Segmented Architecture Research Articles

Visible light-driven photoreforming of polystyrene segmented glycopolymer architectures for enhanced hydrogen generation

In this report, a series of polystyrene segmented new glycopolymer architectures are synthesized, which are utilized in the photoreforming process to achieve a remarkable rate of hydrogen production. The primary building blocks of mono-, bi-, and tetra-functional photo-iniferter were employed in the RAFT polymerization process to design a series of block copolymer architectures using styrene and acetylated glucose methacrylate monomers. Acetylated polymer architectures exhibited higher thermal stability compared to deacetylated polymers. Deacetylated polymers showed lower Tg values than the acetylated polymers. In addition, a wide range of Tg values (55–96 °C) and variations in the Tm values of the acetylated polymers indicate the dependence on the nature of the pendant unit and macromolecular architecture. The deacetylated macromolecule, 1A-PS-b-PGMD diblock copolymer exhibits a hydrogen generation rate of ∼753 μmol/g/h with an AQY of ∼1.84% compared to that of the polystyrene segment alone (53 μmol/g/h, AQY of ∼0.02%). Within the range of possible synthesized glycopolymer architectures, linear and glucose-based triblock glycopolymers show promising activity. The kinetics of the water-splitting reaction are influenced by adjustments to both the solution's pH and the hydrophilicity of the glycomacromolecular chains.

Using structure prediction of negative sense RNA virus nucleoproteins to assess evolutionary relationships.

Negative sense RNA viruses (NSV) include some of the most detrimental human pathogens, including the influenza, Ebola, and measles viruses. NSV genomes consist of one or multiple single-stranded RNA molecules that are encapsidated into one or more ribonucleoprotein (RNP) complexes. These RNPs consist of viral RNA, a viral RNA polymerase, and many copies of the viral nucleoprotein (NP). Current evolutionary relationships within the NSV phylum are based on the alignment of conserved RNA-dependent RNA polymerase (RdRp) domain amino acid sequences. However, the RdRp domain-based phylogeny does not address whether NP, the other core protein in the NSV genome, evolved along the same trajectory or whether several RdRp-NP pairs evolved through convergent evolution in the segmented and non-segmented NSV genome architectures. Addressing how NP and the RdRp domain evolved may help us better understand NSV diversity. Since NP sequences are too short to infer robust phylogenetic relationships, we here used experimentally obtained and AlphaFold 2.0-predicted NP structures to probe whether evolutionary relationships can be estimated using NSV NP sequences. Following flexible structure alignments of modeled structures, we find that the structural homology of the NSV NPs reveals phylogenetic clusters that are consistent with RdRp-based clustering. In addition, we were able to assign viruses for which RdRp sequences are currently missing to phylogenetic clusters based on the available NP sequence. Both our RdRp-based and NP-based relationships deviate from the current NSV classification of the segmented Naedrevirales, which cluster with the other segmented NSVs in our analysis. Overall, our results suggest that the NSV RdRp and NP genes largely evolved along similar trajectories and even short pieces of genetic, protein-coding information can be used to infer evolutionary relationships, potentially making metagenomic analyses more valuable.

Ultrawide Dynamic Sensing from Single‐Photon Counting to Linear Detection Using a Segmented Superconducting Nanowire

AbstractDespite their exceptional sensitivity, single photon detectors typically exhibit limited tolerance to strong light compared to conventional linear photodetectors. Consequently, a disparity arises between these two detector types, hindering the achievement of both high sensitivity and high dynamic range in sensing and imaging. To bridge this gap, a segmented architecture is implemented with a waveform‐variance readout scheme for extacting high‐flux photon informaiton.This approach gives an unprecedented ultra‐high dynamic range of 75 dB at a fixed bias current, where single photon counting mode and quasi‐linear photodetection mode coexist. High‐dynamic imaging, passive thermal imaging, and joint active and passive imaging are demonstrated, which validate the advantages of this dual‐mode detector. Such a versatile detector will offer enhanced flexibility, single‐photon sensitivity, as well as ultra‐wide dynamic range across various scientific and technical domains.

