Linnworks, provider of inventory, order and warehouse management solutions for ecommerce retailers, has announced its new integration with Loop, a post-purchase platform designed to optimise returns, exchanges and reverse logistics.

Veracity Trust Network (Veracity) has been awarded the Cybersecurity Co-Innovation and Development Fund (CCDF) CyberCall grant of S$1 million by the Cyber Security Agency Singapore (CSA).

Radio Frequency Identification (RFID) provides new and profitable opportunities for increasing organisational, financial and operational performance. For instance, the retail and logistics industries can benefit from the superior RFID technology. DENSO explains why.

Black Box, a global information technology solutions provider, has introduced the first solution in its Return to Work suite designed to help organisations and businesses in different industries provide a safer environment for their staff, visitors and customers.

By Adrian Stokes, freelance writer.

Ever wondered how some retail stores seamlessly update their product prices in real-time, avoiding the hassle of manually switching out paper tags on shelves? Discover how electronic shelf labels work and how they can boost your sales and customer satisfaction.

The Co-op Media Network (CMN) is to install 300 new front-of-store digital media screens to turbo-charge its retail media offering, taking the total number of screens to over 9,000 across its store estate.

University of Florida cybersecurity professor Kevin Butler developed the framework, which spells out guidance for countries to prevent fraud and abuse on mobile cash apps.

[Domestic] :
A new online labor union welcomes all members, regardless of occupation or industry, including job seekers who are not currently employed. The civic group Workplace Gapjil 119 announced the union’s launch Monday, saying it is based on an internet community and anyone can participate. The group said ...

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[Domestic] :
Rescue workers on Saturday found the body of one of the 12 missing crew members of a fishing boat that sank off Jeju Island on Friday. According to the Jeju branch of the Korea Coast Guard, a body was retrieved in waters 24 kilometers northwest of Hallim Port at 11:18 p.m. Saturday and transported to Jeju ...

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[Politics] :
The presidential office says it is working to arrange a meeting between President Yoon Suk Yeol and U.S. President-elect Donald Trump. A senior official told reporters on Tuesday that the top office is in close communication with Trump’s team. This comes as the Yoon administration is preparing for the ...

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[Domestic] :
The country is taking steps to make sure the College Scholastic Ability Test(CSAT) proceeds smoothly on Thursday, with local governments and companies adjusting their schedules to reduce traffic congestion. Banks will open later than usual, operating from 10 a.m. to 5 p.m. The government has also ...

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Whether you are an employee or a small business owner, it can be helpful to calculate the number of working days in a year. Most people are familiar with the total number of days in a year: 365. But how many of those days are working days?

If you're buying a new car, you know air conditioning is almost certainly a standard feature. But it wasn't long ago when AC was an expensive option. Find out how this now nearly universal feature works.

Headers can be used to improve the performance of your car's engine. Learn about headers and find out how exhaust headers can improve engine performance.

How does a hybrid car improve your gas mileage? And more importantly, does it pollute less just because it gets better gas mileage? Learn how hybrids work, plus get tips on how to drive a hybrid car for maximum efficiency.

Horsepower rates the engine performance of cars and even lawn mowers. Learn what horsepower means, how it is measured and how it works in high-performance cars.

On this week's episode of I Feel You, DJ Hyerim and NVee dive into their fitness routines, sharing the secrets behind staying in shape and the complicated relationships with personal trainers....

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[Economy] :
Unionized Seoul subway workers will vote on Friday to decide whether they should launch a general strike as labor and management of Seoul's city-run subway operator are facing difficulty in negotiating wages and new hires. According to Seoul Metro, which operates subway Lines One through Eight and ...

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Who we work with  British Geological Survey

Working at BGS  British Geological Survey

Laboratory life: my work experience week at BGS  British Geological Survey

The hydro­thermal synthesis and structural characterization of four novel 3D pillared-layer metal–organic frameworks are studied, revealing how the malleability of copper coordination geometries drives diverse supramolecular isomerism. The findings provide new insights into designing advanced hybrid materials with tailored properties, emphasizing the significant role of reaction conditions and metal ion flexibility in determining network topologies.

