bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Catalyst Surface Structure on the Electrochemical Hydrogenation of Cis,Cis-Muconic Acid
Authors: Prabhu Prathamesh Tushar , Patel Deep M. , Kling Samantha , Nguyen Huy , Roling Luke T. , Tessonnier Jean-Philippe 
Published: August 2024

Adipic acid (AA) production from petroleum-based cyclohexane is one of the largest chemical processes in terms of annual volumetric turnover accounting for 3 million tons as of 2022. The current commercial approach to synthesize AA is through the oxidation of petroleum-derived cyclohexane using nitric acid. The release of N2O in stoichiometric amounts makes it one of the most significant greenhouse gas (GhG) emitting processes. The abundance of biomass in the Midwestern United States has driven significant research efforts to synthesize bio-derived and sustainable commodity products and lower the chemical industry’s carbon footprint.1
cis,cis-Muconic acid (ccMA), a biobased C6 diunsaturated diacid platform molecule can be transformed to commodity chemicals like caprolactam, adipic acid, and terephthalic acid, with AA being of particular interest for the synthesis of nylon 6,6.2

For the first time in literature, we demonstrate appreciable production of AA (conversion: 91%, selectivity: >95%) through electrochemical hydrogenation (ECH) of ccMA on PGM catalysts. Carbon-supported palladium (Pd/C) and platinum (Pt/C) selectively produced AA while bulk Pd and Pt yielded the monounsaturated trans-3-hexenedioic acid (t3HDA) intermediate and H2 under all tested conditions. Such an influence of surface structure on the electrochemistry of organics is not unprecedented. Koper et. al3 studied Pt single crystals for the electrochemical hydrogenation of acetone and showed how activity, selectivity, and extent of catalytic poisoning are highly sensitive to the Pt surface structure. Similarly, we used density functional calculations to elucidate the structure-sensitive nature of ccMA ECH and its intermediates by identifying thermodynamically preferred reaction pathways as a function of surface geometry (terrace vs steps). The energetics coupled with experimental observations suggest that the reduction of ccMA to t3HDA occurs through an outer sphere proton-coupled electron transfer mechanism, while the reduction of HDA to AA preferentially occurs on Pd and Pt (111), the most abundant facet in Pd/C and Pt/C. Our calculations also explain the exceptional performance of Pd/C compared to Pt/C by the weaker binding of Pd terrace sites compared to Pt. Overall, combining renewable electricity, in-situ hydrogen generation from water, and a biologically-produced intermediate enabled us to open a sustainable route for bio-adipic acid production. This allows us to further design and optimize the catalyst for the selective production of biobased AA.
References:
(1) Dell’Anna, M. N. et al. Green Chem.
23, 6456–6468 (2021).
(2) Matthiesen, J. E. et al. ACS Sustain. Chem. Eng. 4, 3575–3585 (2016).
(3) Bondue, C. J. et al. Nat Catal. 2, 243-250 (2019)

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(Invited) Novel Neuromorphic Computing Paradigms Enabled By Emerging Memory Devices
Authors: Jha Rashmi , Gogi Vamshi Kiran Kiran , Barve Siddharth 
Published: August 2024