ASMEvoNAS: Adaptive segmented multi-objective evolutionary network architecture search

Network architecture search (NAS) has attracted much attention as an automatic design technique of network architecture. In particular, multi-objective evolutionary algorithms (MOEAs) have been a popular kind of optimizer in NAS due to their global optimization capability. However, as a population-based iterative search method, MOEAs are subject to the unbearable computational cost of individual evaluation on multiple objectives at each generation, which affects their generalization ability and transferability of MOEA-based NAS. Therefore, an adaptive segmented multi-objective evolutionary network architecture search (ASMEvoNAS) method is proposed in this paper. Firstly, an adaptive segmented evaluation strategy is designed to adaptively select different but more suitable objectives to efficiently assess the candidate architectures at different evolutionary stages, instead of evaluating them by all the considered objectives simultaneously. Thus, the computational cost and complexity of the search process can be controlled and reduced to some extent. Secondly, a preference-based pre-selection strategy is designed to filter out the initialized architectures with high parameter quantities to reduce the total parameter scale of the whole population and memory consumption. Last, a novel desirable gene reservation-based crossover and a directed connection-based mutation are proposed to produce offspring. Experimental results show that ASMEvoNAS shows promising performance on CIFAR-10, CIFAR-100, and ImageNet with error rates of 2.21%, 15.57%, and 24.43% top-1, respectively. The proposed method reduces the search cost to 0.36 GPU-Days on CIFAR-10 while maintaining competitive classification performance compared to state-of-the-art networks. In addition, ASMEvoNAS presents superior performance when dealing with the considered transfer tasks, as well as the benchmark dataset of NAS.

Stability Islands and the Folding Cooperativity of a Seven-Repeat Array from Topoisomerase V.

Cooperativity is a central feature of protein folding, but the thermodynamic and structural origins of cooperativity remain poorly understood. To quantify cooperativity, we measured guanidine-induced unfolding transitions of single helix-hairpin-helix (HhH)2 repeats and tandem pairs from a seven-repeat segment of Methanopyrus kandleri Topoisomerase V (Topo V) to determine intrinsic repeat stability and interfacial free energies between repeats. Most single-repeat constructs are folded and stable; moreover, several pairs have unfolding midpoints that exceed midpoints of the single repeats they comprise, demonstrating favorable coupling between repeats. Analyzing unfolding transitions with a modified Ising model, we find a broad range of intrinsic and interfacial free energies. Surprisingly, the G repeat, which lacks density in the crystal structure of Topo V without DNA, is the most stable repeat in the array. Using nuclear magnetic resonance spectroscopy, we demonstrate that the isolated G repeat adopts a canonical (HhH)2 fold and forms an ordered interface with the F-repeat but not with the H repeat. Using parameters from our paired Ising fit, we built a partition function for the seven-repeat array. The multistate unfolding transition predicted from this partition function is in excellent agreement with the experimental unfolding transition, providing strong justification for the nearest-neighbor model. The seven-repeat partition function predicts a native state in which three independent segments ("stability islands") of interacting repeats are separated by two unstable interfaces. We confirm this segmented architecture by measuring the unfolding transition of an equimolar mixture of these three separate polypeptides. This segmented structural organization may facilitate wrapping around DNA.

