This study aims to solve the site-occupancy issues of any crystalline substance, showing that the structure refinement results should not be limited to a simple description of the crystal geometry but should go beyond that, providing refined site-scattering values consistent with the chemical data. A detailed description of the structure of the amphibole-supergroup minerals is very challenging owing to their complex chemical composition that renders the process of cation partition extremely difficult, particularly because of the occurrence of multivalent elements. Since amphiboles naturally occur under a fibrous morphology and have largely been used to produce asbestos, there is a growing demand for detailed and accurate structural data in order to study the relationships between structure, composition and toxicity. The present study proposes a recommended refinement procedure for both X-ray single-crystal structure refinement (SREF) and Rietveld analysis for tremolite, selected as a test case. The corresponding structural results are compared to estimate the ‘degree of confidence’ of the Rietveld refinement with regard to SREF. In particular, it is shown that the interpretation of the electron density of the tremolite structure by SREF is model dependent. By assuming that the site-scattering values from SREF should be as close as possible to those from electron microprobe analysis, as a crucial constraint for the correct description of the final crystal-chemical model, it is found that it is best satisfied by using partially ionized scattering curves (SCs) for O and Si, and neutral SCs  for other atoms. This combination leads to the best fit to the diffraction data. Moreover, it is found that Rietveld refinement using NOCs produces the best structural results, in excellent agreement with SREF. It is worth noting that, due to the complexity of the diffraction pattern and the fairly large number of freely refinable parameters, refinements with different combinations of SCs produce results almost indistinguishable from a statistical point of view, albeit showing significant differences from a structural point of view. Hawthorne & Oberti, 2007Amphiboles are among the most thoroughly investigated minerals from a structural and crystal-chemical viewpoint. Large crystal-structure databases have been built and extended modelling of the mutual crystal-chemical and structural relations have been developed (F(000), and the scale factor in least-squares refinement. This is due to the fact that their use implies a different number of electrons at θ = 0° affecting the correlation between displacement parameters and scale factor  on X-ray single-crystal diffraction (XRSCD) data. In particular, results can be affected by the use of different types of X-ray scattering curves (SCs): neutral, or partially or fully ionized for anions and cations. It is worth noting that the choice of  ionized SCs may significantly affect the number of electrons in the crystal unit cell at θ = 0°, et al.  and tetrahedral cations (Six4+Alx1–3+ versus SixAlx1–)……(1) using ionized X-ray scattering curves for non-tetrahedral cations and (2) refining the occupancy of ionized versus neutral species for anions , is missing for amphiboles.Nevertheless, to the best of our knowledge, an in-depth systematic and quantitative analysis of the effect of the scattering factor types used for the atoms on the refined SS values, as well as on other refined structural parameters  whose onsets were confirmed by means of other analytical tools. However, to date and to the best of our knowledge, there is no analysis of the ‘confidence level’ of such results compared with those arising from single-crystal SREF. Despite the large wealth of papers addressing this general topic (XRPD versus XRSCD data refinement), none of them has been especially devoted to amphiboles.In order to unravel possible relations between structure, composition and toxicity, detailed and accurate structural data are needed. However, the structural analysis of fibrous amphiboles poses additional complications compared with that of prismatic samples having adequate dimensions for SREF. In fact, despite the promising attempts to use synchrotron nano-diffraction experiments  are used to obtain total SS values that best match the chemical data. In order to provide relevant information to perform an optimal SREF, the present study is addressed to a systematic analysis of