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	<title>Anisotropic &#8211; Science</title>
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	<link>https://scienmag.com</link>
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	<title>Anisotropic &#8211; Science</title>
	<link>https://scienmag.com</link>
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		<title>Anisotropic conductivity modeling for tDCS in Parkinson’s disease using multidimensional diffusion MRI</title>
		<link>https://scienmag.com/anisotropic-conductivity-modeling-for-tdcs-in-parkinsons-disease-using-multidimensional-diffusion-mri/</link>
		
		<dc:creator><![CDATA[Cassandra Pierce]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 16:29:04 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[Anisotropic]]></category>
		<category><![CDATA[Anisotropic conductivity modeling for tDCS in Parkinson’s disease]]></category>
		<category><![CDATA[brain conductivity]]></category>
		<category><![CDATA[brain conductivity tensor orientation]]></category>
		<category><![CDATA[cerebrospinal fluid]]></category>
		<category><![CDATA[conductivity]]></category>
		<category><![CDATA[diffusion tensor imaging]]></category>
		<category><![CDATA[diffusion tensor imaging comparison]]></category>
		<category><![CDATA[electric field modeling]]></category>
		<category><![CDATA[electric-field prediction in transcranial direct current stimulation]]></category>
		<category><![CDATA[electrode montage effects on tDCS]]></category>
		<category><![CDATA[impact of diffusion MRI models on electric-field predictions]]></category>
		<category><![CDATA[MRI elastography]]></category>
		<category><![CDATA[MRI-based brain tissue conductivity modeling]]></category>
		<category><![CDATA[multidimensional diffusion MRI]]></category>
		<category><![CDATA[Parkinson's disease]]></category>
		<category><![CDATA[Parkinson’s disease brain stimulation analysis]]></category>
		<category><![CDATA[q-space trajectory imaging]]></category>
		<category><![CDATA[q-space trajectory imaging in brain modeling]]></category>
		<category><![CDATA[tDCS]]></category>
		<category><![CDATA[tDCS stimulation dosimetry accuracy]]></category>
		<category><![CDATA[white matter conductivity estimation]]></category>
		<category><![CDATA[white-matter anisotropy]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=329825</guid>

					<description><![CDATA[A modeling study of 29 adults found that multidimensional diffusion MRI altered tDCS electric-field predictions by no more than 6.6% compared with conventional DTI, without establishing improved dosimetric accuracy.]]></description>
										<content:encoded><![CDATA[<p>In a modeling study of 29 adults—12 with Parkinson’s disease and 17 controls—multidimensional diffusion MRI changed predicted transcranial direct current stimulation electric-field magnitudes by no more than 6.6% compared with conventional single-shell diffusion tensor imaging. The investigators described their approach as the first multidimensional-diffusion tDCS conductivity model and compared it with DTI and isotropic models across four electrode montages. The results demonstrate the feasibility of incorporating multidimensional diffusion MRI into tDCS simulations, but they do not show that it produces more accurate stimulation dosimetry.</p>
<p>All three models used the same head mesh, electrodes and electric-field solver, allowing the researchers to compare how different representations of brain conductivity affected the predictions. White-matter conductivity was conventionally estimated from single-shell DTI, while q-space trajectory imaging supplied a mean tensor expected to have less kurtosis bias. The principal difference between the two anisotropic models was tensor orientation, which varied by 18 to 25 degrees across white matter. Despite those directional differences, their predicted electric-field magnitudes differed by 6.6% or less under the tested conditions.</p>
<p>An exploratory comparison found no significant differences in predicted electric fields between participants with Parkinson’s disease and controls in any brain region or across the four montages. The authors characterized this group comparison as underpowered, so the finding should not be interpreted as evidence that the two populations receive equivalent stimulation exposure. The small sample also did not provide ground-truth measurements of brain conductivity or tDCS electric fields. The study therefore characterized the sensitivity of model predictions rather than establishing improved dosimetric accuracy.</p>