Implementation of Artificial Intelligence and Machine Learning algorithms on conventional Von Neumann computing architectures are crippled by the memory-wall bottleneck. To overcome these issues, novel computing architectures with high-bandwidth memories, in-memory computing, and near-memory computing capabilities are being developed. Almost all of these architectures will benefit from high-density on-chip non-volatile memories, offered by the emerging non-volatile memory devices. Additionally, emerging memory devices offer rich device physics that can be leveraged for the implementation of novel computing paradigms. This paper will talk about three such emerging memory technologies: Vertical-Thin Film Transistors-Resistive Random Access Memory (V-TFT-RRAMs), Gated-RRAMs, and Ferroelectric Field Effect transistors (FeFETs). A comparative studies of various conventional neuromorphic computing approaches that can be implemented using these devices will be discussed. Finally, materials and device requirements and pending challenges will be discussed by successful realization of the proposed computing approaches.	Implementation of Artificial Intelligence and Machine Learning algorithms on conventional Von-Neumann computing architectures are crippled by the memory-wall bottleneck. To overcome these issues, novel computing architectures with high-bandwidth memories, in-memory computing, and near-memory computing capabilities are getting developed. Almost all of these architectures will benefit from high-density on-chip non-volatile memories, offered by the emerging non-volatile memory devices. Additionally, emerging memory devices offer a rich set of device physics that can be leveraged for the implementation of novel computing paradigms. This paper will talk about three such emerging memory technologies: Vertical-Thin Film Transistors-Resistive Random Access Memory (V-TFT-RRAMs), Gated-RRAMs, and Ferroelectric Field Effect Transistors (FeFETs). A comparative studies of various unconventional and brain-inspired neuromorphic computing approaches that can be implemented using these devices will be discussed. Finally, materials and device requirements and pending challenges will be discussed for these device technologies.
(Invited) Analog Computing with High Precision and Programmability Enabled by Memristors
Authors: Song Wenhao , Yang J. Joshua 
Published: August 2024

While digital computing dominates the technological landscape, analog computing distinguishes itself with superior energy efficiency and high throughput. However, its historical limitation in precision and programmability has confined its application to specific and low-precision domains, notably in neural networks. The escalating challenge posed by the analog data deluge calls for versatile analog platforms. These platforms must not only exhibit exceptional efficiency but also boast reconfigurability and precision.
Recent breakthroughs in analog devices, such as memristors, have laid the groundwork for unparalleled analog computing capabilities. Leveraging the multifaceted role of memristors, we introduce memristive field-programmable analog arrays (FPAAs), mirroring the functionality of their digital counterparts, field-programmable digital arrays (FPGAs). To elevate precision, we delve into the origins of reading noise, successfully mitigating it and achieving an unparalleled 2048 conductance levels in individual memristors—equivalent to 11 bits per cell, setting a record precision among diverse memory types. Acknowledging the persistent demand for single or double precision in various applications, we propose and develop a circuit architecture and programming protocol. This innovation enables analog memories to attain arbitrarily high precision with minimal circuit overhead. Our experimental validation involves a memristor System-on-Chip fabricated in a standard foundry, demonstrating significantly improved precision and power efficiency compared to traditional digital systems.
The co-design approach presented empowers low-precision analog devices to perform high-precision computing within a programmable platform. This demonstration underscores the transformative potential of analog computing, transcending historical limitations and ushering in a new era of precision and efficiency.
Grain Analysis of NCM Cathode Materials by ASTAR Technique and Its Effect on Battery Performance
Authors: Jung Yongjo , Hong Kijoo , Kim Juseong , Lee Sunhwa , Nam Sangcheol 
Published: August 2024

Lithium-ion batteries (LIBs) are one of the most promising energy storage systems for portable electronic devices, electric vehicles, and renewable energy systems. Among the various cathode materials for LIBs, nickel cobalt manganese (NCM) oxide has attracted considerable attention due to its high specific capacity, good cycling stability, and appropriate cost for commercialization. However, Ni-rich NCM (Ni >80%) showed poor cyclability and huge gas evolution because of surface instability.
Single crystal NCM has been suggested as a solution to these issues due to its excellent properties. However, it is difficult to quantify the degree of single crystallinity because it is so far subjective. In this study, we employed ASTAR technique (transmission electron microscopy combined with electron backscatter diffraction) to investigate the microstructural features of NCM cathode materials. Our ASTAR analysis showed that NCM cathode materials consist of complex grain and grain boundary structures with varying orientations and sizes. By analyzing the grain size and its morphology, we were able to define the single crystallinity of NCM cathode materials, including the poly NCM and single crystal NCM particles.
Furthermore, we found that the grain size and its distribution significantly affects the battery performance and lifespan of NCM cathode materials. Specifically, the poly NCM particles exhibited a larger grain boundary and surface area compared to the single crystal NCM particles. The poly NCM particles also showed a faster DC-IR increase and a shorter lifespan than the single crystal NCM particles, indicating that the grain size has a critical influence on the battery performance and lifespan of NCM cathode materials.
Our results provide insights into the design and optimization of NCM cathode materials for next-generation LIBs. By controlling the grain size and its distribution of NCM cathode materials, it is possible to enhance the battery performance and lifespan. Therefore, our study highlights the importance of understanding the microstructural features of NCM cathode materials for developing high-performance and stable LIBs.
Carbon Quantum Dots with Highly Efficient Bandgap Emission for Electroluminescent Light-Emitting Diodes
Authors: Fan Louzhen , Yuan Ting 
Published: August 2024

