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At least 1,639 records · Page 91

Strontium isotope investigation of ungulate movement patterns on the Pleistocene Paleo-Agulhas Plain of the Greater Cape Floristic Region, South Africa

Middle Stone Age sites located within the Greater Cape Floristic Region on the South African southern coast have material culture with early evidence for key modern human behaviors such as projectile weaponry, large animal hunting, and symbolic behavior. In order to interpret how and why these changes evolved, it is necessary to understand their ecological context as it has direct relevance to foraging behavior. During periods of lowered sea level, a largely flat and vast expanse of land existed south of the modern coastline, but it is now submerged by higher sea levels. This exposed area, the Paleo-Agulhas Plain, likely created an ecological context unlike anything in the region today, as evidenced by fossil assemblages dominated by migratory ungulates. One hypothesis is that the Paleo-Agulhas Plain supported a migration ecosystem of large grazers driven by summer rainfall, producing palatable forage during summer in the east, and winter rainfall, producing palatable forage during winter in the west. Furthermore, ungulates may have been moving from the coastal plain in the south to the interior north of the Cape Fold Mountains, as observed for elephants in historic times.

54 ENVIRONMENTAL SCIENCES↗

An isotopic test of the seasonal migration hypothesis for large grazing ungulates inhabiting the Palaeo-Agulhas Plain

The Greater Cape Floristic Region of South Africa was critical to the evolution of early modern humans ( Homo sapiens ) during the Pleistocene. The now submerged continental shelf formed its own ecosystem, the Palaeo-Agulhas Plain (PAP), where early humans lived and foraged. Grazing animals living on the plain might have migrated east and west tracking seasonally varying rains—a hypothesis tested here by examining δ 13 C and δ 18 O of serially-drilled teeth from seven ungulate genera: Alcelaphus , Connochaetes , Antidorcus , Redunca , Damaliscus , and Hippotragus . Modern observations and paleoecological reconstructions indicate that summer rainfall areas to the east have more C 4 grasses while the winter rainfall areas to the west have more C 3 grasses, and that summer and winter rains differ in δ 18 O. Thus, we analyze δ 13 C and δ 18 O preserved in herbivore teeth from the site of PP30 (a hyena den dating to ~151 ka) to infer diet and water source throughout tooth formation. On a generic level, we report none of the samples exhibit δ 13 C or δ 18 O values that differ significantly from a taxon that likely foraged locally through the year (Southern reedbuck, Redunca arundium ). Overall, results indicate that the PAP could support herbivore populations year-round without substantial migration, providing an ecosystem ideal for human inhabitants.

59 BASIC BIOLOGICAL SCIENCES↗

New understanding of rhizosphere processes enabled by advances in molecular and spatially resolved techniques

Understanding the role played by microorganisms within soil systems is challenged by the unique intersection of physics, chemistry, mineralogy and biology in fostering habitat for soil microbial communities. To address these challenges will require observations across multiple spatial and temporal scales to capture the dynamics and emergent behavior from complex and interdependent processes. The heterogeneity and complexity of the rhizosphere require advanced techniques that press the simultaneous frontiers of spatial resolution, analyte sensitivity and specificity, reproducibility, large dynamic range, and high throughput. Fortunately many exciting technical advancements are now available to inform and guide the development of new hypotheses. The aim of this Special issue is to provide a holistic view of the rhizosphere in the perspective of modern molecular biology methodologies that enabled a highly-focused, detailed view on the processes in the rhizosphere, including numerous, strong and complex interactions between plant roots, soil constituents and microorganisms. We discuss the current rhizosphere research challenges and knowledge gaps, as well as perspectives and approaches using newly available state-of-the-art toolboxes. These new approaches and methodologies allow the study of rhizosphere processes and properties, and rhizosphere as a central component of ecosystems and biogeochemical cycles.