An Efficient Segmented Random Access Scan Architecture with Test Compression

Integrated circuit (IC) chip designs relying on Random Access Scan (RAS) architecture for post-production structural tests typically provide lower test power dissipation, test data volume, and test application time compared to the classical serial scan-based Design for Test (DFT) methodology. However, previous RAS schemes incur high signal routing and test area overheads relative to the serial scan way. Unlike serial scan schemes, previous RAS schemes have not been effectively combined with test compression to further reduce test application time and test data volume. Authors have already formally documented a locally addressed (segmented) and compressed Segmented RAS (SRAS) architecture with low area overhead and test application time. This paper describes the SRAS architecture in more detail and provides comparative experimental results. Area overhead is reduced using test access hierarchy (segmented), while adding compression to RAS lowers the test application time. Also presented is another enhancement to incorporate a scan channel multiplex block at hierarchy segments which helps drastically decrease the area and routing overhead of the original architecture to practically implementable levels on commercial circuits. The extra Segment Data Multiplexor (SDM) blocks reduce the area overhead of other components by the multiplexing factor, and the reduction in overall area is significant based on experimental data. Test data compression and auto addressing of segments are achieved by transmitting a seed address to select segments with auto-increment or auto-decrement capability followed by either single cell selection or entire leaf cell segment selection. To further reduce the area overhead and test power, this architecture is enhanced to contain multiple channels at a cost of increased overall test application time with no increase in test data volume. Results of applying the enhancements to a large circuit with one level of intermediate segments with each of them having 256 leaf segments are presented in the paper with and without multichannel multiplexing for comparison.

A 72-GS/s, 8-Bit DAC-Based Wireline Transmitter in 4-nm FinFET CMOS for 200+ Gb/s Serial Links

This article details the design and measurement of a digital-to-analog converter (DAC)-based source-series terminated (SST) transmitter (TX) for wireline applications in 4-nm FinFET CMOS technology. The DAC achieves 8-bit resolution and high analog output bandwidth by using a segmented architecture along with a single-ended LSB. Strength adjustment of the lower four DAC LSBs relative to the upper four DAC MSBs is accomplished with a hybrid analog/digital tuning approach, which overcomes minimum device-size limitations that can limit the effectiveness of pure digital tuning for SST drivers. The resulting DAC design achieves well-matched MSB/LSB segments with −0.63/0.67 LSB integral nonlinearity (INL) and −0.16/0.43 LSB differential nonlinearity (DNL). Time-domain modulation of 216-Gb/s PAM8 and frequency-domain modulation of 212-Gb/s orthogonal frequency-division multiplexing (OFDM) are reported, demonstrating the capability of CMOS DACs to support frequency-domain modulation for wireline applications. The TX consumes 288 mW from a 0.95-V power supply.

Ferroelectric Ternary Content Addressable Memories for Energy-Efficient Associative Search

A fast and efficient search function across the database has been a core component for a number of data-intensive tasks in machine learning, IoT applications, and inference. However, the conventional digital machines implementing the search functionality with repetitive arithmetic operations suffer from the energy efficiency and performance degradation due to the significant data transfer between the storage and processing units in the Von Neumann architecture. Ternary content addressable memories (TCAMs) are an essential hardware form of computing-in-memory (CiM) designs that aim to overcome the data transfer bottlenecks by implementing the parallel associative search function within the memory blocks. While most state-of-the-art TCAM designs focus on improving the information density by harnessing compact nonvolatile memories (NVMs), little efforts have been spent on optimizing the energy efficiency of the NVM-based TCAM. In this article, by exploiting the ferroelectric FET (FeFET) as a representative NVM, we propose an NOR-type 2FeFET-1T and an NAND-type 2FeFET-2T TCAM designs that enable highly energy-efficient associative search by reducing the associated precharge overheads. We then propose a hybrid ferroelectric NAND-NOR (HFNN) TCAM design to further improve the energy efficiency. An HFNN-based segmented architecture is proposed to reduce the search delay and energy by search operation pipeline. Evaluation results suggest that the proposed 2FeFET-1T, 2FeFET-2T and HFNN TCAM design consume <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.03\times $ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8.08\times $ </tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$226.92\times $ </tex-math></inline-formula> less search energy than the conventional 16T complementary metal oxide semiconductor (CMOS) TCAM, respectively. Application benchmarking shows that our proposed 2FeFET-1T/2FeFET-2T/HFNN TCAM can save, on average, 45.2%/50.6%/57.5% the GPU energy consumption as compared to the conventional GPU.

Towards High Conversion Efficiency of Thermoelectric Modules Through Synergistical Optimization of Layered Materials.

