Vous rêvez d'un processeur Ryzen 7 9800X3D, malheureusement les stocks semblent inexistants et la situation ne semble pas vouloir s'arranger dans un futur proche, rien ne garantit que vous puissiez l'avoir au pied de votre sapin… En effet, aujourd'hui, on apprend que le marchand allemand Mindfactory annonce un réapprovisionnement dudit processeur à la fin du mois de décembre ! La question est alors de savoir si le dernier-né d'AMD est victime de son succès ou s'il s'agit d'un nouveau produit lancé avec des stocks inexistants. En France, la situation n'est pas meilleure, le processeur n'est pas en stock chez les marchands les plus connus et le réapprovisionnement est généralement fixé à plus de 15 jours. […]

Presenting SproutWorks 3D Digg Explorer www.sproutworks.com/digg3d.php I have just put SproutWorks 3D Digg Explorer online. It is my latest attempt to display textual information in an interesting way. I use JavaScript with jQuery to script the interactive elements of it. It fetches a JSON string from my server, and creates a three dimensional scene using the data from it.

We've seen 3D printers used for everything from tiny houses to US marine barracks and now we can add teardrop trailer to the list too, courtesy of Lemki Robotix and iScale3D.

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Category: Outdoors, Lifestyle

Tags: Trailer, teardrop trailers, 3D Printing, Camping

short horror story in the form of a series of 1999-era screenshots about a Windows screensaver simulating life on an island #

Buildings that are normally inaccessible can now be explored virtually using smartphones.

This work describes a methodology that supports the design and implementation of software modules, which represent the individual and collaborative three-dimensional interaction process phases. The presented methodology integrates three modeling approaches: Petri Nets, a collaborative manipulation model based on the combination of single user interaction techniques taxonomy, and object-oriented programming concepts. The combination of these elements allows for the description of interaction tasks, the sequence of interaction processes being controlled by Petri Nets with the codes generated automatically. By the integration of these approaches, the present work addresses not only the entire development cycle of both individual and collaborative three-dimensional interaction, but also the reuse of developed interaction blocks in new virtual environment projects.

Aim/Purpose: This review’s main objective was to examine the existing literature on the use of 3D printers in primary education, covering students aged six to twelve across general, special, and inclusive educational environments. Background: A review of the literature indicated a significant oversight – prior reviews insufficiently distinguish the application of 3D printing in primary education from its utilization at higher educational tiers or focused on particular subject areas and learning domains. Considering the distinct nature and critical role of primary education in developing young students’ cognitive abilities and skills, it is essential to concentrate on this specific educational stage. Methodology: The scoping review was selected as the preferred research method. The methodological robustness was augmented through the utilization of the backward snowballing technique. Consequently, a total of 50 papers were identified and subjected to thorough analysis. Contribution: This review has methodically compiled and analyzed the literature on 3D printing use among elementary students, offering a substantial addition to academic conversations. It consolidated and organized research on 3D printers’ educational uses, applying robust and credible criteria. Findings: Many studies featured small sample sizes and limited research on inclusive and special education. The analysis revealed 82 distinct research goals and 13 educational fields, with STEM being the predominant focus. Scholars showed considerable interest in how 3D printers influence skills like creativity and problem-solving, as well as emotions such as engagement and motivation. The majority of studies indicated positive outcomes, enhancing academic achievement, engagement, collaboration, creativity, interest, and motivation. Nonetheless, challenges were noted, highlighting the necessity for teacher training, the expense of equipment, technical difficulties, and the complexities of blending new methods with traditional curricula. Recommendations for Practitioners: To capitalize on the benefits that 3D printers bring, curriculum planners are urged to weave them into their programs, ensuring alignment with educational standards and skill development. The critical role educators play in the effective implementation of this technology necessitates targeted professional development programs to equip them with the expertise for successful integration. Moreover, 3D printing presents a unique opportunity to advance inclusive education for students with disabilities, offering tailored learning experiences and aiding in creating assistive technologies. In recognizing the disparities in access to 3D printing, educational leaders must address the financial and logistical barriers highlighted in the literature. Strategic initiatives are essential to democratize 3D printing access, ensuring all students benefit from this educational tool. Recommendation for Researchers: Comparative studies are critical to elucidate the specific advantages and limitations of 3D printing technology due to the scarcity of research contrasting it with other tools. The variability in reporting durations of interventions and research environments underscores the necessity for uniform methodologies and benchmarks. Because research has predominantly focused on STEM/STEAM education, expanding into different educational areas could provide a comprehensive understanding of 3D printing’s capabilities. The existence of neutral and negative findings signals an opportunity for further investigation. Exploring the factors that impede the successful integration of 3D printing will inform the creation of superior pedagogical approaches and technological refinements. Future Research: As the review confirmed the significant promise of 3D printing technology in enriching education, especially in the context of primary education, the imperative for continued research to refine its application in primary education settings is highlighted.