<p>Whole-brain predicted electric field correlated with brain stiffness measured by magnetic resonance elastography, with a partial correlation of 0.58. After cerebrospinal fluid morphology was included in the statistical model, this relationship was no longer significant, and the partial correlations fell to 0.06–0.09. The result shows that the association weakened after statistical adjustment for cerebrospinal fluid morphology; it does not by itself establish a causal influence of that anatomy. Based on the findings, the authors concluded that Parkinson’s disease modeling efforts should emphasize cerebrospinal fluid- and atrophy-aware head models and dose normalization rather than automatically adopting a more complex diffusion tensor. Overall, the choice of diffusion tensor was a second-order influence on predicted electric fields compared with individual anatomy under the conditions examined.</p>
<p><strong>Subject of Research:</strong> Comparison of multidimensional diffusion MRI and DTI models for predicting tDCS electric fields in Parkinson’s disease</p>
<p><strong>Article Title:</strong> Anisotropic conductivity modeling for tDCS in Parkinson’s disease using multidimensional diffusion MRI</p>
<p><strong>Article References:</strong> Osorio Jurado, S., Skorpil, M., Svenningsson, P., Moreno, R., &amp; Olsson, C. (2026). Anisotropic conductivity modeling for tDCS in Parkinson’s disease using multidimensional diffusion MRI. <em>Frontiers in Human Neuroscience, 20</em>, Article 1972676. <a href="https://doi.org/10.3389/fnhum.2026.1972676" rel="noopener noreferrer">https://doi.org/10.3389/fnhum.2026.1972676</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3389/fnhum.2026.1972676" rel="noopener noreferrer">10.3389/fnhum.2026.1972676</a></p>
<p><strong>Keywords:</strong> tDCS, Parkinson’s disease, multidimensional diffusion MRI, q-space trajectory imaging, diffusion tensor imaging, electric-field modeling, brain conductivity, MRI elastography, cerebrospinal fluid, white-matter anisotropy, Anisotropic, conductivity</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">329825</post-id>	</item>
		<item>
		<title>Automated polarised FTIR unlocks hidden water in pyroxene crystals</title>
		<link>https://scienmag.com/automated-polarised-ftir-unlocks-hidden-water-in-pyroxene-crystals/</link>
		
		<dc:creator><![CDATA[Bethany Barker]]></dc:creator>
		<pubDate>Thu, 15 Oct 2026 06:35:01 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[Earth Science]]></category>
		<category><![CDATA[absorption]]></category>
		<category><![CDATA[advanced hardware and software for mineral analysis]]></category>
		<category><![CDATA[anhydrous]]></category>
		<category><![CDATA[Anisotropic]]></category>
		<category><![CDATA[Automated polarized FTIR spectroscopy for water detection in pyroxene]]></category>
		<category><![CDATA[challenges in detecting water in pyroxene]]></category>
		<category><![CDATA[deep Earth mineral hydration]]></category>
		<category><![CDATA[Fourier]]></category>
		<category><![CDATA[Fourier transform infrared spectroscopy in mineralogy]]></category>
		<category><![CDATA[geoscience techniques for water quantification in mantle]]></category>
		<category><![CDATA[hidden water in Earth's mantle minerals]]></category>
		<category><![CDATA[hydrogen in nominally anhydrous minerals]]></category>
		<category><![CDATA[implications for Earth's electrical conductivity]]></category>
		<category><![CDATA[infrared]]></category>
		<category><![CDATA[innovative methods in geophysical]]></category>
		<category><![CDATA[Investigation]]></category>
		<category><![CDATA[measuring hydroxyl groups in deep Earth minerals]]></category>
		<category><![CDATA[methods]]></category>
		<category><![CDATA[minerals]]></category>
		<category><![CDATA[nominally]]></category>
		<category><![CDATA[quantification]]></category>
		<category><![CDATA[role of water in mantle flow and melting]]></category>
		<category><![CDATA[spectroscopy]]></category>
		<category><![CDATA[transform]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=272979</guid>

					<description><![CDATA[Deep inside the Earth's mantle, the minerals that make up most of its volume are, by name at least, dry. Pyroxene, olivine, and garnet are collectively called nominally anhydrous minerals, or NAMs, because their crystal structures contain no water molecules]]></description>