Waste-heat electricity generation using high-efficiency solid-state conversion technology can significantly decrease dependence on fossil fuels. In this paper, we report a synergistical optimization of layered half-Heusler (hH) materials and module to improve thermoelectric conversion efficiency. This was realized by manufacturing multiple thermoelectric materials with major compositional variations and temperature-gradient-coupled carrier distribution by one-step spark plasma sintering. This strategy provides a solution to overcome the intrinsic concomitants of the conventional segmented architecture that only considers the matching of the figure of merit (zT) with the temperature gradient. The current design is dedicated to temperature-gradient coupled resistivity and compatibility matching, optimum zT matching, and reducing contact resistance sources. By enhancing the quality factor of the materials by Sb-vapor pressure-induced annealing, a superior zT of 1.47 at 973 K was achieved for (Nb, Hf)FeSb hH alloys. Along with the low-temperature high-zT hH alloys of (Nb, Ta, Ti, V)FeSb, the single stage layered hH modules were developed with efficiencies of ∼15.2% and ∼13.5% for the single-leg and unicouple thermoelectric modules, respectively, under ΔT of 670 K. Therefore, this work has a transformative impact on the design and development of next-generation thermoelectric generators for any thermoelectric materials families. This article is protected by copyright. All rights reserved.

High SFDR Current-Steering DAC With Splitting-and-Binary Segmented Architecture and Dynamic-Element-Matching Technique

This brief presents a current-steering digital-to-analog converter (DAC) with “4-bit splitting +8-bit binary” segmented topology. The proposed splitting decoding method can optimize the differential nonlinearity and output glitches of the DAC with a more simplified circuit scale than unary decoding. With a data-transmission topology, the splitting decoder has a low latency and accommodates fast synchronization control of current source switches. Moreover, the dynamic element matching (DEM) technique is used to suppress the harmonic distortion caused by the splitting current source mismatch. The DAC is designed using 0.18- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS technology and occupies an area of 452.82 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}\,\,\times491.76\,\,\mu \text{m}$ </tex-math></inline-formula> . With a 1.8 V analog supply and a 1.2 V digital supply, the DAC dissipates 12.2 mW at 500 MS/s. The spurious-free dynamic range of the DAC improves from 63.18 dB to 73.30 dB using DEM technique for an output signal of 8.30 MHz and by 8-10 dB within the Nyquist bandwidth.

Coronagraphic detection of Earth-like planets with large, actively controlled space telescopes

We explore the capabilities of large segmented telescopes with active and adaptive optics, with a particular focus on a system view, which includes use of approaches that are routine for current large ground-based telescopes. Using a physically motivated order-of-magnitude model, we show that continuous control of telescope misalignments using adjustable optics in an exoplanet imaging instrument significantly relaxes stability requirements for the entire observatory. We start with the recent analysis by Nemati et al., (2020, JATIS 6, id. 039002), which asserts that small monolithic mirrors have an engineering advantage over larger segmented mirrors when it comes to obtaining images stable enough for direct exoplanet imaging and characterization, i.e., picometer stability. When we fold these results into our model of closed-loop operations and properly partition engineering challenges by optimizing error budget allocations, we find that even for the most sensitive modes, allowable drifts are actually of the order of nanometer over an hour, well within easily engineered tolerances. While this order-of-magnitude analysis does not include full end-to-end modeling or proper engineering margins, it showcases the importance of considering continuous wavefront sensing and control when discussing the feasibility of future exoplanet missions. We also quantify how large segmented architectures, in spite of appearing more complex at the observatory level, facilitate closed-loop operations due to their large photon collection abilities. We place our work in the context of larger discussions on aperture size that highlight a more fundamental challenge: the deeper uncertainties in performance of an exo-earth characterizing telescope primarily reside in our knowledge of the frequency of exo-earths; the effects of geological age on the resulting atmospheres; and, most importantly, on the likelihood of detectable life arising on such planets. A mission that sets out to establish whether we are alone among the nearby stars must adopt a mission architecture that is resilient against such intrinsic uncertainties: uncertainties that only direct observations can resolve. Large apertures enabled by segmented telescope designs historically have demonstrated such resilience.