Cryogenic electron microscopy (cryoEM) is a rapidly growing structural biology modality that has been successful in revealing molecular details of biological systems. However, unlike established biophysical and analytical techniques with calibration standards, cryoEM has lacked comprehensive biological test samples. Here, a cryoEM calibration sample consisting of a mixture of compatible macromolecules is introduced that can not only be used for resolution optimization, but also provides multiple reference points for evaluating instrument performance, data quality and image-processing workflows in a single experiment. This combined test specimen provides researchers with a reference point for validating their cryoEM pipeline, benchmarking their methodologies and testing new algorithms.

This review summarizes the methodological aspects of laboratory X-ray powder micro-diffraction and demonstrates the assets of the method in the research of painted artworks for evaluation of their provenance or diagnosing their degradation.

Painted artworks represent a significant group of cultural heritage artifacts, which are primarily admired because of their aesthetic quality. Nevertheless, the value of each particular painting depends also on what is known about it. Material investigation of paintings is one of the most reliable sources of information. Materials in painted artworks (i.e. panel, easel and miniature paintings, wall paintings, polychromed sculptures etc.) represent an extensive set of inorganic and organic phases, which are often present in complicated mixtures and exhibit characteristics reflecting their geological genesis (mineral pigments), manufacturing technology (artificial pigments), diverse biological nature (binders or dyes) or secondary changes (degradation or intentional later interventions). The analyses of paintings are often made challenging by the heterogeneous nature and minute size of micro-samples or, in some cases, even by the impossibility of sampling due to the preciousness, fragility or small dimensions of the artwork. This review demonstrates the successful implementation of laboratory X-ray powder micro-diffraction for material investigation of paintings, illustrating its efficiency for mineralogical analysis of (i) earth-based materials indicating the provenance of paintings, (ii) copper-based pigments pointing to their origin, and (iii) products of both salt corrosion and saponification enabling one to reveal the deterioration and probable original appearance of artworks.

As a representative of the fourth-generation light sources, the High Energy Photon Source (HEPS) in Beijing, China, utilizes a multi-bend achromat lattice to obtain an approximately 100 times emittance reduction compared with third-generation light sources. New technologies bring new challenges to operate the storage ring. In order to meet the beam commissioning requirements of HEPS, a new framework for the development of high-level applications (HLAs) has been created. The key part of the new framework is a dual-layer physical module to facilitate the seamless fusion of physical simulation models with the real machine, allowing for fast switching between different simulation models to accommodate the various simulation scenarios. As a framework designed for development of physical applications, all variables are based on physical quantities. This allows physicists to analytically assess measurement parameters and optimize machine parameters in a more intuitive manner. To enhance both extensibility and adaptability, a modular design strategy is utilized, partitioning the entire framework into discrete modules in alignment with the requirements of HLA development. This strategy not only facilitates the independent development of each module but also minimizes inter-module coupling, thereby simplifying the maintenance and expansion of the entire framework. To simplify the development complexity, the design of the new framework is implemented using Python and is called Python-based Accelerator Physics Application Set (Pyapas). Taking advantage of Python's flexibility and robust library support, we are able to develop and iterate quickly, while also allowing for seamless integration with other scientific computing applications. HLAs for both the HEPS linac and booster have been successfully developed. During the beam commissioning process at the linac, Pyapas's ease of use and reliability have significantly reduced the time required for the beam commissioning operators. As a development framework for HLA designed for the new-generation light sources, Pyapas has the versatility to be employed with HEPS, as well as with other comparable light sources, due to its adaptability.

In recent years, China's advanced light sources have entered a period of rapid construction and development. As modern X-ray detectors and data acquisition technologies advance, these facilities are expected to generate massive volumes of data annually, presenting significant challenges in data management and utilization. These challenges encompass data storage, metadata handling, data transfer and user data access. In response, the Data Organization Management Access Software (DOMAS) has been designed as a framework to address these issues. DOMAS encapsulates four fundamental modules of data management software, including metadata catalogue, metadata acquisition, data transfer and data service. For light source facilities, building a data management system only requires parameter configuration and minimal code development within DOMAS. This paper firstly discusses the development of advanced light sources in China and the associated demands and challenges in data management, prompting a reconsideration of data management software framework design. It then outlines the architecture of the framework, detailing its components and functions. Lastly, it highlights the application progress and effectiveness of DOMAS when deployed for the High Energy Photon Source (HEPS) and Beijing Synchrotron Radiation Facility (BSRF).

