Chemical synthesis of amino acids directly from biomass feedstock is rare. Reported here is a one‐step protocol to convert crude glycerol, from the biodiesel industry, into 43 % alanine over a ...Ru1Ni7/MgO catalyst. The multifunctional catalytic system promotes glycerol conversion into lactic acid, and then into alanine. X‐ray absorption spectroscopy and scanning transmission electron microscopy revealed the existence of bimetallic RuNi species, whereas density‐functional theory calculations suggested Ni‐doped Ru substantially decreased the Ea of C−H bond dissociation of lactate alkoxide to form pyruvate, which is the rate‐determining step. The catalytic route established in this work creates new opportunities for glycerol utilization and enriches the substrate scope of renewable feedstock to access value‐added amino acids.
Direct conversion: 43 % alanine was achieved from crude glycerol over a Ru1Ni7/MgO catalyst. Ni‐doped Ru remarkably promoted lactic acid amination, a key step in the reaction. The catalytic route creates new opportunities for glycerol utilization and enriches the substrate scope of renewable feedstock to access value‐added amino acids.
Physically unclonable function (PUF) and true random number generator (TRNG) are the indispensable primitives for the Internet-of-Things (IoT) security. In this article, a highly robust unified ...PUF<inline-formula> <tex-math notation="LaTeX">/ </tex-math></inline-formula>TRNG design is demonstrated. An entropy source (ES) chip based on 40-nm resistive random access memory (RRAM) is designed and fabricated, and a pseudo-forming technique is developed to ensure excellent robustness. The unified PUF<inline-formula> <tex-math notation="LaTeX">/ </tex-math></inline-formula>TRNG is tested across <inline-formula> <tex-math notation="LaTeX">- 55\,\,^{\circ }\text{C} </tex-math></inline-formula> to 125 °C with different supply voltages, achieving < 0.001% bit error rate (BER) and >0.999 worst case min-entropy simultaneously. Excellent randomness is verified by NIST SP800-22 and 90B tests. This highly robust unified design can implement an authentication system with the authentication error rate (AER) approaching 0% and thus is promising for future IoT security applications.
Resistive random access memory (RRAM) has been extensively studied as a promising candidate for neuromorphic computing. So far, high-precision multibit programing of RRAM for neuromorphic systems is ...done cell-by-cell, which can be very time-consuming. This brief demonstrates a row-by-row parallel program-verify scheme on a fabricated 160-Kb RRAM array using the incremental gate voltage programing (IGVP) method. Statistical analysis indicates that the optimal conductance tuning step size can accelerate the programing process and improve the success rate. Also, for the first time, the fundamental relations between programing success rate, critical path, and parallel efficiency for parallel program-verify methodology on the RRAM array are systematically studied. Moreover, a software-comparable recognition accuracy with only <0.3% accuracy loss is experimentally achieved for MNIST data set classification utilizing the proposed parallel program-verify scheme.
The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often ...employed in virtual auditory systems. Different from well-demonstrated classification applications, all output neurons in localization tasks contribute to the predicted direction, introducing much higher challenges for hardware demonstration with memristor arrays. In this work, with the proposed multi-threshold-update scheme, we experimentally demonstrate the in-situ learning ability of the sound localization function in a 1K analogue memristor array. The experimental and evaluation results reveal that the scheme improves the training accuracy by ∼45.7% compared to the existing method and reduces the energy consumption by ∼184× relative to the previous work. This work represents a significant advance towards memristor-based auditory localization system with low energy consumption and high performance.
Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using ...analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.
Under the background of "Internet ", international cooperation between enterprises becomes more convenient and efficient. In the Internet platform, both enterprises can not only realize long-distance ..."face-to-face" communication, but also realize information exchange through various communication platforms. Compared with the traditional business model, business English under the background of "Internet" is more professional and targeted, so business English translation should not only accurately and effectively transmit business information, but also pay attention to the exchange of aesthetic experience between the two sides. By analyzing the practical application of business English translation, this paper puts forward three aesthetic experiences: harmonious beauty, overall beauty and cultural beauty.