Holistic view↗

Review of heat transfer enhancement techniques for single phase flows

The thermal energy exchange between a flowing fluid and its confining channel is a ubiquitous process in modern society. To enhance the fluid-to-wall or wall-to-fluid heat transfer, several techniques have been developed to maximize the contact area between the fluid and the inner wall and/or disrupt the flow to enhance circulation or induce turbulence. Deployment of channels having features capable of enhancing heat transfer enables the reduction of heat exchanger size while maintaining performance. Reduction in equipment size is critical due to the ability to minimize the required volume of costly working fluids and to mitigate potential safety concerns associated with total system fluid volume. Here, a comprehensive review of single-phase heat transfer enhancement techniques is presented. The article provides a thorough comparison by analyzing the heat transfer rate, pressure drop, and other operational aspects. Single-phase heat transfer enhancement methods are divided into active and passive techniques. Active methods such as electrohydrodynamic (EHD), magnetohydrodynamics (MHD), or mechanical motion require external power to create enhancement. Passive methods such as dimples, fins, or tape inserts do not require external input and rely only on surface modification. Although active methods are more expensive and difficult to implement compared to passive techniques, it enables active control of heat transfer augmentation. Finally, this review develops and summarizes key learning data for design optimization enabled by additive manufacturing and machine learning algorithms, helping to inform these next-generation heat exchanger design methodologies for a plethora of modern applications such as electrification of vehicles, computing, and classical industries.

42 ENGINEERING↗

An Open-Source Virtual Testbed for a Real Net-Zero Energy Community

Net zero energy communities (NZECs) are critical to ensure sustainability and resilience of modernized power systems. System modeling helps overcome technical challenges in designing and operating NZECs. In this paper, we present the modeling work based on a real NZEC. Two sets of models are developed: higher-fidelity physics-based models considering the interaction between subsystems of the studied NZEC and capturing fast-dynamics; and lower-fidelity data-driven models requiring less resource to establish and/or run. All models are validated against measurements from this real NZEC. In addition, we create a simulation framework which streamlines the processes for simulation and thus allows using developed models to form a virtual testbed. To demonstrate the usage of the virtual testbed, a case study is conducted where a building-to-grid integration control is evaluated via simulation. The evaluation results suggest that the tested control significantly smooths the power draw of the studied community and doesn’t sacrifice the thermal comfort to a great extent.

Huang, Sen↗

A Review of Flow Analysis Methods for Determination of Radionuclides in Nuclear Wastes and Nuclear Reactor Coolants

The safety and security nuclear power plant operations depends on the application of the most appropriate techniques and methods of chemical analysis, where modern flow analysis methods find increasing applications. Nevetheless, the current status of development of these methods is more limited than might be expected from their authentic advantages. The main aim of this contribution is to review automated flow analysis procedures developed with various detection methods for application in the nuclear energy industry. The flow analysis methods for determination of radionuclides that have been reported to date have been primarily focused mainly on environmental applications. The needs and benefits of the application of flow methods for the monitoring of nuclear wastes and for process analysis of the primary circuit coolants of light water nuclear reactors are discussed. Application of continuous flow methods (CFA) or injection methods (FIA, SIA) of flow analysis with radiometric detection shorterns the time of analysis and improves precision of determinations due to mechanization of time-consuming operations of sample processing. The use of mass spectrometry (MS) detection enables multicomponent analyses and determination of transuranic isotopes with much better limits of detection compared to radiometric detection.

radiochemical analysis, Sequential Injection and F↗

Waste picker livelihoods and inclusive neoliberal municipal solid waste management policies: The case of the La Chureca garbage dump site in Managua, Nicaragua

Highlights: • Landfill modernization project in Nicaragua yields unintended consequences. • Enclosure of garbage site displaces hundreds of impoverished waste pickers. • Persistent social marginalization contributes to environmental degradation. • Sustainable development must incorporate concerns of informal waste pickers. - Abstract: The modernization (i.e. mechanization, formalization, and capital intensification) and enclosure of municipal solid waste management (MSWM) systems threaten waste picker livelihoods. From 2009 to 2013, a major development project, embodying traditional neoliberal policies with inclusive social policies, transformed the Managua, Nicaragua, municipal solid waste site from an open-air dump where as many as 2,000 informal waste pickers toiled to a sanitary landfill. To investigate waste pickers’ social and economic condition, including labor characteristics, household income, and poverty incidence, after the project’s completion, 146 semi-structured survey questionnaires were administered to four communities adjacent to the landfill and 45 semi-structured interviews were completed with key stakeholders. Findings indicate that hundreds of waste pickers were displaced by the project, employment benefits from the project were unevenly distributed by neighborhood, and informal waste picking endures due to persistent impoverishment, thereby contributing to continued social and economic marginalization and environmental degradation. The findings highlight the limitations of inclusive neoliberal development efforts to transform MSWM in a low-income country.