										<content:encoded><![CDATA[<p>Deep inside the Earth&#8217;s mantle, the minerals that make up most of its volume are, by name at least, dry. Pyroxene, olivine, and garnet are collectively called nominally anhydrous minerals, or NAMs, because their crystal structures contain no water molecules in the conventional sense. Yet these crystals can hold astonishing amounts of hydrogen, bound as hydroxyl groups to oxygen atoms within the lattice, and this hidden water changes everything about how the mantle flows, melts, and conducts electricity. A team of researchers led by Nils B. Gies of the University of Bern, together with Jörg Hermann, Georgia Cametti, and Sonja Aulbach of Goethe University Frankfurt, has now developed a suite of new hardware and software methods that make measuring this invisible hydrogen far more reliable, particularly in the notoriously difficult case of pyroxene. Their work, published in the European Journal of Mineralogy, could reshape how geoscientists quantify water in the deep Earth.</p>
<p>The core problem is one of geometry. Fourier transform infrared spectroscopy, or FTIR, is the workhorse technique for detecting structurally bound hydroxyl in minerals. An infrared beam passes through a crystal, and the hydroxyl groups absorb at characteristic wavenumbers between roughly 3000 and 3800 centimetres to the power of minus one. In an isotropic mineral such as garnet, absorption is identical in every direction, so a single unpolarised measurement, multiplied by three, yields the total absorbance needed to calculate a water content via the Beer-Lambert law. But pyroxene is anisotropic. The hydroxyl dipoles are oriented in specific crystallographic directions, and the amount of light absorbed depends dramatically on how the crystal is oriented relative to the polarisation of the incident beam. Measuring along three mutually perpendicular directions gives the total absorbance, but in low-symmetry crystals, knowing which three directions to choose is anything but straightforward.</p>
<p>For orthorhombic orthopyroxene, the crystallographic axes and the optical indicatrix axes coincide, so randomly oriented grains can be oriented using cleavage, morphology, or optical extinction, and the three principal polarised spectra can be acquired along the a, b, and c axes. Monoclinic clinopyroxene is a different beast entirely. Here, the angle between the crystallographic a axis and the plane containing b and c deviates from ninety degrees, and, crucially, the infrared absorption indicatrices of different hydroxyl-related defects are not always aligned with the axes of the optical indicatrix. As Strens and colleagues established as early as 1982 for polarised visual light spectroscopy, the direction of principal absorption in monoclinic and triclinic crystals does not necessarily coincide with either the crystallographic axes or the principal refractive index directions. Three measurements along the optical indicatrix are therefore insufficient to fully describe the absorption behaviour, even for a single defect type. Four independent directions are needed for monoclinic crystals, and six for triclinic ones.</p>
<p>The first innovation from the Bern group is an automatic polariser, built from an open-source, customisable, low-cost, 3D-printed design. Attached to a Bruker Hyperion microscope, the device uses a stepper motor controlled by an Arduino microcontroller to rotate an infrared polariser in equal-angle increments between 0 and 180 degrees. A limit switch enables automatic incrementation each time the measurement stage returns to its background position, so a full angular polarisation series, comprising 36 to 90 spectra per measurement point, can be acquired without any manual intervention. This eliminates human bias in setting the polarisation angle and allows large numbers of spots to be measured with dramatically less effort. The design, including wiring diagrams, 3D models, and source code, is freely available on GitHub, meaning any laboratory with modest resources can replicate the set-up.</p>
<p>Complementing the hardware is a new software solution called PolPlotModule, an add-on for the open-source spectroscopy processing package SpecXY. The module divides angle-resolved polarised measurements into individual sets of spectra for each measurement position and visualises them as polarisation plots. A MultiSpectraDeconvolution routine performs a Simplex inversion, minimising the global peak deconvolution error across the full set of angle-resolved spectra simultaneously. A two-step Spectral Endmember Estimation routine, first using the N-FINDR algorithm and then a non-negative linear least-squares fit, extracts the pure spectral endmember signatures from large data sets. Together, these tools allow researchers to identify the maximum and minimum absorption directions for each absorption band, which is the prerequisite for accurate water quantification in low-symmetry crystals.</p>