Action recognition plays a vital role in analysing human body behaviour and has significant implications for research and education. However, traditional recognition methods often suffer from issues such as inaccurate time and spatial feature vectors. Therefore, this study addresses the problem of inaccurate recognition of aerobic gymnastics action image data and proposes a visualised three-dimensional convolutional neural network algorithm-based action recognition model. This model incorporates unsupervised visualisation methods into the traditional network and enhances data recognition capabilities through the introduction of a random noise perturbation enhancement algorithm. The research results indicate that the data augmented with noise perturbation achieves the lowest mean square error, reducing the error value from 0.3352 to 0.3095. The use of unsupervised visualisation analysis enables clearer recognition of human actions, and the algorithm model is capable of accurately recognising aerobic movements. Compared to traditional algorithms, the new algorithm exhibits higher recognition accuracy and superior performance.

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Marietta, GA — Ultrafine particles and volatile organic compounds are emitted during 3D printing, according to a recent study from the Chemical Insights Research Institute.

In this blast from the past, Dave Engebretson revisits a column from December 2014 on 3D Audio

3D printing is an additive manufacturing technology that has experienced widespread growth across numerous industries in recent years. It’s used in a wide variety of settings, including laboratories, factories, hospitals and schools.

Atlanta — Emissions from 3D printers may contain fine and ultrafine particles that can damage airway cells and negatively affect respiratory health, result of a recent study show.

Washington — Employers whose workers use 3D printers in non-industrial settings can take steps to limit employee exposure to emissions from heated filaments, polymers and powders, NIOSH says.

With their unique forms, these 3D-printed lamps made from recycled plastic by Emil Robbrecht bring a playful element to your home.

According to a report from Adroit Market Research, 3D printing powder market is projected to grow at a CAGR of 26.6% between 2021 and 2031.

Three-dimensional electron diffraction (3D-ED) is a powerful technique for crystallographic characterization of nanometre-sized crystals that are too small for X-ray diffraction. For accurate crystal structure refinement, however, it is important that the Bragg diffracted intensities are treated dynamically. Bloch wave simulations are often used in 3D-ED, but can be computationally expensive for large unit cell crystals due to the large number of diffracted beams. Proposed here is an alternative method, the `scattering cluster algorithm' (SCA), that replaces the eigen-decomposition operation in Bloch waves with a simpler matrix multiplication. The underlying principle of SCA is that the intensity of a given Bragg reflection is largely determined by intensity transfer (i.e. `scattering') from a cluster of neighbouring diffracted beams. However, the penalty for using matrix multiplication is that the sample must be divided into a series of thin slices and the diffracted beams calculated iteratively, similar to the multislice approach. Therefore, SCA is more suitable for thin specimens. The accuracy and speed of SCA are demonstrated on tri-iso­propyl silane (TIPS) pentacene and rubrene, two exemplar organic materials with large unit cells.

The strong interaction of high-energy electrons with a crystal results in both dynamical elastic scattering and inelastic events, particularly phonon and plasmon excitation, which have relatively large cross sections. For accurate crystal structure refinement it is therefore important to uncover the impact of inelastic scattering on the Bragg beam intensities. Here a combined Bloch wave–Monte Carlo method is used to simulate phonon and plasmon scattering in crystals. The simulated thermal and plasmon diffuse scattering are consistent with experimental results. The simulations also confirm the empirical observation of a weaker unscattered beam intensity with increasing energy loss in the low-loss regime, while the Bragg-diffracted beam intensities do not change significantly. The beam intensities include the diffuse scattered background and have been normalized to adjust for the inelastic scattering cross section. It is speculated that the random azimuthal scattering angle during inelastic events transfers part of the unscattered beam intensity to the inner Bragg reflections. Inelastic scattering should not significantly influence crystal structure refinement, provided there are no artefacts from any background subtraction, since the relative intensity of the diffracted beams (which includes the diffuse scattering) remains approximately constant in the low energy loss regime.