Metal-organic frameworks (MOFs) exhibit structural flexibility induced by temperature and guest adsorption, as demonstrated in the structural breathing transition in certain MOFs between narrow-pore and large-pore phases. Soft modes were suggested to entropically drive such pore breathing through enhanced vibrational dynamics at high temperatures. In this work, oxygen K-edge resonant X-ray emission spectroscopy of the MIL-53(Al) MOF was performed to selectively probe the electronic perturbation accompanying pore breathing dynamics at the ligand carboxyl­ate site for metal–ligand interaction. It was observed that the temperature-induced vibrational dynamics involves switching occupancy between antisymmetric and symmetric configurations of the carboxyl­ate oxygen lone pair orbitals, through which electron density around carboxyl­ate oxygen sites is redistributed and metal–ligand interactions are tuned. In turn, water adsorption involves an additional perturbation of π orbitals not observed in the structural change solely induced by temperature.

StreamSAXS is a Python-based small- and wide-angle X-ray scattering (SAXS/WAXS) data analysis workflow platform with graphical user interface (GUI). It aims to provide an interactive and user-friendly tool for analysis of both batch data files and real-time data streams. Users can easily create customizable workflows through the GUI to meet their specific needs. One characteristic of StreamSAXS is its plug-in framework, which enables developers to extend the built-in workflow tasks. Another feature is the support for both already acquired and real-time data sources, allowing StreamSAXS to function as an offline analysis platform or be integrated into large-scale acquisition systems for end-to-end data management. This paper presents the core design of StreamSAXS and provides user cases demonstrating its utilization for SAXS/WAXS data analysis in offline and online scenarios.

The inherent ambiguity in reconstructed images from coherent diffraction imaging (CDI) poses an intrinsic challenge, as images derived from the same dataset under varying initial conditions often display inconsistencies. This study introduces a method that employs the Noise2Noise approach combined with neural networks to effectively mitigate these ambiguities. We applied this methodology to hundreds of ambiguous reconstructed images retrieved from a single diffraction pattern using a conventional retrieval algorithm. Our results demonstrate that ambiguous features in these reconstructions are effectively treated as inter-reconstruction noise and are significantly reduced. The post-Noise2Noise treated images closely approximate the average and singular value decomposition analysis of various reconstructions, providing consistent and reliable reconstructions.

We report on the latest advancements in Microcrystal Electron Diffraction (3D ED/MicroED), as discussed during a symposium at the National Center for CryoEM Access and Training housed at the New York Structural Biology Center. This snapshot describes cutting-edge developments in various facets of the field and identifies potential avenues for continued progress. Key sections discuss instrumentation access, research applications for small mol­ecules and biomacromolecules, data collection hardware and software, data reduction software, and finally reporting and validation. 3D ED/MicroED is still early in its wide adoption by the structural science community with ample opportunities for expansion, growth, and innovation.

The well-known copper car­box­yl­ate dimer, with four car­box­yl­ate ligands ex­ten­ding outwards towards the corners of a square, has been employed to generate a series of crystalline com­pounds. In particular, this work centres on the use of the 4-hy­droxy­benzoate anion (Hhba−) and its deprotonated phe­nol­ate form 4-oxidobenzoate (hba2−) to obtain complexes with the general formula [Cu2(Hhba)4–x(hba)xL2–y]x−, where L is an axial coligand (including solvent mol­ecules), x = 0, 1 or 2, and y = 0 or 1. In some cases, short hy­dro­gen bonds result in complexes which may be represented as [Cu2(Hhba)2(H0.5hba)2L2]−. The main focus of the investigation is on the formation of a variety of extended networks through hy­dro­gen bonding and, in some crystals, coordinate bonds when bridging coligands (L) are employed. Crystals of [Cu2(Hhba)4(di­ox­ane)2]·4(di­ox­ane) consist of the expected Cu dimer with the Hhba− anions forming hy­dro­gen bonds to 1,4-di­ox­ane mol­ecules which block network formation. In the case of crystals of com­position [Et4N][Cu2(Hhba)2(H0.5hba)2(CH3OH)(H2O)]·2(di­ox­ane), Li[Cu2(Hhba)2(H0.5hba)2(H2O)2]·3(di­ox­ane)·4H2O and [Cu2(Hhba)2(H0.5hba)2(H0.5DABCO)2]·3CH3OH (DABCO is 1,4-di­aza­bicyclo­[2.2.2]octa­ne), square-grid hy­dro­gen-bonded networks are generated in which the complex serves as one type of 4-con­necting node, whilst a second 4-con­necting node is a hy­dro­gen-bonding motif assembled from four phenol/phenolate groups. Another two-dimensional (2D) network based upon a related square-grid structure is formed in the case of [Et4N]2[Cu2(Hhba)2(hba)2(di­ox­ane)2][Cu2(Hhba)4(di­ox­ane)(H2O)]·CH3OH. In [Cu2(Hhba)4(H2O)2]·2(Et4NNO3), a square-grid structure is again apparent, but, in this case, a pair of nitrate anions, along with four phenolic groups and a pair of water mol­ecules, combine to form a second type of 4-con­necting node. When 1,8-bis­(di­methyl­amino)­naphthalene (bdn, `proton sponge') is used as a base, another square-grid network is generated, i.e. [Hbdn]2[Cu2(Hhba)2(hba)2(H2O)2]·3(di­ox­ane)·H2O, but with only the copper dimer complex serving as a 4-con­necting node. Complex three-dimensional networks are formed in [Cu2(Hhba)4(O-bipy)]·H2O and [Cu2(Hhba)4(O-bipy)2]·2(di­ox­ane), where the potentially bridging 4,4'-bi­pyridine N,N'-dioxide (O-bipy) ligand is employed. Rare cases of mixed car­box­yl­ate copper dimer complexes were obtained in the cases of [Cu2(Hhba)3(OAc)(di­ox­ane)]·3.5(di­ox­ane) and [Cu2(Hhba)2(OAc)2(DABCO)2]·10(di­ox­ane), with each structure possessing a 2D network structure. The final com­pound re­por­ted is a simple hy­dro­gen-bonded chain of com­position (H0.5DABCO)(H1.5hba), formed from the reaction of H2hba and DABCO.