the effect of different types of scattering curves used for the atoms on the refined structural parameters of a gem-quality tremolite sample from Merelani (Tanzania). This sample was selected as a case study for its high crystallinity and chemical homogeneity. The SREF results were then compared with those obtained from Rietveld refinement in order to estimate their ‘degree of confidence’. Similarly, in the case of Rietveld refinements, the effects of choosing different SCs have been investigated to identify the best computational conditions, as already done for the spinel structure by Ballirano 2003. The res2.e.g. Bosi et al., 2019Minerals are chemical substances that need to be represented by formulae. There are several types of mineral formulae 2[M(1)2M(2)2M(3)][T(1)4T(2)4]O22O(3)2, where the italicized letters represent non-equivalent structural sites.The general chemical formula of the amphibole-supergroup minerals may be written as AB2C5T8O22W2, where:The general A = □, Na, K, Ca, Pb, Li;2+, Fe2+, Mg, Li;B = Na, Ca, Mn2+, Mn2+, Al, Fe3+, Mn3+, Cr3+, Ti4+, Li;C = Mg, Fe4+, Be;T = Si, Al, Ti2–.W = (OH), F, Cl, OM sites or the W anions at the O(3) site , was chemically characterized by electron microprobe analysis (EMPA). This analysis was obtained using a wavelength-dispersive spectrometer (WDS mode) with a Cameca SX50 instrument at the CNR Istituto di Geologia Ambientale e Geoingegneria , operating at an accelerating potential of 15 kV with a 15 nA current and a 1 µm beam diameter. Minerals and synthetic compounds were used as standards: wollastonite , magnetite (Fe), rutile (Ti), corundum (Al), vanadinite (V), fluorphlogopite (F), periclase (Mg), jadeite (Na), orthoclase (K), sphalerite (Zn), rhodonite (Mn) and metallic Cr. The 3.2.Kα radiation from a fine-focus sealed X-ray tube. The sample-to-detector distance was 4 cm. A total of 3687 exposures  covering a full reciprocal sphere with a completeness of 99.9% and redundancy of approximately 7 were collected. Final unit-cell parameters were refined using the SAINT program  in the range 8° < 2θ < 81°: a = 9.8348 (3) Å, b = 18.0035 (6) Å, c = 5.2825 (2) Å, β = 104.9961 (8)° and V = 903.47 (2) Å3. The associated intensities were processed and corrected for Lorentz and background effects plus polarization, using the APEX2 software program . No violation of C2/m symmetry was detected.A representative crystal fragment (0.21 × 0.22 × 0.31 mm) of the Merelani amphibole was selected for X-ray diffraction measurements on a Bruker KAPPA APEXII single-crystal diffractometer , equipped with a CCD area detector  and a graphite crystal monochromator, using MoSHELXL2013 program , was modelled using the K/K+ scattering factor. The occupancies of the M and M(4) sites were obtained considering the presence of Mg/Mg2+ and Ca/Ca2+ scattering factors, respectively. The T(1) site was first modelled with Si/Si4+ scattering factors, and subsequently its occupancy was fixed to [(Si versus Si4+)0.83Al0.17)] = 1.00, that is, the value obtained from the empirical structural formula (see below) and with the Al scattering factor. The T(2) site was modelled with Si/Si4+ scattering factors and a fixed occupancy of 1. The anion sites were modelled with O/O1−/O2− scattering factors and a fixed occupancy of 1. A final refinement was then done by modelling the site occupancy of the O(3) site with O and F fixed to the values obtained from the empirical formula (see below). Hydrogen site occupancy was also constrained to be equal to the O one.Structure refinement was done using the A key issue in such an atomic model is the type of scattering factors used for the refinement. In detail, nine different SREFs were done using the following combinations:a) Neutral O (O0) SC ;(b) O0 and fully ionized SCs of cations at the M  and A sites (K+);(c) O1− SC;(d) O2− SC;(e) Optimized Ox− SC arising from:(2− versus O1− SC refinement and(i) O2− versus O0 SC refinement ;(ii) Of) Optimized Ox− and Six+ SCs in the case of(2− versus O1− SC refinement and(i) O2− versus O0 SC refinement .(ii) Og) Optimized Ox−, Six+ SCs and fully ionized SCs of cations at the M  and A sites (K1+) in the case of(2− versus O1− SC refinement and(i) O2− versus O0 SC refinement.