Carbon quantum dots (CQDs) feature bright and tunable photoluminescence, solution processability, and low toxicity, showing great potential in optoelectronics. The multicolor fluorescent CQDs were first fabricated as active layers in our lab, and then the high-performance electroluminescent warm white light-emitting diodes (LEDs) were obtained with the synthesized bright red CQDs. More significantly, through designing the triangular structure of the carbon core, fluorescent CQDs first achieved the narrow-bandwidth (∼30 nm) electroluminescent LEDs with appreciable stability, high color purity, and high luminescence performance. These results lay the foundation for the development of next-generation high performance displays based on CQDs. Here, we will report the large-scale synthesis of CQDs with near-unity photoluminescence quantum yield and the synthesis of red (625 nm) phosphorescent carbon quantum dot organic frameworks (CDOFs) with a quantum yield of up to 42.3% and realization of high-efficiency red phosphorescent electroluminescent LEDs. The LEDs based on the CDOFs exhibited a red emission with a maximum luminance of 1818 cd m−2 and an EQE of 5.6%. This work explores the possibility of a new perspective for developing high-performance CQD-based electroluminescent LEDs.
References

Yuxin Shi, Louzhen Fan, et al., Red Phosphorescent Carbon Quantum Dot Organic Framework-Based Electroluminescent Light-Emitting Diodes Exceeding 5% External Quantum Efficiency, Am. Chem. Soc. 2021, 143, 45, 18941–18951

Ting Yuan, Louzhen Fan, et al., Carbon Quantum Dots with Near-Unity Quantum Yield Bandgap Emission for Electroluminescent Light-Emitting Diodes, Angew. Chem. Int. Ed. 2023, e202218568.

Fanglong Yuan，Louzhen Fan, et al., Engineering triangular carbon quantum dots with unprecedented narrow bandwidth emission for multicolored LEDs, Nat. Commun., 2018, 9, 2249.

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Nature-Derived Sulfur Carbons for Highly-Efficient Room Temperature Sodium-Sulfur Energy Storage
Authors: Senokos Evgeny 
Published: August 2024

In recent years, a growing interest in “beyond-Li-ion“ batteries has caused a speedy development of alternative battery technologies based on other alkali metals. Room temperature sodium sulfur (RT Na-S) batteries are potential candidate for sustainable large-scale energy storage systems. They offer low cost, nontoxicity and natural abundance of both cathode and anode materials combined with high theoretical energy density. However, rapid capacity fading related to the irreversible shuttling of soluble polysulfides, poor reaction kinetics and low sulfur utilisation in the cathode materials significantly limit their practical application.
In this work, a microporous sulfur-carbon complex is produced from sustainable natural precursors in a one-pot synthesis via stepwise thermally-induced inverse vulcanisation and condensation. The material exhibits a unique structure, with sulfur chains covalently anchored to the conductive carbon matrix and physically confined in ultra-micropores. An increase in sulfur content in the sulfur-copolymer alters the morphology and chemical composition of the final sulfur-carbon material, enhancing the amount of long-chain sulfur. The combination of optimal microstructure, good electrical conductivity and high content of electrochemically active sulfur translates to an unprecedented ~99% utilisation of sulfur and the highest reported capacity for a room temperature Na-S cathode, along with high rate capability, coulombic efficiency and long-term stability. This study offers an innovative approach towards the understanding of the key chemico-physical properties of the sulfur-carbon composite materials for the development of high-performance cathodes in RT Na-S batteries with an atom-efficient utilisation of sulfur.
(Invited) Quantitative in Vitro/In Vivo Fluorescence Bioimaging with Graphene Quantum Dots
Authors: Naumov Anton V. 
Published: August 2024