The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and training residual neural networks on these data. Here, two per-pattern capabilities of Resonet are demonstrated: (i) interpretation of crystal resolution and (ii) identification of overlapping lattices. Resonet was tested across a compilation of diffraction images from synchrotron experiments and X-ray free-electron laser experiments. Crucially, these models readily execute on graphics processing units and can thus significantly outperform conventional algorithms. While Resonet is currently utilized to provide real-time feedback for macromolecular crystallography users at the Stanford Synchrotron Radiation Lightsource, its simple Python-based interface makes it easy to embed in other processing frameworks. This work highlights the utility of physics-based simulation for training deep neural networks and lays the groundwork for the development of additional models to enhance diffraction collection and analysis.

Data acquisition and processing for cryo-electron tomography can be a significant bottleneck for users. To simplify and streamline the cryo-ET workflow, Tomo Live, an on-the-fly solution that automates the alignment and reconstruction of tilt-series data, enabling real-time data-quality assessment, has been developed. Through the integration of Tomo Live into the data-acquisition workflow for cryo-ET, motion correction is performed directly after each of the acquired tilt angles. Immediately after the tilt-series acquisition has completed, an unattended tilt-series alignment and reconstruction into a 3D volume is performed. The results are displayed in real time in a dedicated remote web platform that runs on the microscope hardware. Through this web platform, users can review the acquired data (aligned stack and 3D volume) and several quality metrics that are obtained during the alignment and reconstruction process. These quality metrics can be used for fast feedback for subsequent acquisitions to save time. Parameters such as Alignment Accuracy, Deleted Tilts and Tilt Axis Correction Angle are visualized as graphs and can be used as filters to export only the best tomograms (raw data, reconstruction and intermediate data) for further processing. Here, the Tomo Live algorithms and workflow are described and representative results on several biological samples are presented. The Tomo Live workflow is accessible to both expert and non-expert users, making it a valuable tool for the continued advancement of structural biology, cell biology and histology.

Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (kinetics-informed NN for time-resolved X-ray crystallography). To validate KINNTREX, multiple realistic scenarios were simulated with increasing levels of complexity. For the simulations, time-resolved X-ray data were generated that mimic data collected from the photocycle of the photoactive yellow protein. KINNTREX only requires the number of intermediates and approximate relaxation times (both obtained from a singular valued decomposition) and does not require an assumption of a candidate mechanism. It successfully predicts a consistent chemical kinetic mechanism, together with difference electron-density maps of the intermediates that appear during the reaction. These features make KINNTREX attractive for tackling a wide range of biomolecular questions. In addition, the versatility of KINNTREX can inspire more NN-based applications to time-resolved data from biological macromolecules obtained by other methods.

