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The title compound, 3-hydroxypropionitrile, was crystallized repeatedly in situ inside a quartz capillary using a liquid nitrogen cryostream. The X-ray powder diffraction patterns obtained indicated the presence of two distinct crystalline phases. The cleanest datasets for each of the phases were used to solve the crystal structures via simulated annealing, followed by refinement and optimization via dispersion-corrected density functional theory (DFT) calculations, with a final Rietveld refinement against the experimental data. The two structures appear to correspond to those proposed in a 1960s literature vibrational spectroscopy paper, one being the more stable with a gauche molecular conformation and the second metastable phase more complex with mixed conformations. Dispersion-corrected DFT computation using lattice parameters for both phases obtained from a single 84 K dataset with co-existing phases shows the stable and metastable phases to differ in energy by less than 0.5 kJ mol−1. A comparison of experimental far infrared spectra published in the 1960s with those calculated from the proposed crystal structures provides some independent supporting evidence for the proposed structures.
The crystal structure of ractopamine hydrochloride has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Ractopamine hydrochloride crystallizes in space group Pbca (#61) with a = 38.5871(49), b = 10.7691(3), c = 8.4003(2) Å, V = 3490.75(41) Å3, and Z = 8. The ractopamine cation contains two chiral centers, and the sample consists of a mixture of the S,S/R,R/S,R and R,S forms. Models for the two diastereomers S,S and S,R were refined, and yielded equivalent residuals, but the S,R form is significantly lower in energy. The crystal structure consists of layers of molecules parallel to the bc-plane. In each structure one of the H atoms on the protonated N atom acts as a donor in a strong discrete N–H⋯Cl hydrogen bond. Hydroxyl groups act as donors in O–H⋯Cl and O–H⋯O hydrogen bonds. Both the classical and C–H⋯Cl and C–H⋯O hydrogen bonds differ between the forms, helping to explain the large microstrain observed for the sample. The powder pattern has been submitted to ICDD® for inclusion in the Powder Diffraction File™ (PDF®).
Materials in a high radioactive environment undergo structural changes. X-ray diffraction (XRD) is commonly used to study the micro-structural changes of such materials. Therefore, a safe procedure is required for the preparation of specimens. In this paper, a simple methodology for the preparation of radioactive powder specimens to be analyzed in a non-nuclearized laboratory diffractometer is presented. The process is carried out inside a shielded glove box, where the milling of the radioactive sample and specimen preparation occurs. Minimum amount of sample is required (<20 mg), which is drop-casted on a polyether ether ketone (PEEK) foil and glue-sealed inside a disposable plastic holder for a safe handling of the specimen. One example using neutron-irradiated granite is shown, where unit-cell parameters and crystal density of the main phases were calculated. The developed methodology represents an easy and affordable way to study neutron irradiated materials with low activity at laboratory scale.
The structure of Ni(3-amino-4,4′-bipyridine)[Ni(CN)4] (or known as Ni-BpyNH2) in powder form was determined using synchrotron X-ray diffraction and refined using the Rietveld refinement technique (R = 8.8%). The orthorhombic (Cmca) cell parameters were determined to be a = 14.7218(3) Å, b = 22.6615(3) Å, c = 12.3833(3) Å, V = 4131.29(9) Å3, and Z = 8. Ni-BpyNH2 forms a 3-D network, with a 2-D Ni(CN)4 net connecting to each other via the BpyNH2 ligands. There are two independent Ni sites on the net. The 2-D nets are connected to each other via the bonding of the pyridine “N” atom to Ni2. The Ni2 site is of six-fold coordination to N with relatively long Ni2–N distances (average of 2.118 Å) as compared to the four-fold coordinated Ni1–C distances (average of 1.850 Å). The Ni(CN)4 net is arranged in a wave-like fashion. The functional group, –NH2, is disordered and was found to be in the m-position relative to the N atom of the pyridine ring. Instead of having a unique position, N has ¼ site occupancy in each of the four m-positions. The powder reference diffraction pattern for Ni-BpyNH2 was prepared and submitted to the Powder Diffraction File (PDF) at the International Centre of Diffraction Data (ICDD).