Graphene Quantum Dots (GQDs) are novel carbon nanomaterials consisting of few layers of partially functionalized graphitic carbon. Their nanometer-scale size together with functional groups render GQDs more water soluble and biocompatible than many other nanocarbon constructs. Like many nanocarbons, GQDs possess structure-dependent optical properties, exhibiting confinement-defined fluorescence in the visible and defect-originated emission in the near-infrared (NIR). These properties give GQDs a certain advantage for applications in therapeutic tracking, imaging, analyte detection and targeted drug/gene delivery. In addition to tracing the location of therapeutic or analyte, GOD fluorescence allows for several modes of quantitative assessment within these applications. In vitro it is utilized to evaluate relative amounts of therapeutics or analytes present within the cells at a certain time period. In vivo NIR emission of the GQDs-based sensors implanted under the skin can help detect trace quantities of analyte in the body, while their NIR fluorescence in animal organs can quantify relative therapeutic uptake over time.
The present work introduces novel studies and analytical tools exploring and enhancing such imaging modalities. Although GQD in vitro fluorescence microscopy imaging is often used to quantitate their (and payload) uptake and excretion, this method suffers from multiple discrepancies including the analysis of dead cells, cellular debris and non-internalized nanomaterials, and can be also time and resource-consuming. Our work aiming to circumvent these issues utilizes Artificial Intelligence (AI) approach to provide more accurate quantification of the uptake/excretion of the GQDs and their payload. In this application the AI algorithms developed in house do not only optimize the imaging, but also provide automated image analysis streamlining the assessment of a variety of GQD biomedical applications including therapeutic delivery and targeting. In vivo quantitative animal imaging with several different types of GQDs, from pristine to doped with rare earth metals for NIR fluorescence enhancement, is performed to evaluate GQD organ accumulation over time. Defect or dopant-originated NIR GQD fluorescence in the range of 900 – 1060 nm due to its high penetration depth can be observed from the organs of sedated live mice and utilized for GQD uptake tracking. NIR imaging of the excised organs allows for quantitative biodistribution assessment with further microscopic confirmation of the GQD content in organ tissue slices. Quantitative optical imaging and analysis presented in this work for GQDs can aid the further advancement of these novel nanomaterials in therapeutic delivery and analyte detection applications in vitro and in vivo.
(Invited) Carbon Nanodots for Improved Plant Genetic Engineering
Authors: Galeana Jesus , Demirer Gozde S 
Published: August 2024

Anthropogenic climate change has made the need for more nutritious and stress-tolerant plants indisputable for providing food security. Climate change has decreased the global agricultural productivity by 21% since 1961, and will continue to drop crop yields by 7.4% for every degree-Celsius increase in temperature. CRISPR genetic engineering can enable previously inaccessible crop tolerances to meet the demand for nutritionally-balanced and high-yielding crops. However, plant biomolecule delivery and transformation are two important bottlenecks that prevent plant genetic engineering from reaching its full potential.
Nanomaterials have already shown promise to deliver genetic cargoes into plant somatic cells for transient expression of proteins1. For most applications in agriculture, however, biomolecules need to be delivered to cells that can give rise to next generation of edited plants, such as germ or stem cells. These cell types are extremely challenging to penetrate and deliver cargoes using traditional approaches, hence forcing researchers to use undifferentiated tissues to transform and go through an arduous regeneration process in tissue culture. This time consuming, inefficient, and highly species dependent approach has been a critical obstacle in plant biology and bioengineering.
We have synthesized small (~3 nm) and positively charged (+35 mV) carbon nanodots (CNDs) from glycerol and polyethyleneimine (PEI) using the microwave method. These CNDs showed high entry efficiency into plant stem cells and ability to deliver DNA cargoes into a model plant Nicotiana benthamiana without affecting stem cell viability and differentiation capability. This is a first-time demonstration of nanoparticle uptake by plant stem cells and cargo expression in these cell types. Once we perform CRISPR gene editing in these stem cells, the edited germ cells and seeds will develop automatically from the stem cells, facilitating the creation of edited and improved new plant varieties.
References:

Demirer, Gozde S., et al. "High aspect ratio nanomaterials enable delivery of functional genetic material without DNA integration in mature plants." Nature nanotechnology 14.5 (2019): 456-464.
(Invited) Low-Frequency Noise in Flexible Carbon-Nanotube Analog Circuits
Authors: Ohno Yutaka 
Published: August 2024

Since flexible devices can come into close contact with the human body, they are suitable for wearable sensor applications for long-term and non-invasive monitoring of biological and physiological signals in various fields such as medical/health care and sports, among others. In order to achieve a fully flexible sensor system, various electronic circuits need to be integrated on a flexible film, including the analog frontend (AFE) and radio-frequency (RF) frontend, as well as the sensors. Recently, we have demonstrated low-voltage CNT-based analog/digital mixed-signal circuits with excellent stability and robustness against variability, including the AFE. One remaining issue with CNT-based analog circuits is low-frequency noise, which directly impacts the sensitivity of the sensor system within the frequency range of physiological signals such as ECG and EEG.
Here, we study the low-frequency noise of flexible carbon nanotube thin-film transistors and their influence on analog circuits. The low-frequency noise exhibits a typical 1/f spectrum. Inserting an interface layer between the CNT channel layer and gate insulator layer reduces Hooge's parameter of the 1/f noise. The results indicate that maintaining distance from the channel to traps in the gate oxide is important for reducing low-frequency noise.
Single-Walled Carbon Nanotube Based Field-Effect Transistors Functionalized with Odorant Receptors for Biosensing Applications
Authors: Icin Izthak , Vainer Yuri , Avnon Asaf , Gal-Oz Reshef , Bohbot Jonathan , Eini Eran 
Published: August 2024

Bioelectronic detection of volatile organic compounds (VOC) has been demonstrated in a wide range of applications, with early reports focusing on environmental exogenous VOCs due to their adverse effects on human health; bacterial VOC signatures used as disease biomarkers, etc. Carbon nanotube field-effect transistors (CNT-FETs) are considered promising devices for bioelectronic detection due to their sensitivity, robustness and compatibility with microelectronic fabrication technologies. However, implementation of CNT-FETs still faces many challenges. Current VOCs detection approaches rely on separation techniques coupled with mass spectrometry, necessitating expensive equipment, labor-intensive preparation steps and trained personnel, and are not suitable for field use. Overcoming the challenges in the development of bioelectronic CNT-FET sensors holds great promise for high-throughput screening of VOCs.
The natural insect odorant receptors (ORs) are highly attractive probes, potentially allowing ultrahigh specificity for VOC biosensing. Insect ORs exhibit remarkable sensitivities and the ability to selectively detect a vast number of VOCs. We have recently developed OR-functionalized carbon nanotube field-effect transistor (FET) devices. These FET devices comprise an isolated single-walled carbon nanotube (SWCNT), serving as the conducting channel material, functionalized with multiple insect ORs. These hybrid devices are capable of transducing ligand binding into an electronic current, without amplification. The insect OR-functionalized CNT FET were applied for the detection of several markers of environmental and clinical importance including Indole, Skatole, Octen-3-ol and Nonyl-aldehyde.
We have developed a bioelectronic assay platform that contains a chip with 61 ORs-functionalized CNT-FET devices. Our unique functionalization method is based on directing the attachment of a native ORs-containing nanovesicles (which we have exogenously expressed and functionally characterized) to a generated CNT-FET point defect. Target binding-induced ionic current and conformational changes of ORs affect an electric field that modulates the device conductance.