(ii) O2− versus O1− or O0), and ionized versus neutral species for cations at T (Si4+ versus Si0) through the FVAR instruction in SHELXL2013. The coefficients for analytical approximation to the scattering factors were taken from Table 6.1.1.4 of the International Tables for Crystallography  site, whose anisotropic displacement parameters were refined to reasonable values. Moreover, in the electron-density synthesis with coefficients (Fo − Fc), all SREFs showed highest peaks (0.6–0.7 e− Å−3) at ca , corresponding to the position of the A(2) site in the amphibole structure. However, refinements with the A site split into A(m) and A(2) failed. Therefore, the A sites were modelled only as an A(m) site. Finally, a smaller peak (0.5 e− Å−3) was also observed at , corresponding to a split M(4)′ site, but any attempt to refine it failed. It should be noted that the presence of M(4)′ is strictly related to the B constituents  = 0.023 a.p.f.u. (atoms per formula unit), as reported in the present chemical formula.The starting structural model included a single M and A sites obtained as a function of the different combinations of SCs. Table 3 lists the variation in equivalent and isotropic displacement parameters for the various SREFs. Relevant bond distances are reported in Table 4 and the results of the cation site population in Table 5. Finally for the single-crystal data, Table 6 lists statistical indicators, the highest peak and deepest hole from the electron-density synthesis with coefficients (Fo − Fc), ionic charges (ICs) for O and Si, and site scattering (SS) of tremolite as a function of different 2θmax from OOSC SREF.Table 2 reports statistical indicators, the highest peak and deepest hole in the difference Fourier synthesis, ionic charges (ICs) for O and Si, and SS at the 3.3.Kα[Cu Kα1] radiation.X-ray powder diffraction (XRPD) data were collected on a Bruker AXS D8 Advance instrument operating in θ/θ geometry in transmission mode. The instrument is equipped with focusing multilayer graded (Göbel) mirrors located along the incident beam and Soller slits on both incident (2.3° opening angle) and diffracted  beams. Intensities were collected using a VÅntec-1 position-sensitive detector (PSD) set at an opening angle of 6° 2θ. A fragment of the large crystal of tremolite was selected for XRPD. The fragment was gently ground, in ethanol, in an agate mortar and the resulting powder was loaded into two 0.7 mm diameter borosilicate-glass capillaries that were fixed to a standard goniometer head and aligned. Two capillaries were prepared to check for data collection reproducibility. Data were collected in the 5–145° 2θ angular range, with a 0.0218° 2θ step size and 10 s counting time using Cu TOPAS6 ′ site, in agreement with SREF. On the basis of the SREF information (see below), Ti4+ can be identified as a C cation and allocated at the M(1) site. This assignment requires the application of the substitution mechanism M(1)Ti4+ + 2WO2− → M(1) + 2W(OH)− that reduces the amount of (OH) at the O(3) site  = 2.000 a.p.f.u. and 24 anions (Table 1The present yellowish–green amphibole sample from Merelani (Tanzania) is chemically homogeneous, as indicated by the small standard deviation values of the EMPA data Table 1. Crystals Table 1.et al. Σ0.290B(Ca1.945Mn2+0.016Mg0.032Fe2+0.007)Σ2.000C(Mg4.580Al0.343V0.040Cr0.007Ti0.030)Σ5.000T(Si7.320Al0.680)Σ8.000 O22W(OH1.609F0.331O0.060)Σ2.000.2Mg5Si8O22(OH)2, with ca 30% component of fluorpargasite, ideally NaCa2(Mg4Al)(Si6Al2)O22(F)2.This composition corresponds to tremolite, ideally CaM sites (Table 5), the following empirical structural formula is proposed:Based on the SREF information and optimized cation distributions over the A(Na0.185K0.105)Σ0.290M(4)(Ca1.945Mn2+0.016Mg0.032Fe2+0.007)Σ2.000 [M(1)(Mg1.940Al0.030Ti0.030)Σ2.000M(2)(Mg1.740Al0.213V0.040Cr0.007)Σ2.000M(3)(Mg0.900Al0.100)Σ1.000] [T(1)(Si3.320Al0.680)Σ4.000T(2)(Si4.000)] O22O(3)(OH1.609F0.331O0.060)Σ2.000.A sites  and et al. , was also characterized by Fritz  al. 2007. These a4.2.Ueq , that were used in the present SREF. The shaded area delineates the extension of the experimental data set collected, which spans from ca 0.055 to 0.91 Å−1. As can be seen, differences between the various curves occur at both ends of the range.Fig. 2T(1) site population for models (a)–(e) led to significantly different results, as shown by the Si amounts varying from 2.3 (1) a.p.f.u. for the NOC model to 3.48 (9) a.p.f.u. for the O2− model and to 3.08 (8) a.p.f.u. for the OOC model. Owing to the occurrence of correlations larger than 0.8 between the refined site occupancy factors and displacement parameters in the correlation matrix