54 ENVIRONMENTAL SCIENCES↗

Enhanced Collisional Losses from a Magnetic Mirror Using the Lenard-Bernstein Collision Operator

Collisions are crucial in governing particle and energy transport in plasmas confined in a magnetic mirror trap. Modern gyrokinetic codes model transport in magnetic mirrors, but some utilize approximate model collision operators. This study focuses on a Pastukhov-style method of images calculation of particle and energy confinement times using a Lenard-Bernstein model collision operator. Prior work on parallel particle and energy balances used a different Fokker-Planck plasma collision operator. The method must be extended in non-trivial ways to study the Lenard-Bernstein operator. To assess the effectiveness of our approach, we compare our results with a modern finite element solver. Our findings reveal that the particle confinement time scales like a exp( a 2 ) using the Lenard-Bernstein operator, in contrast to the more accurate scaling that the Coulomb collision operator would yield a 2 exp( a 2 ), where a 2 is approximately proportional to the ambipolar potential. We propose that codes solving for collisional losses in magnetic mirrors utilizing the Lenard-Bernstein or Dougherty collision operator scale their collision frequency of any electrostatically confined species. This study illuminates the collision operator’s intricate role in the Pastukhov-style method of images calculation of collisional confinement.

fusion plasma↗

A Roadmap for Edge Computing Enabled Automated Multidimensional Transmission Electron Microscopy

The advent of modern, high-speed electron detectors has made the collection of multidimensional hyperspectral transmission electron microscopy datasets, such as 4D-STEM, a routine. However, many microscopists find such experiments daunting since analysis, collection, long-term storage, and networking of such datasets remain challenging. Some common issues are their large and unwieldy size that often are several gigabytes, non-standardized data analysis routines, and a lack of clarity about the computing and network resources needed to utilize the electron microscope. The existing computing and networking bottlenecks introduce significant penalties in each step of these experiments, and thus, real-time analysis-driven automated experimentation for multidimensional TEM is challenging. One solution is to integrate microscopy with edge computing, where moderately powerful computational hardware performs the preliminary analysis before handing off the heavier computation to high-performance computing (HPC) systems. In this work, we trace the roots of computation in modern electron microscopy, demonstrate deep learning experiments running on an edge system, and discuss the networking requirements for tying together microscopes, edge computers, and HPC systems.

47 OTHER INSTRUMENTATION↗

Identifying Important Ions and Positions in Mass Spectrometry Imaging Data Using CUR Matrix Decompositions

Mass spectrometry imaging enables label-free, high-resolution spatial mapping of the chemical composition of complex, biological samples. Typical experiments require selecting ions and/or positions from the images: ions for fragmentation studies to identify keystone compounds and positions for follow up validation measurements using microdissection or other orthogonal techniques. Unfortunately, with modern imaging machines, these must be selected from an overwhelming amount of raw data. Existing techniques to reduce the volume of data, the most popular of which are principle component analysis and non-negative matrix factorization, have the disadvantage that they return difficult-to-interpret linear combinations of actual data elements. In this work, we show that CX and CUR matrix decompositions can be used directly to address this selection need. CX and CUR matrix decompositions use empirical statistical leverage scores of the input data to provide provably good low-rank approximations of the measured data that are expressed in terms of actual ions and actual positions, as opposed to difficult-to-interpret eigenions and eigenpositions. We show that this leads to effective prioritization of information for both ions and positions. In particular, important ions can be found either by using the leverage scores as a ranking function and using a deterministic greedy selection algorithm or by using the leverage scores as an importance sampling distribution and using a random sampling algorithm; however, selection of important positions from the original matrix performed significantly better when they were chosen with the random sampling algorithm. Also, we show that 20 ions or 40 locations can be used to reconstruct the original matrix to a tolerance of 17% error for a widely studied image of brain lipids; and we provide a scalable implementation of this method that is applicable for analysis of the raw data where there are often more than a million rows and/or columns, which is larger than SVD-based low-rank approximation methods can handle. Lastly, these results introduce the concept of CX/CUR matrix factorizations to mass spectrometry imaging, describing their utility and illustrating principled algorithmic approaches to deal with the overwhelming amount of data generated by modern mass spectrometry imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical Imaging of Atmospheric Particles