Appreciating that the role of the solute–solvent and other outer-sphere interactions is essential for understanding chemistry and chemical dynamics in solution, experimental approaches are needed to address the structural consequences of these interactions, complementing condensed-matter simulations and coarse-grained theories. High-energy X-ray scattering (HEXS) combined with pair distribution function analysis presents the opportunity to probe these structures directly and to develop quantitative, atomistic models of molecular systems in situ in the solution phase. However, at concentrations relevant to solution-phase chemistry, the total scattering signal is dominated by the bulk solvent, prompting researchers to adopt a differential approach to eliminate this unwanted background. Though similar approaches are well established in quantitative structural studies of macromolecules in solution by small- and wide-angle X-ray scattering (SAXS/WAXS), analogous studies in the HEXS regime—where sub-ångström spatial resolution is achieved—remain underdeveloped, in part due to the lack of a rigorous theoretical description of the experiment. To address this, herein we develop a framework for differential solution scattering experiments conducted at high energies, which includes concepts of the solvent-excluded volume introduced to describe SAXS/WAXS data, as well as concepts from the time-resolved X-ray scattering community. Our theory is supported by numerical simulations and experiment and paves the way for establishing quantitative methods to determine the atomic structures of small molecules in solution with resolution approaching that of crystallography.

Spectroscopic data, particularly diffraction data, are essential for materials characterization due to their comprehensive crystallographic information. The current crystallographic phase identification, however, is very time consuming. To address this challenge, we have developed a real-time crystallographic phase identifier based on a convolutional self-attention neural network (CPICANN). Trained on 692 190 simulated powder X-ray diffraction (XRD) patterns from 23 073 distinct inorganic crystallographic information files, CPICANN demonstrates superior phase-identification power. Single-phase identification on simulated XRD patterns yields 98.5 and 87.5% accuracies with and without elemental information, respectively, outperforming JADE software (68.2 and 38.7%, respectively). Bi-phase identification on simulated XRD patterns achieves 84.2 and 51.5% accuracies, respectively. In experimental settings, CPICANN achieves an 80% identification accuracy, surpassing JADE software (61%). Integration of CPICANN into XRD refinement software will significantly advance the cutting-edge technology in XRD materials characterization.

Crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents heavily influences the macroscopic behavior of the material. To study local crystallographic texture with both high spatial and angular resolution, we developed Texture Tomography (TexTOM). This approach allows the user to model the diffraction data of polycrystalline materials using the full reciprocal space of the crystal ensemble and describe the texture in each voxel via an orientation distribution function, hence it provides 3D reconstructions of the local texture by measuring the probabilities of all crystal orientations. The TexTOM approach addresses limitations associated with existing models: it correlates the intensities from several Bragg reflections, thus reducing ambiguities resulting from symmetry. Further, it yields quantitative probability distributions of local real space crystal orientations without further assumptions about the sample structure. Finally, its efficient mathematical formulation enables reconstructions faster than the time scale of the experiment. This manuscript presents the mathematical model, the inversion strategy and its current experimental implementation. We show characterizations of simulated data as well as experimental data obtained from a synthetic, inorganic model sample: the silica–witherite biomorph. TexTOM provides a versatile framework to reconstruct 3D quantitative texture information for polycrystalline samples; it opens the door for unprecedented insights into the nanostructural makeup of natural and technical materials.

Mineral identification and quantification are key to the understanding and, hence, the capacity to predict material properties. The method of choice for mineral quantification is powder X-ray diffraction (XRD), generally using a Rietveld refinement approach. However, a successful Rietveld refinement requires preliminary identification of the phases that make up the sample. This is generally carried out manually, and this task becomes extremely long or virtually impossible in the case of very large datasets such as those from synchrotron X-ray diffraction computed tomography. To circumvent this issue, this article proposes a novel neural network (NN) method for automating phase identification and quantification. An XRD pattern calculation code was used to generate large datasets of synthetic data that are used to train the NN. This approach offers significant advantages, including the ability to construct databases with a substantial number of XRD patterns and the introduction of extensive variability into these patterns. To enhance the performance of the NN, a specifically designed loss function for proportion inference was employed during the training process, offering improved efficiency and stability compared with traditional functions. The NN, trained exclusively with synthetic data, proved its ability to identify and quantify mineral phases on synthetic and real XRD patterns. Trained NN errors were equal to 0.5% for phase quantification on the synthetic test set, and 6% on the experimental data, in a system containing four phases of contrasting crystal structures (calcite, gibbsite, dolomite and hematite). The proposed method is freely available on GitHub and allows for major advances since it can be applied to any dataset, regardless of the mineral phases present.

