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At least 667 records · Page 37

Assembly of small silica nanoparticles using lipid-tethered DNA ‘bonds’

Single-stranded DNA molecules modified with cholesterol functional groups are physically tethered to silica nanoparticles (diameter 25 nm) that are encapsulated in a lipid bilayer. Such tethering increases the azimuthal mobility of the DNA molecules across the nanoparticle surface and enables nonspecific bonding, eliminating the need for specialized surface chemistries (such as silane or thiol ligands). To induce assembly, double-stranded DNA ‘bridge’ molecules are then added with complementary nucleotides to the DNA ‘anchor’ molecules that are physically tethered to the lipids on the surface of the particles. Assembly is observed to occur at room temperature and without the need for temperature annealing. Using automated liquid handling tools, assemblies are created in high throughput and rapidly characterized using SAXS. It is determined that the relative concentration of DNA-to-silica and the ionic strength of the solution are important parameters that affect the resulting assembly. Analysis of SAXS data is performed using coarse-grained particle dynamics simulations. The results support the spontaneous formation of semi-crystalline particle assemblies by particle condensation, where the interparticle distance is tuned by the sequence of the DNA ‘bridge’ used to link the particles. Crystallinity analysis performed on the resulting simulations, optimized to match SAXS observations, suggest that particle clusters display increased crystallinity in the center of the clusters, but their maximum size remains relatively small (sub-micron) before settling occurs, which limits the extent of crystallization.

Chiang, Huat Thart [Univ. of Washington, Seattle, ↗

2023 American Society for Mass Spectrometry (ASMS) 71st Annual Conference on Mass Spectrometry and Allied Topics

Introduction (120 words max) Understanding metal-cluster chemistry occuring at solvent boundaries in the aqueous and organic phases has applications in environments from cellular processes to nuclear fuel reprocessing. Transport of metal ions at the boundaries from aqueous to organic phases involves forming a metal-ligand complex, and wherever the initial metal coordination environment is significantly different from the final one, the metal transitions through a series of transient species in passing from one phase to another. Here an investigation of the role of coordination in the chemistry of the transient species using gas-phase measurements that are free of solvent effects to better understand the binding of complexes of metals with triphenylphosphine chalcogenide ligands, examining metal-ligand homo- and hetero-dimers to better understand transient species. Methods (120 word max) Mass spectrometry and collision induced dissociation (CID) experiments were performed with a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer (QTOF) and Bruker amaZon speed ETD (ion trap). High resolution/high mass accuracy spectra were generated using the QTOF. External calibration was performed with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Both mass spectrometers were equipped with either the electrospray ionization source or nanospray sources. Metal samples were prepared between 40 – 60 uM of the metal-ligand complex in 25% water and 75% acetonitrile. Metal-ion clusters were isolated and subjected to collision induced dissociation. Density functional theory calculations were performed. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters with triphenylphosphine chalcogenide ligands were observed for group I metals with triphenylphosphine chalcogenide samples in the mass spectrum upon electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation spectra were acquired. We observed clusters of group I metal with triphenylphosphine oxide, triphenyl phosphine sulfide, and triphenylphosphine selenide, with homodimers and heterodimer formation. In samples where the ligands were mixed, we observed mixed sodium ligand clusters at varying amounts. These mixed ligand clusters were fragmented. Metal clusters of mixed ligand dimers containing triphenylphosphine oxide showed preferential loss of the other ligand, either triphenylphosphine sulfide or triphenyl selenide. In samples with mixed triphenylphosphine sulfide and triphenylphosphine selenium ligands, sodium bound similarly between the ligands, and losses were more evenly split, showing loss ratio upon CID with losses of triphenylphosphine sulfide:triphenylphosphine selenide 43:57 ratio observed on CID. These results suggest that the oxide binds significantly more strongly than either the selenium or sulfur triphenylphosphine ligand, and the sulfur and selenium ligands are more evenly bound. Calculations were performed using density functional theory to calculate likely structures and bond energies between the group I metal and the ligands. Novel Aspect Novel analysis of sodium bound dimers with chalcogenide triphenylphosphine ligands were investigated using mass spectrometry and theoretical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Significant Roles of Surface Hydrides in Enhancing the Performance of Cu/BaTiO 2.8 H 0.2 Catalyst for CO 2 Hydrogenation to Methanol