Airborne particles are very dynamic and highly reactive components of the Earth’s atmosphere. Their high surface area and water content provide a unique reaction environment for multiphase chemistry that continually modifies particle composition and properties that consequently impact air quality as well as concentrations of gas-phase species. By absorbing and scattering solar and terrestrial radiation, particles directly influence the planet’s radiative balance. Their indirect effects include modifying the nucleation, lifetime, and physical properties of clouds. Due to the sensitivity of the atmospheric environment to all these variables, fundamental studies of chemical transformations of atmospheric particles, their sources, continuously evolving composition, and physical properties are of highest research priority. Accurate descriptions of particles and their effects in the atmosphere require comprehensive information not only on the particle-type populations and their size distributions and concentrations, but also on the diversity and the spatial heterogeneity of chemical components within individual particles. Developments and applications of modern chemical imaging approaches for off-line characterization of atmospheric particles have been at the forefront of modern experimental studies and have resulted in a transformative impact in atmospheric chemistry and physics. This Account presents a synopsis of recent advances in chemical imaging of atmospheric particles collected on substrates during field and laboratory experiments. The unique advantage of chemical imaging methods is that they simultaneously provide two analytical measurements: imaging of particles to assess variability in their individual sizes and morphology, as well as particle specific speciation of their composition and spatial heterogeneity of different chemical components within individual particles. We also highlight analytical chemistry approaches that enable chemical imaging of particles with different levels of elemental and molecular specificity, including applications of multimodal methodologies where the same or similar groups of particles are probed by two or more complementary techniques. These approaches provide unique experimental insights on the nature and sources of particles, understanding their physical properties, atmospheric reactivity, and transformations. Chemical imaging data provide unique experimental input for atmospheric models that simulate aging and changes in particle-type populations, internal composition, and their associated optical and cloud forming properties. Here, we highlight applications of chemical imaging in selected recent studies, discuss their existing limitations, and forecast future research directions for this area.

54 ENVIRONMENTAL SCIENCES↗

Intercomparison of the Radio-Chronometric Ages of Plutonium-Certified Reference Materials with Distinct Isotopic Compositions

In this article, an intercomparison of the radio-chronometric ages of four distinct plutonium-certified reference materials varying in chemical form, isotopic composition, and period of production are presented. The cross-comparison of the different 234 U/ 238 Pu, 235 U/ 239 Pu, 236 U/ 240 Pu, and 241 Am/ 241 Pu model purification ages obtained at four independent analytical facilities covering a range of laboratory environments from bulk sample processing to clean facilities dedicated to nuclear forensic investigation of environmental samples enables a true assessment of the state-of-practice in “age dating capabilities” for nuclear materials. The analytical techniques evaluated used modern mass spectrometer instrumentation including thermal ionization mass spectrometers and inductively coupled plasma mass spectrometers for isotopic abundance measurements. Both multicollector and single collector instruments were utilized to generate the data presented here. Consensus values established in this study make it possible to use these isotopic standards as quality control standards for radio-chronometry applications. Results highlight the need for plutonium isotopic standards that are certified for 234 U/ 238 Pu, 235 U/ 239 Pu, 236 U/ 240 Pu, and 241 Am/ 241 Pu model purification ages as well as other multigenerational radio-chronometers such as 237 Np/ 241 Pu. Due to the capabilities of modern analytical instrumentation, analytical laboratories that focus on trace level analyses can obtain model ages with marginally larger uncertainties than laboratories that handle bulk samples. Lastly, when isotope ratio measurement techniques like thermal ionization mass spectrometry and inductively coupled plasma mass spectrometry with comparable precision are utilized, model purification ages with similar uncertainties are obtained.

