The crystal structure of anthraquinone-2-carboxylic acid has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Anthraquinone-2-carboxylic acid crystallizes in space group P-1 (#2) with a = 3.7942(2), b = 13.266(5), c = 22.835(15) Å, α = 73.355(30), β = 89.486(6), γ = 86.061(1)°, V = 1098.50(7) Å3, and Z = 4. The crystal structure contains two independent molecules of anthraquinone-2-carboxylic acid. Although the expected hydrogen-bonded dimers are present, the dimers are not centrosymmetric. The dimer contains one molecule of each planar low-energy conformation. The crystal structure consists of a herringbone array of centrosymmetric pairs of molecules parallel to the bc-plane. The molecules stack along the short a-axis. The powder pattern has been submitted to ICDD® for inclusion in the Powder Diffraction File™ (PDF®).

The seed coat of tobacco displays an intriguing cellular pattern characterised by puzzle-like shapes whose specific function is unknown. Here, we perform a detailed investigation of the structure of tobacco seeds by electron microscopy and then follow the germination process by time lapse optical microscopy. We use particle image velocimetry to reveal the local deformation fields and perform compression experiments to study the mechanical properties of the seeds as a function of their hydration. To understand the mechanical role of the observed coat structure, we perform finite element calculations comparing structure with puzzle-shaped cells with similar structures lacking re-entrant features. The results indicate that puzzle-shaped cells act as stress suppressors and reduce the Poisson’s ratio of the seed coat structure. We thus conclude that the peculiar cellular structure of these seed coats serves a mechanical purpose that could be relevant to control germination.

The dynamic charge density of KZnB3O6, which contains edge-sharing BO4 units, has been characterized using laboratory and synchrotron X-ray diffraction techniques. The experimental electron density distribution (EDD) was constructed using the maximum-entropy method (MEM) from single crystal diffraction data obtained at 81 and 298 K. Additionally, MEM-based pattern fitting (MPF) method was employed to refine the synchrotron powder diffraction data obtained at 100 K. Both the room-temperature single crystal diffraction data and the cryogenic synchrotron powder diffraction data reveal an intriguing phenomenon: the edge-shared B2O2 ring exhibits a significant charge density accumulation between the O atoms. Further analysis of high-quality single crystal diffraction data collected at 81 K, with both high resolution and large signal-to-noise ratio, reveals no direct O–O bonding within the B2O2 ring. The experimental EDD of KZnB3O6 obtained aligns with the results obtained from ab-initio calculations. Our work underscores the importance of obtaining high-quality experimental data to accurately determine EDDs.

The crystal structure of anhydrous Al-MFI (NH4) containing adsorbed Ar has been determined and refined using synchrotron X-ray powder diffraction data taken at 90 K, and optimized using density functional theory techniques. Six highly occupied Ar sites almost completely fill the pore volume of the zeolite. Changing the gas flow from Ar to He at 90 K decreases the Ar occupancies of all six sites, but two decrease more than the others. Warming the sample from 90 to 295 K in Ar flow results in further decreases in site occupancies, but five of the original six sites persist.

Biocalcification is a naturally occurring mineralisation phenomenon resulting from the urease produced by microorganisms inhabiting soil environments. This process, often referred to as microbially induced calcite precipitation (MICP), is primarily exploited in an engineering context for soil stabilisation and the repair of concrete structures. MICP represents an emerging area of research in architecture and design. In this paper, we discuss the appropriation of MICP on Papier Plume, a foam made of paper waste used in the context of ImpressioVivo: a design-led research project exploring the conception and fabrication of 3D-printed and bacterially induced bio-sourced materials for a circular design framework. In the light of a previous study based on two strategies of calcification: (1) direct inoculation (2) spraying, we – a team of two designers and a microbiologist – discuss the relevance of an immersion strategy applied to the dry paper foam substrate. By doing so, we reflect on the relevance of MICP as a material design process underpinned by sustainable and circularity concerns, from a design perspective, but also into an attempt to embrace the perspective of the bacteria supporting these experiments; namely Sporosarcina pasteurii.

Neural networks are vulnerable to adversarial perturbations: slight changes to inputs that can result in unexpected outputs. In neural network control systems, these inputs are often noisy sensor readings. In such settings, natural sensor noise – or an adversary who can manipulate them – may cause the system to fail. In this paper, we introduce the first technique to provably compute the minimum magnitude of sensor noise that can cause a neural network control system to violate a safety property from a given initial state. Our algorithm constructs a tree of possible successors with increasing noise until a specification is violated. We build on open-loop neural network verification methods to determine the least amount of noise that could change actions at each step of a closed-loop execution. We prove that this method identifies the unsafe trajectory with the least noise that leads to a safety violation. We evaluate our method on four systems: the Cart Pole and LunarLander environments from OpenAI gym, an aircraft collision avoidance system based on a neural network compression of ACAS Xu, and the SafeRL Aircraft Rejoin scenario. Our analysis produces unsafe trajectories where deviations under $1{\rm{\% }}$ of the sensor noise range make the systems behave erroneously.

Self-sealing is becoming a necessary function in sustainable systems for enhancing materials lifetime and improving system resilience. In this context, plants are prime models as they have developed various concepts. Moreover, implementing self-sealing into engineering applications is becoming more feasible with the advent of programmable materials. That is because these materials are able to implement simple algorithms by locally and globally processing information and adapting to changing conditions. However, the transfer of bio-inspired system functions into technological applications is tedious. It requires an intimate understanding of the selected biological models and the technological problem. To support the transfer of concepts and principles, we propose easy-to-read flow charts as a common language for biologists and engineers. Describing the functions of biological models and their underlying functional principles as process flow diagrams, allows to convert detailed biological insights into sequential step-wise algorithms, which turns the focus on building blocks necessary to achieve specific functions. We present a first set of flow charts for selected plant models exhibiting different self-sealing mechanisms based on hydraulics, mechanical instabilities, and sap release. For these plant-inspired control flows, we identified technical statements to classify metamaterial mechanisms and unit cells, which represent possible solutions for the steps in the algorithms for sealing procedures in future technical applications. A common language of flow charts will simplify the transfer of functional principles found in plant models into technological applications. Programmable materials expand the available design space of materials, putting us within reach to implement self-sealing functions inspired by plants.

The field of research related to CO2 capture is significant and really attractive for sustainable green chemistry. Focusing attention on this topic in our research led to obtaining new compounds based on diamines. As a result of the syntheses carried out using aqueous solutions of diamines exposed to the slow action of carbon dioxide from the air, three new monocarbamates were obtained. X-ray powder diffraction data for the obtained compounds: 12-propCO2 (C4H10N2O2) [a = 9.3033(7), b = 9.2485(7), c = 7.4735(7) Å, β = 111.214(7)°, V = 599.46 Å3, Z = 4, space group Ia]; 13-propCO2 (C4H10N2O2) [a = 5.0065(10), b = 12.2093(23), c = 4.9006(10) Å, β = 96.457(18)°, V = 297.65 Å3, Z = 2, space group P21]; and 13-dytekCO2 (C6H14N2O2) [a = 28.374(3), c = 5.1726(9) Å, V = 3606.53 Å3, Z = 18, space group $R\bar{3}$] are reported in this paper.