Abstract Tuning the anionic site of catalyst supports can impact reaction pathways by creating active sites on the support or influencing metal‐support interactions when using supported metal nanoparticles. This study focuses on CO 2 hydrogenation over supported Cu nanoparticles, revealing a 3‐fold increase in methanol yield when replacing oxygen anions with hydrides in the perovskite support (Cu/BaTiO 2.8 H 0.2 yields ~146 mg/h/gCu vs. Cu/BaTiO 3 yields ~50 mg/h/gCu). The contrast suggests that significant roles are played by the support hydrides in the reaction. Temperature programmed reaction and isotopic labelling studies indicate that BaTiO 2.8 H 0.2 surface hydride species follow a Mars van Krevelen mechanism in CO 2 hydrogenation, promoting methanol production. High‐pressure steady‐state isotopic transient kinetic analysis (SSITKA) studies suggest that Cu/BaTiO 2.8 H 0.2 possesses both a higher density and more active and selective sites for methanol production compared to Cu/BaTiO 3 . An operando high‐pressure diffuse reflectance infrared spectroscopy (DRIFTS)‐SSITKA study shows that formate species are the major surface intermediates over both catalysts, and the subsequent hydrogenation steps of formate are likely rate‐limiting. However, the catalytic reactivity of Cu/BaTiO 2.8 H 0.2 towards the formate species is much higher than Cu/BaTiO 3 , likely due to the altered electronic structure of interface Cu sites by the hydrides in the support as validated by density functional theory (DFT) calculations.

He, Yang↗

Tailoring the Selective Oxidation of Hydroxyl-Containing Compounds via Precisely Tuning the Hydrogen-Bond Strength of Catalyst H-Bond Acceptors

The unique performance of the enzyme is mainly achieved via weak interactions between the “outer coordination sphere” and the substrate. Inspired by this process, we developed 3D encapsulated-structure catalysts with hydrogen-bond engineering on the shell, which mimics the “outer coordination sphere” of an enzyme. Various hydrogen bond acceptors (C=O, S=O, and N–O groups) are imparted in the shell. Concentration-dependent 1H NMR, inverse-phase gas Chromatography (IGC) measurements, and DFT calculations underscore that the hydrogen bond strength between the acceptor groups and alcohol follows the order of C=O < S=O < N–O. The hydroxyl compound oxidation rate vs the hydrogen bond strength follows a volcano behavior, reminiscent of Sabatier’s principle. The performance variation among catalysts is attributed to the adsorption strength of the substrate. The proposed bioinspired design principle expands the scope of encapsulated catalysts, enabling fine regulation of catalytic activity through precise microenvironment control via weak interactions with substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning Dzyaloshinskii-Moriya interactions in magnetic bilayers with a ferroelectric substrate

Our group performed systematic first-principles calculations to explore the possibility of manipulating Dzyaloshinskii-Moriya interactions (DMIs) in heavy metal/ferromagnetic metal bilayers with ferroelectric (FE) polarization of a PbTiO 3 (PTO) substrate. Significantly, both the sign and magnitude of the DMI can be tailored by the FE polarization reversal in PTO. Moreover, the DMIs of Ir/Co/PTO and Ir/Fe/PTO can achieve large values (|d| > 10 meV) under the influence of an upward electric polarization of PTO. Our findings provided useful strategies for enhancing and tailoring DMIs in complex heterostructures and paved the way for the development of DMI-based devices with ultralow power consumption.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Low SWaP Semiconductor Laser Transmitter Modules For ASCENDS Mission Applications