of SHELXL, the population at T(1) was fixed to that of the structural formula. As far as the population at T(2) is concerned, we decided to consider this site as occupied by Si as no conclusive evidence was observed pointing towards the presence of T(2)Al.Attempts to refine the wR2 values ranging from 0.0314 to 0.0517. The highest wR2 indices (>0.0373) are associated with models (a), (b), (c) and (d), whereas models (e), (f) and (g) have smaller wR2 values (<0.0347), despite the different combinations of SCs used  site. As a consequence, no significant correlation occurred between the O and Si SC optimization parameters of FVAR, nor between other structural parameters such as site occupancy factors (SOFs). As a further proof, all the SREFs were repeated after significant modification of the starting parameters, obtaining convergence toward a unequivocal minimum.The two largest correlation matrix elements observed consistently in all the SREFs (0.71 and 0.79) only regarded the displacement parameters most disagreeable reflection listed in SHELXL  and A (K+) sites, as in model (b) associated with neutral O and Si SCs and model (g) coupled with optimized O and Si SCs, resulted in SS values almost identical to those obtained with neutral SCs, except for the A(m) site. In that case, fully ionized SCs produced a small increase in the SS of ca 0.1 e− , M(4) and A(m), respectively. Switching from O0 to O1− and to O2− SCs  led to a progressive decrease in the wR2 values along with a regular increase, by ca 3% and 7%, in the SS at the M and A(m) sites, respectively. However, in model (d) the SS values at M were 0.9–1.3% higher than those obtained from the chemical formula , but a further improvement in terms of R indices was reached for model (f), in particular for O2− versus O0 SC optimization (OOSC), yielding the lowest wR2 value of 0.0314.A significantly better fit with the chemical data was obtained for model (2− versus O0 instead of O2− versus O1− in both models (e) and (f) not only produced a marginal reduction in wR2, but a significant difference in the IC values of O and Si. However, the use of such different combinations of SCs does not modify the SS values. It is worth noting that SS values at the M and A(m) sites obtained from model (e) were in excellent agreement with the chemical formula, while those from model (f) were only slightly smaller.The latter converged to ICs for O and Si of −1.288 and +0.887, respectively. As a general observation, refinement of O2− versus O0, instead of O2− versus O1−, are only apparently surprising. In fact, they can be explained by plotting f0 of O1−  sites of 61.05 (10) e−, in excellent agreement with 61.17 e− from the chemical formula. Note that the refinement with NOC led to a significantly lower SS value of 59.99 (14) e− for M  Table 2. The incAs far as bond distances are concerned, differences among the various refinements are within experimental uncertainty (last column of Table 4T(1)(Si3.32Al0.68) population, dictated by the chemical data, is in excellent agreement with the 0.60 a.p.f.u. Al, calculated from the equation of Oberti et al. (2007T(2) was considered to host exclusively Si. However, throughout the various refinements we consistently observed a higher Ueq for T(2) than for T(1). This feature could possibly be an indication of the occurrence of minor T(2)Al. By the evaluation of Fig. 11 of Oberti et al. (2007ca 0.1 T(2)Al a.p.f.u. might be estimated from the observed 〈T(2)—O〉 of 1.634 Å. However, due to the extremely large data dispersion, Oberti et al. (2007T(2)Al based on structure refinement.…we cannot presently provide a simple procedure to evaluate ’. Therefore, T(2) was assumed to be fully occupied by Si.With regard to the site populations, the  al. 2007:As pre al. 2007, a conte al. 2007 suggesteM site populations were derived from the OOSC values according to the procedure of Vignaroli et al.  site of both the SS values and the corresponding aggregate sizes of the constituent cations 〈Mr〉  sites. Aluminium shows the site preference M(2) > M(3) >> M(1), in agreement with the occurrence of 〈M(3)—O〉 mean bond distance shorter than 〈M(1)—O〉 mean bond distance , and V3+ and Cr3+ at M(2). Similarly, the M(4) site contains prevailing Ca plus minor amounts of Mg, Mn2+ and Fe2+, whereas A(m) hosts K and Na. Trace amounts of Na are also accommodated at the A(2) site, whose occurrence was detected from difference Fourier maps but