In the title mol­ecule, C7H7N3O, the pyrimidine ring is essentially planar, with the propynyl group rotated out of this plane by 15.31 (4)°. In the crystal, a tri-periodic network is formed by N—H⋯O, N—H⋯N and C—H⋯O hydrogen-bonding and slipped π–π stacking inter­actions, leading to narrow channels extending parallel to the c axis. Hirshfeld surface analysis of the crystal structure reveals that the most important contributions for the crystal packing are from H⋯H (36.2%), H⋯C/C⋯H (20.9%), H⋯O/O⋯H (17.8%) and H⋯N/N⋯H (12.2%) inter­actions, showing that hydrogen-bonding and van der Waals inter­actions are the dominant inter­actions in the crystal packing. Evaluation of the electrostatic, dispersion and total energy frameworks indicates that the stabilization is dominated by the electrostatic energy contributions. The mol­ecular structure optimized by density functional theory (DFT) calculations at the B3LYP/6–311 G(d,p) level is compared with the experimentally determined structure in the solid state. The HOMO–LUMO behaviour was also elucidated to determine the energy gap.

In the title compound, C20H18O4, the dihedral angle between the 2H-chromen-2-one ring system and the phenyl ring is 89.12 (5)°. In the crystal, the mol­ecules are connected through C—H⋯O hydrogen bonds to generate [010] double chains that are reinforced by weak aromatic π–π stacking inter­actions. The unit-cell packing can be described as a tilted herringbone motif. The H⋯H, H⋯O/O⋯H, H⋯C/C⋯H and C⋯C contacts contribute 46.7, 24.2, 16.7 and 7.6%, respectively, to its Hirshfeld surface.

The title compound, C16H11N2OF, is a member of the azo dye family. The dihedral angle subtended by the benzene ring and the naphthalene ring system measures 18.75 (7)°, indicating that the compound is not perfectly planar. An intra­molecular N—H⋯O hydrogen bond occurs between the imino and carbonyl groups. In the crystal, the mol­ecules are linked into inversion dimers by C—H⋯O inter­actions. Aromatic π–π stacking between the naphthalene ring systems lead to the formation of chains along [001]. A Hirshfeld surface analysis was undertaken to investigate and qu­antify the inter­molecular inter­actions. In addition, energy frameworks were used to examine the cooperative effect of these inter­molecular inter­actions across the crystal, showing dispersion energy to be the most influential factor in the crystal organization of the compound.

In the title benzyl­ideneaniline Schiff base, C18H22N2O, the aromatic rings are inclined to each other by 46.01 (6)°, while the Car—N= C—Car torsion angle is 176.9 (1)°. In the crystal, the only identifiable directional inter­action is a weak C—H⋯π hydrogen bond, which generates inversion dimers that stack along the a-axis direction.

The title compound, C16H17N3O3, is racemic as it crystallizes in a centrosymmetric space group (Poverline{1}), although the trans disposition of substituents about the central C—C bond is established. The five- and six-membered rings are oriented at a dihedral angle of 75.88 (8)°. In the crystal, N—H⋯N hydrogen bonds form chains of mol­ecules extending along the c-axis direction that are connected by inversion-related pairs of O—H⋯N into ribbons. The ribbons are linked by C—H⋯π(ring) inter­actions, forming layers parallel to the ab plane. A Hirshfeld surface analysis indicates that the most important contributions for the crystal packing are from H⋯H (45.9%), H⋯N/N⋯H (23.3%), H⋯C/C⋯H (16.2%) and H⋯O/O⋯H (12.3%) inter­actions. Hydrogen bonding and van der Waals inter­actions are the dominant inter­actions in the crystal packing. The volume of the crystal voids and the percentage of free space were calculated to be 100.94 Å3 and 13.20%, showing that there is no large cavity in the crystal packing. Evaluation of the electrostatic, dispersion and total energy frameworks indicates that the stabilization is dominated by the electrostatic energy contributions in the title compound. Moreover, the DFT-optimized structure at the B3LYP/6–311 G(d,p) level is compared with the experimentally determined mol­ecular structure in the solid state. The HOMO–LUMO behaviour was elucidated to determine the energy gap.