The National Research Council's (NRC) Decadal Survey (DS) of Earth Science and Applications from Space has identified the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) as an important atmospheric science mission. NASA Langley Research Center, working with its partners, is developing fiber laser architecture based intensity modulated CW laser absorption spectrometer for measuring XCO2 in the 1571 nm spectral band. In support of this measurement, remote sensing of O2 in the 1260 nm spectral band for surface pressure measurements is also being developed. In this paper, we will present recent progress made in the development of advanced transmitter modules for CO2 and O2 sensing. Advanced DFB seed laser modules incorporating low-noise variable laser bias current supply and low-noise variable temperature control circuit have been developed. The 1571 nm modules operate at >80 mW and could be tuned continuously over the wavelength range of 1569-1574nm at a rate of 2 pm/mV. Fine tuning was demonstrated by adjusting the laser drive at a rate of 0.7 pm/mV. Heterodyne linewidth measurements have been performed showing linewidth ~200 kHz and frequency jitter ~75 MHz. In the case of 1260 nm DFB laser modules, we have shown continuous tuning over a range of 1261.4 - 1262.6 nm by changing chip operating temperature and 1261.0 - 1262.0 nm by changing the laser diode drive level. In addition, we have created a new laser package configuration which has been shown to improve the TEC coefficient of performance by a factor of 5 and improved the overall efficiency of the laser module by a factor of 2.

Prasad, Narasimha S.↗

Tuning Phase Lock Loop Controller of Grid Following Inverters by Reinforcement Learning to Support Networked Microgrid Operations

The dynamic operation of networked microgrids leads to varying topological configurations and generator commitments and dispatches. These variations correspond to systems with different electrical characteristics. The fixed control gains of high-speed power electronic devices may result in undesirable system performance when the electrical characteristics change significantly. As such, it is necessary to tune the control gains of power electronics devices to adapt to the changing system characteristics. This paper uses observer-based reinforcement learning to automatically tune the proportional-integral (PI) gains of phase lock loop (PLL) controller of grid-following (GFL) inverters to adapt to the changing system strengths, that would be seen in networked microgrid operations. Simulation results using an operational electric distribution system, modeled as networked microgrids, are presented to demonstrate the need and effectiveness of the proposed adaptive controls.

networked microgrids, reinforcement learning, grid↗

Mass Spectrometer Observing Lunar Operations (MSoLo)

Introduction: In 2019, the National Aeronautics and Space Administration (NASA) announced that it would seek to have humans return to the moon by 2024 in the hopes of establishing a more sustainable lunar presence by 2028. This goal comes with many challenges, one of upmost importance will be to utilize resources that can be found on the moon. Water, which has been identified in the lunar Polar Regions, will be a key resource for in-situ resource utilization (ISRU), as it is capable of being processed for vehicular fuel, as well as life support systems materials such as oxygen. Upcoming Commercial Lunar Payload Services (CLPS) missions will be critical for these resource assessments. Methods: A modified commercial off-the-shelf (COTS) mass spectrometer developed at Kennedy Space Center known as MSolo, consisting of a quadrupole mass filter and space rated electronics undergoes testing and modifications in order to study operational parameters to unconventional approaches needed in flight situations. In general, MSolo operates in the 0-100 m/z range with the ability to detect with a faraday cup (FC) or an electron multiplier (EM) for enhanced detection. A crossbeam (XB) ionization source is used. Preliminary Data: Prior to construction, little information was available on how the MSolo system would perform at lunar like environments, factors such as temperatures (possible fluctuations from 70 to -45 °C), vibrations from launch and their side effects, the general ability to operate while the entire system (hardware and electronic components) were in a vacuum environment, were factors that while know to flight instruments, were something new to a modified COTS system. As components start to warm up, temperature becomes a key factor (ie. heat can no longer escape the electronics as no atmosphere is present), therefore it becomes crucial to find new ways to maintain stable signals and keep the instrument tuned. Calibration itself becomes an important parameter that needs to be performed while maintaining all flight like characteristics. Even the structure itself of MSolo’s sensor needed to be changed to survive the verification parameters needed to be approved for flight. Most important, all the modifications made to the COTS system have to keep the instrument working at the same specifications of the standard commercial systems. Novel Aspect: Results gathered provide key parameters that will assist to the unconventional mass spectrometry approaches of the upcoming CLPS missions to which MSolo has been selected to.