A model for the crystal structure of carbadox has been generated and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Carbadox crystallizes in space group P21 (#4) with a = 13.8155(3), b = 21.4662(1), c = 16.3297(3) Å, β = 110.0931(7)°, V = 4548.10(3) Å3, and Z = 16. The crystal structure is characterized by approximately parallel stacking of the eight independent carbadox molecules parallel to the bc-plane. There are two different molecular configurations of the eight carbadox molecules; five are in the lower-energy configuration and three are in a ~10% higher-energy configuration. This arrangement likely achieves the lowest-energy crystalline packing via hydrogen bonding. Hydrogen bonds link the molecules both within and between the planes. Each of the amino groups forms a N–H⋯O hydrogen bond to an oxygen atom of the 1,4-dioxidoquinoxaline ring system of another molecule. The result is four pairs of hydrogen-bonded molecules, which form rings with graph set R2,2(14). Variation in specimen preparation can affect the preferred orientation of particles considerably. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).
The crystal structure of indacaterol hydrogen maleate has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Indacaterol hydrogen maleate crystallizes in space group P-1 (#24) with a = 8.86616(9), b = 9.75866(21), c = 16.67848(36) Å, α = 102.6301(10), β = 94.1736(6), γ = 113.2644(2)°, V = 1273.095(7) Å3, and Z = 2 at 295 K. The crystal structure consists of layers of cations and anions parallel to the ab-plane. Traditional N–H⋯O and O–H⋯O hydrogen bonds link the cations and anions into chains along the a-axis. There is a strong intramolecular charge-assisted O–H⋯O hydrogen bond in the non-planar hydrogen maleate anion. There are also two C–H⋯O hydrogen bonds between the anion and cation. The cation makes a strong N–H⋯O hydrogen bond to the anion, but also acts as a hydrogen bond donor to an aromatic C in another cation. The amino group makes bifurcated N–H⋯O hydrogen bonds, one intramolecular and the other intermolecular. The hydroxyl group acts as a donor to another cation. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).
Biodesign is a relatively new interdisciplinary field, which has grown rapidly over the last decade (as evidenced for example by the growth in student teams entering the Biodesign Challenge from 9 in 2016 to 52 in 2024).
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.
Artificial intelligence (AI) has always drawn inspiration from the brain, from its most basic forms like nodes and layers to more recent advances that mimic individual neurons and various aspects of visual and sensory processing.
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.
Intelligent electromagnetic (EM) sensing is a powerful contactless examination tool in science, engineering and military, enabling us to 'see' and 'understand' visually invisible targets. Using intelligence, the sensor can organize by itself the task-oriented sensing pipeline (data acquisition plus processing) without human intervention. Intelligent metasurface sensors, synergizing ultrathin artificial materials (AMs) for flexible wave manipulation and artificial intelligences (AIs) for powerful data manipulation, emerge in response to the proper time and conditions, and have attracted growing interest over the past years. The authors expect that the results in this Element could be utilized to achieve the goal that conventional sensors cannot achieve, and that the developed strategies can be extended over the entire EM spectra and beyond, which will produce important impacts on the society of the robot-human alliance.
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.
Master fundamental technologies for modern semiconductor integrated circuits with this definitive textbook. It includes an early introduction of a state-of-the-art CMOS process flow, exposes students to big-picture thinking from the outset, and encourages a practical integration mindset. Extensive use of process and TCAD simulation, using industry tools such as Silvaco Athena and Victory Process, provides students with deeper insight into physical principles, and prepares them for applying these tools in a real-world setting. Accessible framing assumes only a basic background in chemistry, physics and mathematics, providing a gentle introduction for students from a wide range of backgrounds; and over 450 figures (many in color), and more than 280 end-of-chapter problems, will support and cement student understanding. Accompanied by lecture slides and solutions for instructors, this is the ideal introduction to semiconductor technology for senior undergraduate and graduate students in electrical engineering, materials science and physics, and for semiconductor engineering professionals seeking an authoritative introductory reference.