<p>The key insight enabling the new workflow is the use of silicon-oxygen overtone bands in the wavenumber range between 1250 and 2300 centimetres to the power of minus one as orientation fingerprints. These overtone bands, which arise from the fundamental silicon-oxygen stretching vibrations, are present in every pyroxene spectrum regardless of hydrogen content, and their polarisation behaviour is characteristic of specific crystal directions. From a large data set covering diopside, augite, and omphacite, the researchers recognised five distinct spectral endmembers aligned with the optical indicatrix axes X, Y, and Z, the crystallographic b and c axes, and the orthogonal direction a-star, defined as the normal vector to the b-c plane. Once these overtone endmembers are identified, groups of mutually perpendicular spectra can be found, reducing the uncertainty in the total integrated absorbance of the hydroxyl region and thus improving water content determination.</p>
<p>The practical consequences are substantial. For diopside and augite, crystal cuts along the axes of the optical indicatrix are best suited to determining the total integrated absorbance, whereas for omphacite, cuts along the crystallographic b and c axes and the a-star direction give the most reproducible results. The average deviation between the total integrated absorbance calculated from different orthogonal endmember combinations is smaller than 7 percent across all investigated samples, with a maximum observed deviation below 16 percent. The researchers also demonstrated that silicon-oxygen overtones can evaluate sample homogeneity: spectra with identical overtone signals are measured in crystal sections with the same orientation and polarisation direction, so hydroxyl absorption becomes directly comparable between grains. In an inhomogeneous orogenic eclogite from the western Gneiss region of Norway, this approach revealed variations in water content across different grains that would be invisible using unpolarised spectra, where it remains unclear whether absorbance variation reflects orientation or genuine differences in hydrogen content.</p>
<p>Beyond quantification, the angular polarisation series provides a powerful tool for understanding how hydrogen is actually incorporated into the crystal structure. In the gem-quality diopside from Binntal, Switzerland, at least seven overlapping absorption bands were identifiable, and the polarisation behaviour allowed the researchers to distinguish two families of defects corresponding to different incorporation mechanisms: hydrogen on the tetrahedral site, absorbing between 3660 and 3600 centimetres to the power of minus one, and hydrogen on the octahedral M site, absorbing between 3590 and 3300 centimetres to the power of minus one. The observed polarisation behaviour agrees remarkably well with Density Functional Theory modelling by Balan and colleagues, which predicts different pleochroism for defects involving different trivalent cations such as aluminium, iron, and chromium. In the magmatic augite from Mount Guntur in western Java, the FTIR mappings revealed that water zoning is preserved at magmatic temperatures and is strongly coupled to chemical zonation, with higher-wavenumber bands anticorrelating with iron and correlating with chromium and calcium, while M-site-related defects show similarities with aluminium, titanium, silicon, and magnesium.</p>
<p>The team also proposed a new nomenclature for polarised FTIR measurements in low-symmetry crystals, stated as a vector subscripted by a plane. The vector describes the polarisation direction of the incident infrared beam, set by rotating the polariser, while the plane is the crystal section orthogonal to that vector. This flexible scheme, which can combine Miller indices, optical indicatrix axes, crystallographic axes, or any other defined vectors such as a-star, makes different samples directly comparable in terms of absorption behaviour and anisotropy, something previous nomenclature constrained to the optical indicatrix could not achieve, particularly since the angle between the crystallographic c axis and the optical axes X and Z depends on major element composition and can vary from 4 to 94 degrees across clinopyroxene compositions.</p>