Following the work of Day & Hawthorne [Acta Cryst. (2022), A78, 212–233] and Day et al. [Acta Cryst. (2024), A80, 258–281], the program GraphT–T has been developed to embed graphical representations of observed and hypothetical chains of (SiO4)4− tetrahedra into 2D and 3D Euclidean space. During embedding, the distance between linked vertices (T–T distances) and the distance between unlinked vertices (T⋯T separations) in the resultant unit-distance graph are restrained to the average observed distance between linked Si tetrahedra (3.06±0.15 Å) and the minimum separation between unlinked vertices is restrained to be equal to or greater than the minimum distance between unlinked Si tetrahedra (3.713 Å) in silicate minerals. The notional interactions between vertices are described by a 3D spring-force algorithm in which the attractive forces between linked vertices behave according to Hooke's law and the repulsive forces between unlinked vertices behave according to Coulomb's law. Embedding parameters (i.e. spring coefficient, k, and Coulomb's constant, K) are iteratively refined during embedding to determine if it is possible to embed a given graph to produce a unit-distance graph with T–T distances and T⋯T separations that are compatible with the observed T–T distances and T⋯T separations in crystal structures. The resultant unit-distance graphs are denoted as compatible and may form crystal structures if and only if all distances between linked vertices (T–T distances) agree with the average observed distance between linked Si tetrahedra (3.06±0.15 Å) and the minimum separation between unlinked vertices is equal to or greater than the minimum distance between unlinked Si tetrahedra (3.713 Å) in silicate minerals. If the unit-distance graph does not satisfy these conditions, it is considered incompatible and the corresponding chain of tetrahedra is unlikely to form crystal structures. Using GraphT–T, Day et al. [Acta Cryst. (2024), A80, 258–281] have shown that several topological properties of chain graphs influence the flexibility (and rigidity) of the corresponding chains of Si tetrahedra and may explain why particular compatible chain arrangements (and the minerals in which they occur) are more common than others and/or why incompatible chain arrangements do not occur in crystals despite being topologically possible.

Owing to the difficulties associated with working with carbohydrates, validating glycan 3D structures prior to deposition into the Protein Data Bank has become a staple of the structure-solution pipeline. The Privateer software provides integrative methods for the validation, analysis, refinement and graphical representation of 3D atomic structures of glycans, both as ligands and as protein modifiers. While Privateer is free software, it requires users to install any of the structural biology software suites that support it or to build it from source code. Here, the Privateer web app is presented, which is always up to date and available to be used online (https://privateer.york.ac.uk) without installation. This self-updating tool, which runs locally on the user's machine, will allow structural biologists to simply and quickly analyse carbohydrate ligands and protein glycosylation from a web browser whilst retaining all confidential information on their devices.

Glucose-6-phosphate dehydrogenase (G6PD) is the first enzyme in the pentose phosphate pathway. It has been extensively studied by biochemical and structural techniques. 13 X-ray crystal structures and five electron cryo-microscopy structures in the PDB are focused on in this topical review. Two F420-dependent glucose-6-phosphate dehydrogenase (FGD) structures are also reported. The significant differences between human and parasite G6PDs can be exploited to find selective drugs against infections such as malaria and leishmaniasis. Furthermore, G6PD is a prognostic marker in several cancer types and is also considered to be a tumour target. On the other hand, FGD is considered to be a target against Mycobacterium tuberculosis and possesses a high biotechnological potential in biocatalysis and bioremediation.

Animations, videos and 3D models have been designed to visualize the effects of symmetry operators on selected cases of crystal structures, pointing out the relationship with the diagrams published in International Tables for Crystallography, Vol. A.

A new processing technique for synchrotron scanning 3D X-ray diffraction data is introduced, utilizing symmetric Bragg reflections hkl and hkl, known as Friedel pairs. This technique is designed to tackle the difficulties associated with large, highly deformed, polyphase materials, especially geological samples.

This article describes the implementation of GRIP as a module of GRASP, enabling the fully three-dimensional visualization and analysis of data collected on small-angle neutron scattering instruments.

A series of animations, videos and 3D models that were developed, filmed or built to teach the symmetry properties of crystals are described. At first, these resources were designed for graduate students taking a basic crystallography course, coming from different careers, at the National Autonomous University of Mexico. However, the COVID-19 pandemic had the effect of accelerating the generation of didactic material. Besides our experience with postgraduate students, we have noted that 3D models attract the attention of children, and therefore we believe that these models are particularly useful for teaching children about the assembled arrangements of crystal structures.