not refined. The results of this iterative optimization procedure in terms of differences between the corresponding 〈Mr〉 values obtained from the observed bond distances and those calculated from the site populations are about 0.002 Å. Regarding the SS, the final site populations from OOSC SREF at the M sites produced SS values smaller by 0.33% than those obtained from the chemical data. The larger discrepancy (ca 0.2 e−) obtained for A(m) may be ascribed to the simplified description adopted for the A site, which yields an increase in the anisotropic displacement parameters, with Ueq up to 0.0516 (15) Å2, to compensate for static disorder and in turn a reduction in the SS value.The  al. 2014. This pr〉 Table 5. In deta2− versus O0, instead of O2− versus O1−, resulted in a marginal decrease in wR2 along with significant differences in the refined IC values for both O and Si. Moreover, while the IC values for O are very close to those observed in model (e), the IC values of Si are significantly higher, up to +1.730 for the refinement of O2− versus O0. This value agrees with the range of +1 to +2 reported by Hawthorne et al. (1995A(m) mentioned above.Of particular interest is the refinement done with OOSC and fully ionized SCs for non-tetrahedrally coordinated cations. As reported above, the refinement of O al. 1995 for Si if) and (g) provide the best description of the present tremolite structure. Although these models are very similar, model (f) provides better statistics, as indicated by the R indices.As a conclusion of this section, models (f) have been further investigated to different resolution limits of 2θmax: 81° (full data set), 75°, 70°, 65° and 60°  of model (° Table 6. The resFo − Fc); the highest peak consistently corresponds to the A(2) sites, whereas the second peak corresponds to the M(4)′ site only for 2θmax = 81°.(1) Progressive increases in the highest peak and deepest hole from the electron-density synthesis with coefficients ((2) Progressive decrease (from −1.378 to −1.288) and increase (from +0.776 to +0.887) in the ionic charges of O and Si, respectively.M and A(m) sites. In detail, the sum of the SS at M decreases from 61.28 to 61.05 e− for 2θmax = 60° and 81°, respectively.(3) Progressive decrease in the SS values at the max = 60°, moderate correlations occur between the principal axes of the ellipsoids describing the atom displacement parameters of the M sites and the corresponding site occupancy factors. For 2θmax = 81°, these correlations drop below 0.5.(4) Progressive reduction (not listed in Table 6M and A sites with increasing atom displacement parameters of the T and O sites.(5) Progressive decrease in the atom displacement parameters of the max = 81°. Differences from the refinement at 2θmax = 60° are within 3σ, thus showing a dispersion larger than that arising from different choices of SCs.(6) Progressive convergence of the bond-distance values towards those refined to 2θ4.3.Rietveld refinements of the data collected on the two capillaries provided fully reproducible structural data with differences within experimental uncertainty. Therefore, our discussion will focus on the results from one of the two samples only. Consistent with the type of experimental setup used, the spherical harmonics coefficients of the preferred orientation correction refined to very small values and they were remarkably constant for all refinements Table 7. This beRwp values of all refinements lay within the narrow range of 0.0290–0.0309. The lowest value was obtained by a combination of optimized SCs for both O and Si plus fully ionized SCs for non-tetrahedrally coordinated cations, that, as mentioned above, produce significantly overestimated SS at the various M sites. Therefore, it is clear that statistical indicators cannot be used as the only guide for selecting the best computational setup to perform such refinements. This is caused by the occurrence of several nearly equivalent  minima in the least-squares procedure. As in the case of SREF, we observed that refinement of O2− versus O0 SCs instead of O2− versus O1− SCs produced a general, minor, improvement of the fit. In a further analogy with SREF, passing from NOC to O2− SC has the effect of regularly increasing the SS at both M and A sites. Similar to SREF, individual and mean M—O bond distances are almost unaffected  and of individual T—O and M—O bond distances (〈ΔσBD〉) were ca 2.7 and 3.3, respectively. The