A 12-Bit Current-Steering DAC With Unary- Splitting -Binary Segmented Architecture and Improved Decoding Circuit Topology

This article presents a “three unary bits +five splitting bits + four binary bits” segmented 500-MS/s current-steering digital-to-analog converter (DAC). The proposed splitting decoding method is between the unary decoding and binary decoding, in terms of number of switched elements. It can optimize the differential nonlinearity and output glitches of DAC, with a more simplified circuit scale than unary decoding method. Due to the data-transmission topology, both the proposed thermometer and splitting decoders feature lower transistor count and occupy less area than other competitors. Their low latency accommodates to fast synchronization control of current source switches and its beneficial to the spurious-free dynamic range (SFDR) improvement of DAC. When implemented in a 0.18- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process, the 12-bit DAC occupies an active area of 536 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}\,\,\times \,\,340\,\,\mu \text{m}$ </tex-math></inline-formula> , with the proposed decoders occupying only 28 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}\,\,\times \,\,75\,\,\mu \text{m}$ </tex-math></inline-formula> . The DAC dissipates 17.20 mW at 500 MS/s with a 1.8-V analog supply and a 1.2-V digital supply. The differential and integral nonlinearities are measured to be 0.28 and 1.16 LSB, respectively. The DAC also features SFDRs of 68.83 and 62.06 dB for input signals of 6.34 and 239.74 MHz, respectively.

A Segmented Adaptive Router for Near Energy-Proportional Networks-on-Chip

A Network-on-Chip (NoC) is an essential component of a chip multiprocessor (CMP) which however contributes to a large fraction of system energy. The unpredictability of traffic across a NoC frequently involves an expensive over-sizing of NoC resources which in turn leads to a significant contribution to the CMP power consumption. There exists a body of work addressing this issue, however so far solutions fall short when aiming for power reduction whilst maintaining high NoC performance. This paper proposes to combine router architecture optimizations with smart resource management to overcome this limitation. Based on a fully segmented architecture, we present an online adaptive router adjusting its active routing resources to meet the current traffic demand. This enhanced power-gating strategy significantly decreases both static and dynamic power consumption of the NoC, up to 70% for synthetic traffic patterns and up to 58% for real traffic workloads, while preserving NoC latency and throughput. Thanks to these adaptive power-saving mechanisms the proposed segmented NoC router provides near energy-proportional operation across the range of used benchmarks.

Utility of Chemical Upcycling in Transforming Postconsumer PET to PBT-Based Thermoplastic Copolyesters Containing a Renewable Fatty-Acid-Derived Soft Block.

Thermoplastic copolyesters (TPCs) are important structural components in countless high performance applications that require excellent thermal stability and outstanding mechanical integrity. Segmented multiblock architectures are often employed for the most demanding applications, in which semicrystalline segments of poly(butylene terephthalate) (PBT) are combined with various low T g soft blocks. These segmented copolymers are nearly always synthesized from pristine feedstocks that are derived from fossil-fuel sources. In this work, we show a straightforward, one-pot synthetic approach to prepare TPCs starting from high-molar mass poly(ethylene terephthalate) recyclate (rPET) combined with a hydrophobic fatty acid dimer diol flexible segment. Transesterification is exploited to create a multiblock architecture. The high molar mass and segment distribution are elucidated by detailed size-exclusion chromatography and proton and carbon nuclear magnetic resonance spectroscopy. It is also shown that rPET can be chemically converted to PBT through a molecular exchange, in which the ethylene glycol is substituted by introducing 1,4-butane diol. A series of copolymers with various compositions was prepared with either PET or PBT segments and the final thermal properties and mechanical performance is compared between the two different constructs. Ultimately, PBT-based TPCs crystallize faster and exhibit a higher modulus over the range of explored compositions, making them ideal for applications that require injection molding. This represents an ideal, sustainable approach to making conventional TPCs, utilizing recyclate and biobased components to produce high performance polymer constructs via an easily accessible upcycling route.