The present study introduces a processing strategy for synchrotron scanning 3D X-ray diffraction (s3DXRD) data, aimed at addressing the challenges posed by large, highly deformed, polyphase materials such as crystalline rocks. Leveraging symmetric Bragg reflections known as Friedel pairs, our method enables diffraction events to be precisely located within the sample volume. This method allows for fitting the phase, crystal structure and unit-cell parameters at the intra-grain scale on a voxel grid. The processing workflow incorporates several new modules, designed to (i) efficiently match Friedel pairs in large s3DXRD datasets containing up to 108 diffraction peaks; (ii) assign phases to each pixel or voxel, resolving potential ambiguities arising from overlap in scattering angles between different crystallographic phases; and (iii) fit the crystal orientation and unit cell locally on a point-by-point basis. We demonstrate the effectiveness of our technique on fractured granite samples, highlighting the ability of the method to characterize complex geological materials and show their internal structure and mineral composition. Additionally, we include the characterization of a metal gasket made of a commercial aluminium alloy, which surrounded the granite sample during experiments. The results show the effectiveness of the technique in recovering information about the internal texture and residual strain of materials that have undergone high levels of plastic deformation.

This work presents a detailed analysis of the performance of X-ray magnetic circular dichroism photoemission electron microscopy (XMCD-PEEM) as a tool for vector reconstruction of magnetization. For this, 360° domain wall ring structures which form in a synthetic antiferromagnet are chosen as the model to conduct the quantitative analysis. An assessment is made of how the quality of the results is affected depending on the number of projections that are involved in the reconstruction process, as well as their angular distribution. For this a self-consistent error metric is developed which allows an estimation of the optimum azimuthal rotation angular range and number of projections. This work thus proposes XMCD-PEEM as a powerful tool for vector imaging of complex 3D magnetic structures.

Nanoscale structural and electronic heterogeneities are prevalent in condensed matter physics. Investigating these heterogeneities in 3D has become an important task for understanding material properties. To provide a tool to unravel the connection between nanoscale heterogeneity and macroscopic emergent properties in magnetic materials, scanning transmission X-ray microscopy (STXM) is combined with X-ray magnetic circular dichroism. A vector tomography algorithm has been developed to reconstruct the full 3D magnetic vector field without any prior noise assumptions or knowledge about the sample. Two tomographic scans around the vertical axis are acquired on single-crystalline Nd2Fe14B pillars tilted at two different angles, with 2D STXM projections recorded using a focused 120 nm X-ray beam with left and right circular polarization. Image alignment and iterative registration have been implemented based on the 2D STXM projections for the two tilts. Dichroic projections obtained from difference images are used for the tomographic reconstruction to obtain the 3D magnetization distribution at the nanoscale.

Understanding the correlation between chemical and microstructural properties is critical for unraveling the fundamental relationship between materials chemistry and physical structures that can benefit materials science and engineering. Here, we demonstrate novel in situ correlative imaging of the X-ray Compton scattering computed tomography (XCS-CT) technique for studying this fundamental relationship. XCS-CT can image light elements that do not usually exhibit strong signals using other X-ray characterization techniques. This paper describes the XCS-CT setup and data analysis method for calculating the valence electron momentum density and lithium-ion concentration, and provides two examples of spatially and temporally resolved chemical properties inside batteries in 3D. XCS-CT was applied to study two types of rechargeable lithium batteries in standard coin cell casings: (1) a lithium-ion battery containing a cathode of bespoke microstructure and liquid electrolyte, and (2) a solid-state battery containing a solid-polymer electrolyte. The XCS-CT technique is beneficial to a wide variety of materials and systems to map chemical composition changes in 3D structures.

Beauveriolides, including the main beauveriolide I {systematic name: (3R,6S,9S,13S)-9-benzyl-13-[(2S)-hexan-2-yl]-6-methyl-3-(2-methyl­prop­yl)-1-oxa-4,7,10-tri­aza­cyclo­tridecane-2,5,8,11-tetrone, C27H41N3O5}, are a series of cyclo­depsipeptides that have shown promising results in the treatment of Alzheimer's disease and in the prevention of foam cell formation in atherosclerosis. Their crystal structure studies have been difficult due to their tiny crystal size and fibre-like morphology, until now. Recent developments in 3D electron diffraction methodology have made it possible to accurately study the crystal structures of submicron crystals by overcoming the problems of beam sensitivity and dynamical scattering. In this study, the absolute structure of beauveriolide I was determined by 3D electron diffraction. The cyclo­dep­si­peptide crystallizes in the space group I2 with lattice parameters a = 40.2744 (4), b = 5.0976 (5), c = 27.698 (4) Å and β = 105.729 (6)°. After dynamical refinement, its absolute structure was determined by comparing the R factors and calculating the z-scores of the two possible enanti­omorphs of beauveriolide I.

