the interface with the sheath. For larger distances, the pileup region seems to shift, and it recedes from that interface further into the upstream solar wind. This might refer to a change in the sheath formation mechanism (driven versus non-driven) with heliocentric distance, suggesting the relevance of the CME propagation and the expansion behavior in the outer heliosphere. A comparison to previous studies showed inconsistencies over the solar cycle, which makes more detailed studies necessary in order to fully understand the evolution of ICME structures.

Connection-Based Zagreb Indices of Polycyclic Aromatic Hydrocarbons Structures.

Topological indices (TIs) are mathematical formulas that are applied in mathematical chemistry to predict the physical and chemical properties of various chemical structures. In this study, three different types of polycyclic aromatic hydrocarbon structures (PAHs) (i.e., Hexa-peri-hexabenzocoronene, Dodeca-benzo-circumcoronene, and Hexa-cata- hexabenzocoronene) are studied with the help of the different connection number-based Zagreb indices. ϑ = (V(ϑ),E(ϑ)) is used as a graph, where V(ϑ) is a collection of vertices and E(ϑ) is a collection of edges. For a vertex y, ∈V(ϑ), the degree d_ϑ (y), is the number of those vertices that are at a distance of 1 from y and the connection number ρ_ϑ (y) is the number of such vertices that are at a distance of 2 from vertex y. Theoretical applications of topological indices were described in detail. Finally, we obtained the first and second Zagreb connections as well as the modified first, second, third, and fourth Zagreb connection indices, which were calculated for three different types (Hexa-peri-hexabenzocorone, Dodeca-benzo-circumcoronene, and Hexa-cata-hexabenzocoronene) of polycyclic aromatic hydrocarbon structures.

Degree Descriptors and Graph Entropy Quantities of Zeolite ACO.

Cheminformatics is a fascinating emerging subfield of chemical graph theory that studies quantitative structure-activity and property relationships of molecules and, in turn, uses these to predict the physical and chemical properties, which are extremely useful in drug discovery and optimization. Knowledge discovery can be put to use in pharmaceutical data matching to help in finding promising lead compounds. Topological descriptors are numerical quantities corresponding to the chemical structures that are used in the study of these phenomena. This paper is concerned with developing the generalized analytical expression of topological descriptors for zeolite ACO structures with underlying degree and degree-sum parameters. To demonstrate improved discrimination power between the topological descriptors, we have further modified Shannon's entropy approach and used it to calculate the entropy measures of zeolite ACO structures.

Roles of lncRNA-MALAT1 in the Progression and Prognosis of Gliomas.

Long noncoding RNAs (lncRNAs) represent a large subgroup of RNA transcripts that lack the function of coding proteins and may be essential universal genes involved in carcinogenesis and metastasis. LncRNA metastasis-associated lung adenocarcinoma transcript 1 (lncRNAMALAT1) is overexpressed in various human tumors, including gliomas. However, the biological function and molecular mechanism of action of lncRNA-MALAT1 in gliomas have not yet been systematically elucidated. Accumulating evidence suggests that the abnormal expression of lncRNA-MALAT1 in gliomas is associated with various physical properties of the glioma, such as tumor growth, metastasis, apoptosis, drug resistance, and prognosis. Furthermore, lncRNAs, as tumor progression and prognostic markers in gliomas, may affect tumorigenesis, proliferation of glioma stem cells, and drug resistance. In this review, we summarize the knowledge on the biological functions and prognostic value of lncRNA-MALAT1 in gliomas. This mini-review aims to deepen the understanding of lncRNA-MALAT1 as a novel potential therapeutic target for the individualized precision treatment of gliomas.

Machine learning applications in studies of the physical properties of active galactic nuclei based on photometric observations

Context. We investigate the physical nature of active galactic nuclei (AGNs) using machine learning (ML) tools. Aims. We show that the redshift, z, bolometric luminosity, LBol, central mass of the supermassive black hole (SMBH), MBH, Eddington ratio, λEdd, and AGN class (obscured or unobscured) can be reconstructed through multi-wavelength photometric observations only. Methods. We trained a random forest regressor (RFR) ML-model on 7616 spectroscopically observed AGNs from the SPIDERS-AGN survey, which had previously been cross-matched with soft X-ray observations (from ROSAT or XMM), WISE mid-infrared photometry, and optical photometry from SDSS ugriz filters. We built a catalog of 21 050 AGNs that were subsequently reconstructed with the trained RFR; for 9687 sources, we found archival redshift measurements. All AGNs were classified as either type 1 or type 2 using a random forest classifier (RFC) algorithm on a subset of known sources. All known photometric measurement uncertainties were incorporated via a simulation-based approach. Results. We present the reconstructed catalog of 21 050 AGNs with redshifts ranging from 0 < z < 2.5. We determined z estimations for 11 363 new sources, with both accuracy and outlier rates within 2%. The distinction between type 1 or type 2 AGNs could be identified with respective efficiencies of 94% and 89%. The estimated obscuration level, a proxy for AGN classification, of all sources is given in the dataset. The LBol, MBH, and λEdd values are given for 21 050 new sources with their estimated error. These results have been made publicly available. Conclusions. The release of this catalog will advance AGN studies by presenting key parameters of the accretion history of 6 dex in luminosity over a wide range of z. Similar applications of ML techniques using photometric data only will be essential in the future, with large datasets from eROSITA, JSWT, and the VRO poised to be released in the next decade.