A 36.2 dB High SNR and PVT/Leakage-Robust eDRAM Computing-In-Memory Macro With Segmented BL and Reference Cell Array

Computing-in-memory (CIM) shows high energy-efficiency through the analog DNN computation inside the memory macros. However, as the DNN size increases, the energy-efficiency of CIM is reduced by external memory access (EMA). One of the promising solutions is eDRAM based CIM to increase memory capacity with a high density cell. Although the eDRAM-CIM has a higher density than the SRAM-CIM, it suffers from both poor robustness and a low signal-to-noise ratio (SNR). In this brief, the energy-efficient eDRAM-CIM macro is proposed while improving computational robustness and SNR with three key features: 1) High SNR voltage-based accumulation with segmented BL architecture (SBLA), resulting in 17.1 dB higher SNR, 2) canceling PVT/leakage-induced error with common-mode error canceling (CMEC) circuit, resulting in 51.4&#x0025; PVT variation reduction and 51.4&#x0025; refresh power reduction, 3) a ReLU-based zero-gating ADC (ZG-ADC), resulting in ADC power reduction up to 58.1&#x0025;. According to these new features, the proposed eDRAM-CIM macro achieves 81.5-to-115.0 TOPS/W energy-efficiency with 209-to-295 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power consumption when 4b <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 4b MAC operation is performed with 250 MHz core frequency. The proposed macro also achieves 91.52&#x0025; accuracy at the CIFAR-10 object classification dataset (ResNet-20) without accuracy drop even with PVT variation.

Design and Implementation of High Speed and Low Power 12-bit SAR ADC using 22nm FinFET

Successive Approximation Register (SAR) Analog to Digital Converter (ADC) architecture comprises of sub modules such as comparator, Digital to Analog Converter and SAR logic. Each of these modules imposes challenges as the signal makes transition from analog to digital and vice-versa. Design strategies for optimum design of circuits considering 22nm FinFET technology meeting area, timing, power requirements and ADC metrics is presented in this work. Operational Transconductance Amplifier (OTA) based comparator, 12-bit two stage segmented resistive string DAC architecture and low power SAR logic is designed and integrated to form the ADC architecture with maximum sampling rate of 1 GS/s. Circuit schematic is captured in Cadence environment with optimum geometrical parameters and performance metrics of the proposed ADC is evaluated in MATLAB environment. Differential Non Linearity and Integral Non Linearity metrics for the 12-bit ADC is limited to +1.15/-1 LSB and +1.22/-0.69 LSB respectively. ENOB of 10.1663 with SNR of 62.9613 dB is achieved for the designed ADC measured for conversion of input signal of 100 MHz with 20dB noise. ADC with sampling frequency upto 1 GSps is designed in this work with low power dissipation less than 10 mW.

Design and development of industrial IoT-based system for behavior profiling of non-linear dynamic production systems based on energy flow theory

In this paper, a solution effective energy consumption monitoring of fast-response energy systems in industrial environments was proposed, designed, and developed. Moreover, in this research, production systems are characterized as non-linear dynamic systems, with the hypothesis that the identification and introduction of non-linear members (variables) can have a significant impact on improving system performance by providing clear insight and realistic representation of system behavior due to a series of non-linear activities that stimulate the system state changes, which can be spotted through the manner and intensity of energy use in the observed system. The research is oriented towards achieving favorable conditions to deploy dynamic energy management systems by means of the IoT and big data, as highly prominent concepts of Industry 4.0 technologies into scientifically-driven industrial practice. The motivation behind this is driven by the transition that this highly digital modern age brought upon us, in which energy management systems could be treated as a continual, dynamic process instead of remaining characterized as static with periodical system audits. In addition, a segmented system architecture of the proposed solution was described in detail, while initial experimental results justified the given hypothesis. The generated results indicated that the process of energy consumption quantification, not only ensures reliable, accurate, and real-time information but opens the door towards system behavior profiling, predictive maintenance, event forensics, data-driven prognostics, etc. Lastly, the points of future investigations were indicated as well.