<p>The implications reach far beyond the laboratory. Water in nominally anhydrous minerals governs the viscosity and melting behaviour of the mantle, influences electrical conductivity, and controls the transport of hydrogen into the deep Earth through subduction. Accurate quantification of this hidden hydrogen has been hampered for decades by the anisotropy problem, particularly in monoclinic minerals like clinopyroxene, which is one of the most abundant phases in eclogites and mantle peridotites. By automating the acquisition of angle-resolved polarised spectra, providing open-source tools for their processing and visualisation, and establishing robust protocols for identifying the spectral endmembers needed for quantification, the Bern group has given the community a framework to measure mantle water with unprecedented precision. The work provides a foundation for investigating hydrogen incorporation mechanisms in clinopyroxene and other monoclinic or triclinic crystals, and it demonstrates that acquiring more than three independent polarised measurements is essential to fully describe absorption anisotropy in low-symmetry crystals. As the hidden water inventory of the deep Earth comes into sharper focus, these new methods promise to make the invisible measurable.</p>
<p><strong>Subject of Research:</strong> New methods for Fourier transform infrared spectroscopy investigation and quantification of OH absorption in anisotropic nominally anhydrous minerals: the example of pyroxene</p>
<p><strong>Article Title:</strong> New methods for Fourier transform infrared spectroscopy investigation and quantification of OH absorption in anisotropic nominally anhydrous minerals: the example of pyroxene</p>
<p><strong>Article References:</strong> Gies, N. B., Hermann, J., Cametti, G., &amp; Aulbach, S. (2026). New methods for Fourier transform infrared spectroscopy investigation and quantification of OH absorption in anisotropic nominally anhydrous minerals: the example of pyroxene. <em>European Journal of Mineralogy, 38</em>(5), 583-627. <a href="https://doi.org/10.5194/ejm-38-583-2026" rel="noopener noreferrer">https://doi.org/10.5194/ejm-38-583-2026</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.5194/ejm-38-583-2026" rel="noopener noreferrer">10.5194/ejm-38-583-2026</a></p>
<p><strong>Keywords:</strong> methods, Fourier, transform, infrared, spectroscopy, investigation, quantification, absorption, anisotropic, nominally, anhydrous, minerals</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">272979</post-id>	</item>
		<item>
		<title>Strained Silicon Quantum Dots Reveal New Design Rules for Intermediate-Band Solar Cells</title>
		<link>https://scienmag.com/strained-silicon-quantum-dots-reveal-new-design-rules-for-intermediate-band-solar-cells/</link>
		
		<dc:creator><![CDATA[Katie Riggs]]></dc:creator>
		<pubDate>Sat, 12 Sep 2026 20:27:40 +0000</pubDate>
				<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[AM1.5G spectrum]]></category>
		<category><![CDATA[Anisotropic]]></category>
		<category><![CDATA[band alignment]]></category>
		<category><![CDATA[effective mass anisotropy]]></category>
		<category><![CDATA[efficiency enhancement in silicon solar cells]]></category>
		<category><![CDATA[electron]]></category>
		<category><![CDATA[intermediate band solar cell design rules]]></category>
		<category><![CDATA[intermediate-band solar cell]]></category>
		<category><![CDATA[intermediate-band solar cells]]></category>
		<category><![CDATA[miniband dispersion]]></category>
		<category><![CDATA[multi-step photon absorption in solar cells]]></category>
		<category><![CDATA[nanostructured silicon for solar energy]]></category>
		<category><![CDATA[Photovoltaics]]></category>
		<category><![CDATA[quantum confinement in silicon-germanium systems]]></category>
		<category><![CDATA[quantum dot-based photovoltaic devices]]></category>
		<category><![CDATA[Si1-xGex]]></category>
		<category><![CDATA[SiGe superlattice]]></category>
		<category><![CDATA[silicon quantum dots]]></category>
		<category><![CDATA[silicon-based intermediate band materials]]></category>
		<category><![CDATA[silicon-germanium quantum dot superlattices]]></category>
		<category><![CDATA[strain effects in silicon quantum dots]]></category>
		<category><![CDATA[strain-engineered silicon quantum dots]]></category>
		<category><![CDATA[superlattice engineering for solar energy]]></category>
		<category><![CDATA[tensile strain]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=198340</guid>

					<description><![CDATA[A new theoretical study maps the design space of strained silicon quantum-dot superlattices that could support intermediate-band photovoltaics compatible with silicon technology.]]></description>