MSolo↗

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Abstract Although beam emittance is critical for the performance of high-brightness accelerators, optimization is often time limited as emittance calculations, commonly done via quadrupole scans, are typically slow. Such calculations are a type of multipoint query , i.e. each query requires multiple secondary measurements. Traditional black-box optimizers such as Bayesian optimization are slow and inefficient when dealing with such objectives as they must acquire the full series of measurements, but return only the emittance, with each query. We propose a new information-theoretic algorithm, Multipoint-BAX , for black-box optimization on multipoint queries, which queries and models individual beam-size measurements using techniques from Bayesian Algorithm Execution (BAX). Our method avoids the slow multipoint query on the accelerator by acquiring points through a virtual objective , i.e. calculating the emittance objective from a fast learned model rather than directly from the accelerator. We use Multipoint-BAX to minimize emittance at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Tests II (FACET-II). In simulation, our method is 20× faster and more robust to noise compared to existing methods. In live tests, it matched the hand-tuned emittance at FACET-II and achieved a 24% lower emittance than hand-tuning at LCLS. Our method represents a conceptual shift for optimizing multipoint queries, and we anticipate that it can be readily adapted to similar problems in particle accelerators and other scientific instruments.

43 PARTICLE ACCELERATORS↗

Tuning the Kinetics of Zinc-Ion Insertion/Extraction in V 2 O 5 by In Situ Polyaniline Intercalation Enables Improved Aqueous Zinc-Ion Storage Performance

Rechargeable zinc-ion batteries (ZIBs) are emerging as a promising alternative for Li-ion batteries. However, the developed cathodes suffer from sluggish Zn 2+ diffusion kinetics, leading to poor rate capability and inadequate cycle life. Herein, an in situ polyaniline (PANI) intercalation strategy is developed to facilitate the Zn 2+ (de)intercalation kinetics in V 2 O 5 . In this way, a remarkably enlarged interlayer distance (13.90 Å) can be constructed alternatively between the V-O layers, offering expediting channels for facile Zn 2+ diffusion. Importantly, the electrostatic interactions between the Zn 2+ and the host O 2- , which is another key factor in hindering the Zn 2+ diffusion kinetics, can be effectively blocked by the unique π-conjugated structure of PANI. As a result, the PANI-intercalated V 2 O 5 exhibits a stable and highly reversible electrochemical reaction during repetitive Zn 2+ insertion and extraction, as demonstrated by in situ synchrotron X-ray diffraction and Raman studies. Further first-principles calculations clearly reveal a remarkably lowered binding energy between Zn 2+ and host O 2- , which explains the favorable kinetics in PANI-intercalated V 2 O 5 . Benefitting from the above, the overall electrochemical performance of PANI-intercalated V 2 O 5 electrode is remarkable improved, exhibiting excellent high rate capability of 197.1 mAh g -1 at current density of 20 A g -1 with capacity retention of 97.6% over 2000 cycles.

36 MATERIALS SCIENCE↗

Opening the Bandgap of Metallic Half-Heuslers via the Introduction of d–d Orbital Interactions

Half-Heusler compounds with semiconducting behavior have been developed as high-performance thermoelectric materials for power generation. Many half-Heusler compounds also exhibit metallic behavior without a bandgap and thus inferior thermoelectric performance. Here, taking metallic half-Heusler MgNiSb as an example, a bandgap opening strategy is proposed by introducing the d–d orbital interactions, which enables the opening of the bandgap and the improvement of the thermoelectric performance. The width of the bandgap can be engineered by tuning the strength of the d–d orbital interactions. The conduction type and the carrier density can also be modulated in the Mg 1- x Ti x NiSb system. Both improved n-type and p-type thermoelectric properties are realized, which are much higher than that of the metallic MgNiSb. The proposed bandgap opening strategy can be employed to design and develop new half-Heusler semiconductors for functional and energy applications.