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.

3D electron diffraction (3D ED), or microcrystal electron diffraction (MicroED), has become an alternative technique for determining the high-resolution crystal structures of compounds from sub-micron-sized crystals. Here, we considered l-alanine, α-glycine and urea, which are known to form good-quality crystals, and collected high-resolution 3D ED data on our in-house TEM instrument. In this study, we present a comparison of independent atom model (IAM) and transferable aspherical atom model (TAAM) kinematical refinement against experimental and simulated data. TAAM refinement on both experimental and simulated data clearly improves the model fitting statistics (R factors and residual electrostatic potential) compared to IAM refinement. This shows that TAAM better represents the experimental electrostatic potential of organic crystals than IAM. Furthermore, we compared the geometrical parameters and atomic displacement parameters (ADPs) resulting from the experimental refinements with the simulated refinements, with the periodic density functional theory (DFT) calculations and with published X-ray and neutron crystal structures. The TAAM refinements on the 3D ED data did not improve the accuracy of the bond lengths between the non-H atoms. The experimental 3D ED data provided more accurate H-atom positions than the IAM refinements on the X-ray diffraction data. The IAM refinements against 3D ED data had a tendency to lead to slightly longer X—H bond lengths than TAAM, but the difference was statistically insignificant. Atomic displacement parameters were too large by tens of percent for l-alanine and α-glycine. Most probably, other unmodelled effects were causing this behaviour, such as radiation damage or dynamical scattering.

In this study, we report the results of continuous rotation electron diffraction studies of single DyPO4·nH2O (rhabdophane) nanocrystals. The diffraction patterns can be fit to a trigonal lattice (P3121) with lattice parameters a = 7.019 (5) and c = 6.417 (5) Å. However, there is also a set of diffuse background scattering features present that are associated with a disordered superstructure that is double these lattice parameters and fits with an arrangement of water mol­ecules present in the structure pore. Pair distribution function (PDF) maps based on the diffuse background allowed the extent of the water correlation to be estimated, with 2–3 nm correlation along the c axis and ∼5 nm along the a/b axis.

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules (e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

Although COF-300 is often used as an example to study the synthesis and structure of (3D) covalent organic frameworks (COFs), knowledge of the underlying synthetic processes is still fragmented. Here, an optimized synthetic procedure based on a combination of linker protection and modulation was applied. Using this approach, the influence of time and temperature on the synthesis of COF-300 was studied. Synthesis times that were too short produced materials with limited crystallinity and porosity, lacking the typical pore flexibility associated with COF-300. On the other hand, synthesis times that were too long could be characterized by loss of crystallinity and pore order by degradation of the tetrakis(4-aminophenyl)methane (TAM) linker used. The presence of the degradation product was confirmed by visual inspection, Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). As TAM is by far the most popular linker for the synthesis of 3D COFs, this degradation process might be one of the reasons why the development of 3D COFs is still lagging compared with 2D COFs. However, COF crystals obtained via an optimized procedure could be structurally probed using 3D electron diffraction (3DED). The 3DED analysis resulted in a full structure determination of COF-300 at atomic resolution with satisfying data parameters. Comparison of our 3DED-derived structural model with previously reported single-crystal X-ray diffraction data for this material, as well as parameters derived from the Cambridge Structural Database, demonstrates the high accuracy of the 3DED method for structure determination. This validation might accelerate the exploitation of 3DED as a structure determination technique for COFs and other porous materials.

Cryogenic electron microscopy (cryo-EM) is a pivotal technique for imaging macromolecular structures. However, despite extensive processing of large image sets collected in cryo-EM experiments to amplify the signal-to-noise ratio, the reconstructed 3D protein-density maps are often limited in quality due to residual noise, which in turn affects the accuracy of the macromolecular representation. Here, crefDenoiser is introduced, a denoising neural network model designed to enhance the signal in 3D cryo-EM maps produced with standard processing pipelines. The crefDenoiser model is trained without the need for `clean' ground-truth target maps. Instead, a custom dataset is employed, composed of real noisy protein half-maps sourced from the Electron Microscopy Data Bank repository. Competing with the current state-of-the-art, crefDenoiser is designed to optimize for the theoretical noise-free map during self-supervised training. We demonstrate that our model successfully amplifies the signal across a wide variety of protein maps, outperforming a classic map denoiser and following a network-based sharpening model. Without biasing the map, the proposed denoising method leads to improved visibility of protein structural features, including protein domains, secondary structure elements and modest high-resolution feature restoration.

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.