In this article, we review the existing analog resistive switching memory (RSM) devices and their hardware technologies for in-memory learning, as well as their challenges and prospects. Since the ...characteristics of the devices are different for in-memory learning and digital memory applications, it is important to have an in-depth understanding across different layers from devices and circuits to architectures and algorithms. First, based on a top-down view from architecture to devices for analog computing, we define the main figures of merit (FoMs) and perform a comprehensive analysis of analog RSM hardware including the basic device characteristics, hardware algorithms, and the corresponding mapping methods for device arrays, as well as the architecture and circuit design considerations for neural networks. Second, we classify the FoMs of analog RSM devices into two levels. Level 1 FoMs are essential for achieving the functionality of a system (e.g., linearity, symmetry, dynamic range, level numbers, fluctuation, variability, and yield). Level 2 FoMs are those that make a functional system more efficient and reliable (e.g., area, operational voltage, energy consumption, speed, endurance, retention, and compatibility with back-end-of-line processing). By constructing a device-to-application simulation framework, we perform an in-depth analysis of how these FoMs influence in-memory learning and give a target list of the device requirements. Lastly, we evaluate the main FoMs of most existing devices with analog characteristics and review optimization methods from programming schemes to materials and device structures. The key challenges and prospects from the device to system level for analog RSM devices are discussed.
Abstract
Power dissipation is a fundamental issue for future chip-based electronics. As promising channel materials, two-dimensional semiconductors show excellent capabilities of scaling dimensions ...and reducing off-state currents. However, field-effect transistors based on two-dimensional materials are still confronted with the fundamental thermionic limitation of the subthreshold swing of 60 mV decade
−1
at room temperature. Here, we present an atomic threshold-switching field-effect transistor constructed by integrating a metal filamentary threshold switch with a two-dimensional MoS
2
channel, and obtain abrupt steepness in the turn-on characteristics and 4.5 mV decade
−1
subthreshold swing (over five decades). This is achieved by using the negative differential resistance effect from the threshold switch to induce an internal voltage amplification across the MoS
2
channel. Notably, in such devices, the simultaneous achievement of efficient electrostatics, very small sub-thermionic subthreshold swings, and ultralow leakage currents, would be highly desirable for next-generation energy-efficient integrated circuits and ultralow-power applications.
► Food melanoidins are generally anionic coloured compounds. ► Melanoidins are LMW pigments or HMW compounds with LMW chromophore. ► Melanoidins have several potential health-promoting effects. ► ...Structure–health effects relationship of melanoidins has not been fully elucidated.
Melanoidins are compounds generated in the late stages of the Maillard reaction from reducing sugars and proteins or amino acids during food processing and preservation. Recently the effects of melanoidins on human health and the chemical characterisation of the beneficial components have gained a lot of attention. Food melanoidins have been reported to be anionic, coloured compounds and some of their key chromophores have been elucidated. The antioxidant activity and other biological effects of melanoidins from real foods and model systems have been widely studied. Despite this, very few different melanoidin structures have actually been described, and specific health effects have yet to be linked to chemically distinct melanoidins. The variety of different Maillard reaction products formed during the reaction, in conjunction with the difficulty in purifying and identifying them, makes a thorough analysis of melanoidins challenging. This review provides a comprehensive look at what is known to date about melanoidin structure, the formation mechanism for these compounds, and the biological properties related to the beneficial health effects of melanoidins.
The electrochemical nitrate reduction reaction (NO
RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, ...tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metal d-states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the hollow *N and subsurface metal atoms is significant while the bridge-bidentate *NO
is not directly affected. Among those intermetallics predicted, we synthesize monodisperse ordered B2 CuPd nanocubes that demonstrate high performance for NO
RR to ammonia with a Faradaic efficiency of 92.5% at -0.5 V
and a yield rate of 6.25 mol h
g
at -0.6 V
. This study provides machine-learned design rules besides the d-band center metrics, paving the path toward data-driven discovery of catalytic materials beyond linear scaling limitations.
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