										<content:encoded><![CDATA[<p>Silicon has long dominated the solar industry, but its fundamental physics imposes hard limits on how much sunlight a single-junction cell can convert into electricity. Photons with less energy than silicon&#8217;s band gap simply pass through the material, while photons carrying far more energy than needed dump their excess as heat. A new theoretical study published in Results in Physics by Diero Lassina and colleagues at institutions in Burkina Faso offers a carefully quantified path around both losses, mapping out precisely which nanostructured silicon-germanium designs could support an intermediate band, an extra electronic manifold sandwiched inside the forbidden gap that allows sunlight to be harvested in two lower-energy steps while, in the ideal limit, preserving the output voltage.</p>
<p>The intermediate-band solar cell concept, first proposed by Luque and Martí in 1997, has been demonstrated experimentally in expensive III-V compound semiconductor systems, but its compatibility with mainstream silicon manufacturing has remained an open question. The new work addresses this by simulating a periodic superlattice of cubic silicon quantum dots, each under tensile strain, embedded in a relaxed silicon-germanium matrix. When quantum dots are packed close enough together, their confined electron wave functions overlap and isolated energy levels broaden into minibands, which could serve as the intermediate band. Crucially, the team replaced the simplified single effective mass used in their earlier work with the full anisotropic effective mass tensor of the strain-split silicon Delta-2 valleys, with transverse masses of 0.19 and a longitudinal mass of 0.916 times the free electron mass, oriented along the growth axis.</p>
<p>That change turned out to matter enormously. The researchers scanned 495 different geometries, varying the dot size from 3.0 to 8.0 nanometres, the barrier thickness between dots from 1.0 to 5.0 nanometres, and the germanium fraction in the matrix from 0.20 to 0.38, solving the anisotropic BenDaniel-Duke Hamiltonian on a fine finite-difference grid with Bloch boundary conditions at 132 high-symmetry wave-vector points. Their central finding is that mass anisotropy alters the dispersion and isolation of the minibands far more strongly than it shifts the band minimum itself. The light transverse masses amplify spreading in the plane of the dots, while the heavy longitudinal mass suppresses it along the stacking direction, so bandwidths and inter-band overlaps change in ways a scalar mass simply cannot capture.</p>
<p>To qualify as a usable intermediate band, the lowest electron miniband had to satisfy four criteria simultaneously: it must remain fully bound below the barrier, carry a thermal margin exceeding one thermal energy unit at room temperature, span at least 5 millielectronvolts to form a genuine band rather than a flat level, and sit at least 5 millielectronvolts away from the next higher miniband to avoid parasitic hybridisation. Under these core conditions, 171 of the 495 geometries passed; adding an upper width limit of 50 millielectronvolts, designed to prevent the band from becoming too delocalised, trimmed the strict set to 170. Notably, no geometry survived at barrier thicknesses of 1.5 nanometres or below. In all 110 of those thin-barrier cases, the isolation criterion failed because strong tunnelling broadens adjacent bands until they overlap, and in 22 cases the lowest band even lost full confinement.</p>
<p>Perhaps the most consequential revision is compositional. The earlier scalar-mass model had pointed to a single optimum germanium fraction near 0.30. The tensor calculation instead reveals a favourable plateau at higher germanium contents, roughly x = 0.35 to 0.38, where the stronger electron barrier balances the increased in-plane coupling introduced by the lighter transverse masses. The comparison between models is striking: only 66 structures, about a third of the scalar core, survive in both models. One hundred five geometries enter the tensor core because anisotropic broadening lifts their bandwidth above the minimum threshold, while 138 scalar survivors drop out, mostly because their inter-miniband separation falls below 5 millielectronvolts. Median changes across the full scan included a 35.78 millielectronvolt reduction in inter-band separation, underscoring why density-of-states-equivalent masses are inadequate for directional kinetic modelling.</p>