36 MATERIALS SCIENCE↗

In Situ X-Ray Absorption Spectroscopy Disentangles the Roles of Copper and Silver in a Bimetallic Catalyst for the Oxygen Reduction Reaction

Silver-based bimetallic catalysts for the oxygen reduction reaction (ORR) are promising for a wide variety of renewable energy technologies, including alkaline fuel cells and metal-air batteries. The activity of bimetallic catalysts can sometimes surpass that of either constituent element, but the origin of the enhanced performance is still debated. At a given active site, two complementary mechanisms are proposed to explain the performance improvements: the binding energy of intermediate adsorbates can be tuned by direct electronic contributions from the alloying element or by changes in the bond lengths from lattice distortion. To distinguish between these effects and elucidate the respective roles of each element in the bimetallic, it is critical to study catalysts at the molecular scale under reaction conditions. In this work, we use in situ X-ray absorption spectroscopy (XAS) alongside density functional theory (DFT) to show that direct electronic rather than geometric effects are the primary cause of improved ORR activity in a bimetallic CuAg catalyst. Our results indicate that the local bonding as well as the electronic structure of Ag are virtually unchanged by the presence of Cu, whereas the electronic states of Cu in CuAg are significantly altered. DFT calculations support these experimental findings. We show strong evidence that the activity of the bimetallic CuAg catalyst exceeds the sum of the activities of Cu and Ag, not by incremental improvement of the active Ag sites, but by creating highly active Cu-centered catalytic sites. The insight that the main role of Ag in bimetallic catalysts may be to promote its fellow element through local electronic interactions provides a new design principle for engineering the next generation of bimetallic catalysts for the ORR and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Descriptors for Hydrogen Evolution on Single Atom Catalysts in Nitrogen-Doped Graphene

Single-atom catalysts (SACs) are a new research frontier in electrocatalysis such as in the hydrogen evolution reaction (HER). Recent theoretical and experimental studies have demonstrated that certain M–N–C (metal–nitrogen–carbon) based SACs exhibit excellent performance for HER. Here we report a new approach to tune HER activity for SACs by changing the size and dimensionality of the carbon substrate while maintaining the same coordination environment. In this work, we screen the 3d, 4d, and 5d transition metal SACs in N-doped 2D graphene and nanographenes of several sizes for HER using first-principles density functional theory (DFT). Nanographenes containing V, Rh, and Ir are predicted to have significantly enhanced HER activity compared to their 2D graphene counterparts. We turn to machine learning to accurately predict the free energy of hydrogen adsorption (ΔGH) based on various descriptors and compressed sensing to identify key descriptors for activity, which can be used to further screen for additional candidates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymer Hole Transport Materials for Perovskite Solar Cells via Buchwald–Hartwig Amination

The development of low-cost materials for charge-selective contacts that provide good energetic alignment with perovskite active layers, favorable thermal properties, and lead to efficient photoconversion is becoming an increasingly important aspect of the perovskite solar cell (PSC) field. Presented here is a series of polymers based on a one-pot polymerization of aryl dihalides with primary aryl amines to produce solution-processable polymers in high yield, with simple purification, and promising properties for high performing P-I-N PSC devices. How these properties can be tuned by careful selection of the reactant chemical moieties is discussed. Through this strategy, a wide range of relevant properties such as glass transition temperature, highest occupied molecular orbital tuning, and polydispersity are explored. When implemented into devices using a triple-cation FAMACs perovskite active layer, the hole transport material series shows average power conversion efficiencies (PCE) in excess of 17%, which is comparable to controls using state-of-the-art poly(triarylamine). How different synthetic parameters such as the reaction time and purification protocol impact device performance is also investigated.

14 SOLAR ENERGY↗

Atomically dispersed Pb ionic sites in PbCdSe quantum dot gels enhance room-temperature NO2 sensing

Abstract Atmospheric NO 2 is of great concern due to its adverse effects on human health and the environment, motivating research on NO 2 detection and remediation. Existing low-cost room-temperature NO 2 sensors often suffer from low sensitivity at the ppb level or long recovery times, reflecting the trade-off between sensor response and recovery time. Here, we report an atomically dispersed metal ion strategy to address it. We discover that bimetallic PbCdSe quantum dot (QD) gels containing atomically dispersed Pb ionic sites achieve the optimal combination of strong sensor response and fast recovery, leading to a high-performance room-temperature p-type semiconductor NO 2 sensor as characterized by a combination of ultra–low limit of detection, high sensitivity and stability, fast response and recovery. With the help of theoretical calculations, we reveal the high performance of the PbCdSe QD gel arises from the unique tuning effects of Pb ionic sites on NO 2 binding at their neighboring Cd sites.