total SS at M refined to 60.5 (2) e−, 0.5 e− less than that obtained from SREF and ca 0.7 e− less than that calculated from site partitioning using the EMPA data. This behaviour was previously reported and quantified by Ballirano et al. (2017M(2) was consistently found to be moderately underestimated. This is exactly the same result as obtained in the present refinement that shows an excellent fit with the EPMA data of the SS at M(1) and M(3).The NOC refinement produced a structure in excellent agreement with SREF. The mean differences from OOSC SREF, expressed in the form of the number of standard uncertainties (σ), of the SS at the  al. 2017 and Ball al. 2017. In partA(m) is higher than that obtained from both SREF and EMPA, but it represents the only significant discrepancy between the two structural data sets. Note that this behaviour is consistent with that observed in reference Rietveld refinements performed by our research group. In detail, we found minor electron density at A sites even in the case of virtually alkali-free tremolite samples, suggesting that this overestimation is actually an artefact. This effect could possibly be amplified, as observed in SREF, by the generalized use of simplified structural modelling of those sites [A(m) or A(2/m) and fixed/isotropic displacement parameters].The SS at T—O and M—O bond distances were within ± 0.009 Å of the corresponding value from OOSC SREF. The 〈〈rM〉〉 of 0.711 Å from Rietveld refinement is slightly larger than the value of 0.706 Å from OOSC SREF. We deliberately avoid any discussion of the behaviour of the individual and mean A(m)—O bond distances owing to the significantly higher associated standard uncertainties compared with those of the T—O and M—O bond distances.As far as bond distances are concerned, the mean Rwp and marginally alters the mean bond distances as 〈ΔσBD〉 is always close to 3.4. In the case of the refinement using the O1− SC, the results indicate a structure very close to that of NOC, albeit coupled to slightly higher agreement indices. The OOC refinement produced results intermediate between those obtained with O2− and O1− SCs. The 〈〈rM〉〉 reaches a value of 0.713 Å in the case of choosing OOC. In contrast, 〈ΔσM SS〉 increases progressively. This is predominantly due to the large rise in SS at M(4). Moreover, SS at A(m) increases as well.The use of increasingly reduced oxygen SCs produces a very minor increase in Rwp was marginally smaller at M, as was SS that reached a value of 60.3 (2) e−. In contrast, both M(4) and A(m) refined to higher SS values. Where OOSC performed significantly worse than NOC was in the case of 〈〈rM〉〉 that was calculated to 0.716 Å, a significantly higher value than 0.711 Å from NOC and, especially, than 0.706 Å from OOSC SREF.The OOSC refinement produced results similar to those of NOC. The value of M sites, whereas a better agreement than neutral ones was observed at A(m). The difference in the mean bond distances with respect to SREF 〈ΔσBD〉 was slightly higher that that observed in the case of the use of neutral SCs from non-tetrahedral cations, being close to 4.In the case of choosing fully oxidized SCs for non-tetrahedrally coordinated cations, as mentioned at the beginning of this section, they produced a very large overestimation of SS at Therefore, according to the present results, the use of NOC produces the best agreement with SREF structural data. However, a few regular behaviours were observed, confirming the findings of previous Rietveld refinements of fibrous amphiboles with the same experimental setup:M sites is consistently underestimated from Rietveld refinements and such underestimation is almost completely taken up by M(2). The underestimation is proportional to the total SS at the M sites  Total SS at the A site(s);(2) The ‘missing’ SS seems to be (partly) re-allocated at the T— and M—O bond distances are expected to be within ± 0.01 Å from SREF (in the present case 0.003–0.009 Å);(3) Mean T(2)—O(2)].