<p>The team also resolved a subtle band-alignment question that has puzzled researchers in this material system: how adding germanium to the matrix can still create a barrier for electrons. The answer lies in strain. Tensile strain in the silicon dot splits the conduction valleys, and for the Si-rich compositions studied, the relevant strained alignment places the matrix conduction edge above the dot edge, with the offset given by 0.64 times the germanium fraction. The valence-band alignment, meanwhile, is type II: the highest heavy-hole state sits in the silicon-germanium matrix while the electron miniband resides in the strained silicon dot. This spatial separation makes the valence-band-to-intermediate-band transition spatially indirect, a fact with real implications for optical strength that the authors flag as requiring future phonon-assisted treatment.</p>
<p>To connect these electronic structures to actual sunlight, the researchers integrated the ASTM G173-03(2020) AM1.5G reference solar spectrum, using its full tabulated 2002 wavelengths from 280 to 4000 nanometres at an integrated power of 1000.371 watts per square metre without renormalisation. Because a miniband has finite width, the position chosen within it, bottom, centre or top, changes the two sub-gap photon thresholds. The spectrum was partitioned into three disjoint energy windows corresponding to the two-step and direct transitions, and the matched two-photon flux was taken as the smaller of the two sub-gap channels. In every one of the 170 strict geometries and at every placement, the valence-band-to-intermediate-band channel was the limiting one, a structural consequence of the fact that the width of that spectral window equals the second transition energy, which is bounded by the conduction-band offset and never exceeds 0.2432 electronvolts across the studied range.</p>
<p>The placement sensitivity analysis delivered another practical lesson. Moving the assumed intermediate state from the bottom to the top of the miniband changed the matched two-step photon flux by a median of 5.91 percent and by more than 51 percent in the extreme case, with 31 of 170 geometries shifting by over 20 percent. The ideal total spectral current bound, by contrast, moved by less than 3.9 percent because the direct above-gap contribution dominates that aggregate. The authors stress that their photon counts are upper bounds assuming perfect absorption and collection: phonon-assisted optical matrix elements, carrier occupations, recombination, escape mechanisms, and device electrostatics are all excluded from the present calculation, so the numbers should guide material screening rather than efficiency claims.</p>
<p>The study also probes robustness. Because a periodic unit cell cannot represent the random disorder of real self-assembled dot arrays, the team examined what happens when each retained design is nudged by a single 0.5-nanometre grid step in dot size or barrier thickness. Only about 41 percent of core geometries kept their classification across all nearest-neighbour changes, with median shifts as large as 6.10 millielectronvolts in isolation energy. The practical message for experimentalists is clear: choose candidate structures from the interior of the high-germanium design region, never from its staircase-shaped boundary, and subject the survivors to fuller models incorporating phonon-assisted absorption, disorder, recombination kinetics and device fields before any efficiency prediction can be trusted. In doing so, the work delivers exactly what screening studies are meant to provide, a defensible shortlist of silicon-compatible nanostructures worth the investment of more expensive simulation and, eventually, growth.</p>
<p><strong>Subject of Research:</strong> Anisotropic electron minibands and solar spectral usability in tensile-strained Si/SiGe quantum-dot superlattices for intermediate-band solar cells</p>
<p><strong>Article Title:</strong> Anisotropic electron minibands and AM1.5G spectral usability windows in tensile-strained Si/relaxed Si 1-x Ge x quantum-dot superlattices</p>
<p><strong>Article References:</strong> Lassina, D., Soumaïla, D., Michel, K. O., Alain, D., Raguilignaba, S., &amp; François, Z. (2026). Anisotropic electron minibands and AM1.5G spectral usability windows in tensile-strained Si/relaxed Si1-xGex quantum-dot superlattices. <em>Results in Physics</em>, Article 108754. <a href="https://doi.org/10.1016/j.rinp.2026.108754" rel="noopener noreferrer">https://doi.org/10.1016/j.rinp.2026.108754</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1016/j.rinp.2026.108754" rel="noopener noreferrer">10.1016/j.rinp.2026.108754</a></p>
<p><strong>Keywords:</strong> intermediate-band solar cell, silicon quantum dots, SiGe superlattice, miniband dispersion, effective mass anisotropy, AM1.5G spectrum, tensile strain, band alignment, photovoltaics, Si1-xGex, Anisotropic, electron</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">198340</post-id>	</item>
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