Luminal Fluid Motion Inside an In Vitro Dissolution Model of the Human Ascending Colon Assessed Using Magnetic Resonance Imaging.

Knowledge of luminal flow inside the human colon remains elusive, despite its importance for the design of new colon-targeted drug delivery systems and physiologically relevant in silico models of dissolution mechanics within the colon. This study uses magnetic resonance imaging (MRI) techniques to visualise, measure and differentiate between different motility patterns within an anatomically representative in vitro dissolution model of the human ascending colon: the dynamic colon model (DCM). The segmented architecture and peristalsis-like contractile activity of the DCM generated flow profiles that were distinct from compendial dissolution apparatuses. MRI enabled different motility patterns to be classified by the degree of mixing-related motion using a new tagging method. Different media viscosities could also be differentiated, which is important for an understanding of colonic pathophysiology, the conditions that a colon-targeted dosage form may be subjected to and the effectiveness of treatments. The tagged MRI data showed that the DCM effectively mimicked wall motion, luminal flow patterns and the velocities of the contents of the human ascending colon. Accurate reproduction of in vivo hydrodynamics is an essential capability for a biorelevant mechanical model of the colon to make it suitable for in vitro data generation for in vitro in vivo evaluation (IVIVE) or in vitro in vivo correlation (IVIVC). This work illustrates how the DCM provides new insight into how motion of the colonic walls may control luminal hydrodynamics, driving erosion of a dosage form and subsequent drug release, compared to traditional pharmacopeial methods.

Mechanically versatile isosorbide‐based thermoplastic copolyether‐esters with a poly(ethylene glycol) soft segment

AbstractSegmented thermoplastic copolyether esters (TPEE's) with a partially renewable hard block containing isosorbide (ISB) and poly(ethylene glycol) (PEG) soft blocks were prepared by melt polycondensation. A range of compositions was accessible despite the relatively low reactivity of the sterically and electronically hindered ISB monomer. The small‐scale reactions performed in the melt were limited in terms of achievable molar mass. This is attributed to the challenge of attaining stoichiometric balance in the feed and maintaining this balance throughout the high temperature (&gt;200°C) reactions. Nevertheless, products were isolated that could be manipulated and melt‐pressed into specimen for tensile testing. Varying the feed compositions gave rise to copolymers exhibiting a broad range of mechanical properties (elastic modulus from 1–66 MPa). These characteristics are consistent with a segmented polymer architecture with morphological features similar to commercially available TPEE counterparts. These results pave the way for more responsibly sourced building blocks being incorporated into materials with high market value potential.

Robust Circuit and System Design for General-Purpose Computational Resistive Memories

Resistive switching devices (memristors) constitute a promising device technology that has emerged for the development of future energy-efficient general-purpose computational memories. Research has been done both at device and circuit level for the realization of primitive logic operations with memristors. Likewise, important efforts are placed on the development of logic synthesis algorithms for resistive RAM (ReRAM)-based computing. However, system-level design of computational memories has not been given significant consideration, and developing arithmetic logic unit (ALU) functionality entirely using ReRAM-based word-wise arithmetic operations remains a challenging task. In this context, we present our results in circuit- and system-level design, towards implementing a ReRAM-based general-purpose computational memory with ALU functionality. We built upon the 1T1R crossbar topology and adopted a logic design style in which all computations are equivalent to modified memory read operations for higher reliability, performed either in a word-wise or bit-wise manner, owing to an enhanced peripheral circuitry. Moreover, we present the concept of a segmented ReRAM architecture with functional and topological features that benefit flexibility of data movement and improve latency of multi-level (sequential) in-memory computations. Robust system functionality is validated via LTspice circuit simulations for an n-bit word-wise binary adder, showing promising performance features compared to other state-of-the-art implementations.