36 MATERIALS SCIENCE↗

Molecular surface programming of rectifying junctions between InAs colloidal quantum dot solids

Heavy-metal-free III–V colloidal quantum dots (CQDs) show promise in optoelectronics: Recent advancements in the synthesis of large-diameter indium arsenide (InAs) CQDs provide access to short-wave infrared (IR) wavelengths for three-dimensional ranging and imaging. In early studies, however, we were unable to achieve a rectifying photodiode using CQDs and molybdenum oxide/polymer hole transport layers, as the shallow valence bandedge (5.0 eV) was misaligned with the ionization potentials of the widely used transport layers. This occurred when increasing CQD diameter to decrease the bandgap below 1.1 eV. Here, we develop a rectifying junction among InAs CQD layers, where we use molecular surface modifiers to tune the energy levels of InAs CQDs electrostatically. Previously developed bifunctional dithiol ligands, established for II-VI and IV-VI CQDs, exhibit slow reaction kinetics with III-V surfaces, causing the exchange to fail. Here, we study carboxylate and thiolate binding groups, united with electron-donating free end groups, that shift upward the valence bandedge of InAs CQDs, producing valence band energies as shallow as 4.8 eV. Photophysical studies combined with density functional theory show that carboxylate-based passivants participate in strong bidentate bridging with both In and As on the CQD surface. The tuned CQD layer incorporated into a photodiode structure achieves improved performance with EQE (external quantum efficiency) of 35% (>1 μm) and dark current density < 400 nA cm -2 , a >25% increase in EQE and >90% reduced dark current density compared to the reference device. This work represents an advance over previous III-V CQD short-wavelength IR photodetectors (EQE < 5%, dark current > 10,000 nA cm -2 ).

36 MATERIALS SCIENCE↗

Transfer Learning Trained LSTM Models for Household Load Profile Forecasting

Grid edge renewable energy resources, such as rooftop solar photovoltaics, closely interact with consumer load profiles. Therefore, forecasting future electricity demand, ideally at the individual household level, is indispensable. In this paper, we present a transfer learning enhanced household load profile forecasting method. First, we tune a long short-term memory forecasting model to perform day-ahead prediction of household electricity load profiles. Then we improve these individualized models using transfer learning, and we use k-means clustering to create optimal source data sets. We find average improvements of 4.38% (largest improvement of 10.71%) when the entire data set was used to train the source model and 2.45% (largest improvement of 11.57%) in the mean absolute error when households were first clustered and used to train separate source models for each cluster. We find that transfer learning with clustered data can effectively boost the forecasting performance of the LSTM models. We use realistic household power measurements for 148 real residential households in Austin, Texas.

deep learning↗

Thermal Management for FPGA Nodes in HPC Systems

The integration of FPGAs into large-scale computing systems is gaining attention. In these systems, real-time data handling for networking, tasks for scientific computing, and machine learning can be executed with customized datapaths on reconfigurable fabric within heterogeneous compute nodes. At the same time, thermal management, particularly battling the cooling cost and guaranteeing the reliability, is a continuing concern. The introduction of new heterogeneous components into HPC nodes only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is less explored. Here, we first show that the thermal behaviors of different FPGAs of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning–based model to capture the thermal behavior of each individual FPGA in the cluster. We then propose two thermal management strategies guided by our thermal model. First, we mitigate thermal variation and hotspots across the cluster by proactive thermal-aware task placement. Under the tested system and benchmarks, we achieve up to 26.4° C and on average 13.3° C system temperature reduction with no performance penalty. Second, we utilize this thermal model to guide HLS parameter tuning at the task design stage to achieve improved thermal response after deployment.

97 MATHEMATICS AND COMPUTING↗