36 MATERIALS SCIENCE↗

Investigating the Intercalation Chemistry of Alkali Ions in Fluoride Perovskites

Reversible intercalation reactions provide the basis for modern battery electrodes. Despite decades of exploration of electrode materials, the potential for materials in the nonoxide chemical space with regards to intercalation chemistry is vast and rather untested. Transition metal fluorides stand out as an obvious target. To this end, we report herein a new family of iron fluoride-based perovskite cathode materials A x K 1–x FeF 3 (A = Li, Na). By starting with KFeF 3 , approximately 75% of K + ions were subsequently replaced by Li + and Na + through electrochemical means. X-ray diffraction and Fe X-ray absorption spectroscopy confirmed the existence of intercalation of alkali metal ions in the perovskite structure, which is associated with the Fe 2+/3+ redox couple. A computational study by density functional theory showed agreement with the structural and electrochemical data obtained experimentally, which suggested the possibility of fluoride-based materials as potential intercalation electrodes. This study increases our understanding of the intercalation chemistry of ternary fluorides, which could inform efforts toward the exploration of new electrode materials.

36 MATERIALS SCIENCE↗

Ligand–Metal Complementarity in Rare-Earth and Actinide Chemistry

In this article, the rare-earths are comprised of scandium, yttrium, and the lanthanides (atomic numbers 21, 39, and 57–71). (1) While these elements are essential to modern life, they were historically characterized as simple, perhaps dull, compared to the rich multielectron chemistry of d-block metals in catalysts and enzymes. These descriptions were quite fair and largely true at the time that these elements were being discovered and the first compounds containing them were being synthesized, although much progress has been made to overturn this view of the rare earths. Similarly, discussions about actinide chemistry are sometimes limited to research pertinent to the nuclear industry, which, while comprising technologies vital to modern society, does not celebrate the fascinating chemical space that much of the actinide series occupies. These historic characterizations of most of the rare-earth and actinide elements persist in some textbooks, and we acknowledge that it is a helpful place to start; however, altogether these series comprise 32 elements-27% of the 118 known by 2024-and we suggest it would be an unfortunate twist of physics if such a large proportion of the Periodic Table were genuinely dull. Indeed, as this Inorganic Chemistry Forum Issue “Ligand-Metal Complementarity in Rare-Earth and Actinide Chemistry” highlights, the chemistry-let alone the physics, that is, spectroscopy and magnetism-of these elements is rich and depends on ligands!

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Modes Elucidate the Nuclear Magnetic Resonance Relaxation of Viscous Fluids

The Bloembergen, Purcell, and Pound (BPP) theory of nuclear magnetic resonance (NMR) relaxation in fluids dating back to 1948 continues to be the linchpin in interpreting NMR relaxation data in applications ranging from characterizing fluids in porous media to medical imaging (MRI). The BPP theory is founded on assuming molecules are hard spheres with 1 H– 1 H dipole pairs reorienting randomly; assumptions that are severe in light of modern understanding of liquids. Nevertheless, it is intriguing to this day that the BPP theory was consistent with the original experimental data for glycerol, a hydrogen-bonding molecular fluid for which the hard-sphere-rigid-dipole assumption is inapplicable. To better understand this incongruity, atomistic molecular simulations are used to compute 1 H NMR T 1 relaxation dispersion (i.e., frequency dependence) in two contrasting cases: glycerol, and a (non hydrogen-bonding) viscosity standard. At high viscosities, simulations predict distinct functional forms of T 1 for glycerol compared to the viscosity standard, in agreement with modern measurements, yet both in contrast to BPP theory. The cause of these departures from BPP theory is elucidated, without assuming any relaxation models and without any free parameters, by decomposing the simulated T 1 response into dynamic molecular modes for both intramolecular and intermolecular interactions. The decomposition into dynamic molecular modes provides an alternative framework to understand the physics of NMR relaxation for viscous fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advanced Potential Energy Surfaces for Molecular Simulation

Advanced potential energy surfaces are defined as theoretical models that explicitly include many-body effects that transcend the standard fixed-charge, pairwise-additive paradigm typically used in molecular simulation. However, several factors relating to their software implementation have precluded their widespread use in condensed-phase simulations: the computational cost of the theoretical models, a paucity of approximate models and algorithmic improvements that can ameliorate their cost, underdeveloped interfaces and limited dissemination in computational code bases that are widely used in the computational chemistry community, and software implementations that have not kept pace with modern high-performance computing (HPC) architectures, such as multicore CPUs and modern graphics processing units (GPUs). Here in this Feature Article we review recent progress made in these areas, including well-defined polarization approximations and new multipole electrostatic formulations, novel methods for solving the mutual polarization equations and increasing the MD time step, combining linear-scaling electronic structure methods with new QM/MM methods that account for mutual polarization between the two regions, and the greatly improved software deployment of these models and methods onto GPU and CPU hardware platforms. Finally, we have now approached an era where multipole-based polarizable force fields can be routinely used to obtain computational results comparable to state-of-the-art density functional theory while reaching sampling statistics that are acceptable when compared to that obtained from simpler fixed partial charge force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data

The ever-increasing power of modern super-computers, along with the availability of highly scalable atomistic simulation codes, has begun to revolutionize predictive modeling of materials. In particular, molecular dynamics (MD) has led to breakthrough advances in diverse fields, including tribology, catalysis, sensing, and nanoparticle self-assembly. Furthermore, recent integration of MD simulations with X-ray characterization has demonstrated promise in real-time 3-D characterization of materials on the atomic scale. The popularity of MD is driven by its applicability at disparate length/time scales, ranging from ab initio MD (hundreds of atoms and tens of picoseconds) to all-atom classical MD (millions of atoms over microseconds), and coarse-grained (CG) models (micrometers and tens of microseconds). Nevertheless, a substantial gap persists between AIMD, which is highly accurate but restricted to extremely small sizes, and those based on classical force fields (atomistic and CG) with limited accuracy but access to larger length/time scales. The accuracy and predictive power of classical MD simulations is dictated by the empirical force fields, and their capability to capture the relevant physics. Here, we discuss some of our recent work on the use of machine learning (ML) to combine the accuracy and flexibility of electronic structure calculations with the speed of classical potentials. Our ML framework attempts to bridge the significant gulf that exists between the handful of research groups that develop new interatomic potential models (often requiring several years of effort), and the increasingly large user community from academia and industry that applies these models. Our data-driven approach represents significant departure from the status quo and involves several steps including generation and manipulation of extensive training data sets through electronic structure calculations, defining novel potential functional forms, employing state-of-the-art ML algorithms to formulate highly optimized training procedures, and subsequently developing user-friendly workflow tools integrating these algorithms on high-performance computers (HPCs). Our ML approach shows marked success in developing force fields for a wide range of materials from metals, oxides, nitrides, and heterointerfaces to two-dimensional (2D) materials.

Chan, Henry↗

Understanding the Adsorption of Rare-Earth Elements in Oligo-Grafted Mesoporous Carbon

Rare-earth elements (REEs) are 17 elements of the periodic table primarily consisting of lanthanides. In modern society, the usage of REEs is ubiquitous in almost all modern gadgets and therefore efficient recovery and separation of REEs are of high importance. Selective adsorption and chelation of REEs in solid sorbents is a unique and sustainable process for their recovery. In this work, single-stranded oligos with 100 units of thymine were grafted onto carboxylated mesoporous carbon to synthesize a sorbent with phosphorus and oxygen functionalities. Additionally, the sorbent was characterized by X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, and scanning electron microscopy-energy-dispersive X-ray spectroscopy. Three different REEs with varying atomic radii and densities, Lu, Dy, and La, were adsorbed onto the carbon from aqueous solutions. It was observed that the adsorbed amounts increased with the increase in the atomic radius or decrease in the atomic density. Calculation of the distribution coefficients for all the equilibrium adsorption amounts suggested that adsorption is more effective in the lower concentration region. The L 3 -edge X-ray absorption near-edge structure confirmed a 3+ oxidation state of REEs in the adsorbed phase. Extended X-ray absorption fine structure (EXAFS) confirmed the binding of REEs with oxygen functionalities in the adsorbed phase. The radial distribution functions calculated from the EXAFS data suggest a longer RE–O distance for La compared to those for Lu and Dy. The coordination numbers and Debye–Waller factors have typical values of about 8–9 atoms and 0.01–0.02 Å 2 , respectively.

36 MATERIALS SCIENCE↗