(4) Discrepancies of individual bond distances (not reported) are obviously greater than those of the mean values and they could possibly be reduced by imposing restraints [maximum discrepancy in the present case 0.027 Å for 1.7−, in close agreement with SREF) produced better SS, and better displacement parameter modelling and agreement indices as well. This is possibly due to several concurrent reasons, such as the very limited superposition of reflections caused by the high symmetry and smaller absorption, which is generally better modelled than higher values, and a slightly extended 2θ range  and A(m) sites obtained from EMPA (105.07 e−) is closer to that obtained from the SREF model with partially ionized and neutral SCs (104.63 e−) than to that obtained from the SREF model with all neutral SCs (102.02 e−). Moreover, the experimental data should include, whenever possible, high-angle reflections (2θ > 60°) because they contribute to reducing correlation(s) and provide an improved description of the crystal structure.In the present study, we have shown that the interpretation of the electron density of the tremolite structure is model-dependent. As a valid constraint for the correct description of the model, we assumed that SS values from SREF should be as close as possible to those from EMPA. This assumption was best satisfied by using partially ionized SCs for O and Si, and neutral SCs for the other atoms, which also led to the best fit to the diffraction data. In this regard, it should be noted that the SCs used in SREF are calculated for isolated atoms or ions  sites, predominantly taken up by M(2), and to T— and M—O mean bond distances within ± 0.01 Å of the SREF values. However, before generalizing the obtained results to the analysis of fibrous amphiboles, some caution should be exercised. In fact, the analysed sample consisted of a chemically homogeneous fragment of a large gem-quality crystal. In contrast, large compositional variation is not uncommon in amphiboles when analysing fibres from a certain location. In fact, the term ‘suite’ has often been used to describe the large chemical variability observed at a few ‘classic’ locations, in some cases embracing as many as three amphibole species [e.g. Libby, Montana, USA  complexity of the diffraction pattern and the corresponding high number of freely refinable parameters, refinements performed with different combinations of SCs produced results almost indistinguishable from a statistical viewpoint. This is probably due to the correlation between absorption effects and the shapes of the various SCs, mutually compensating each other. Therefore, under the selected experimental conditions it is recommended to use NOC, which produced the closest structural representation of the tremolite sample compared with SREF in terms of both SS and bond distances. Those computational conditions led to an underestimation of the total SS at the etc.) but should go beyond that, providing refined SS values consistent with the chemical data. In this regard, it should be noted that the refined SS value can be interpreted in terms of atomic constituents only if the chemical information is incorporated into the interpretation procedure. The resulting crystal-chemical model  can hence be evaluated, for example, as the best match between the number of electrons obtained from SREF and EMPA data. Recently, Hawthorne et al.  tremolite, powder. DOI: 10.1107/S2052520621004844/yh5012tremolitesup2.hklStructure factors: contains datablock(s) tremolite. DOI: 10.1107/S2052520621004844/yh5012powdersup3.rtvRietveld powder data: contains datablock(s) powder. DOI: 2082220, 2082221CCDC references:


Multi-element two-dimensional (2D) materials hold great promise in the context of tailoring the physical and chemical properties of the materials via stoichiometric engineering. However, the rational and controllable synthesis of complex 2D materials remains a challenge. Herein, we demonstrate the preparation of large-area thin quaternary 2D material flakes via mechanical exfoliation from a naturally occurring bulk crystal named gillulyite. Furthermore, the anisotropic linear and nonlinear optical properties including anisotropic Raman scattering, linear dichroism, and anisotropic third-harmonic generation (THG) of the exfoliated gillulyite flakes are investigated. The observed highly anisotropic optical properties originate from the reduced in-plane crystal symmetry. Additionally, the third-order nonlinear susceptibility of gillulyite crystal is retrieved from the measured thickness-dependent THG emission. We anticipate that the demonstrated strong anisotropic linear and nonlinear optical responses of gillulyite crystal will facilitate the better understanding of light-matter interaction in quaternary 2D materials and its implications in technological innovations such as photodetectors, frequency modulators, nonlinear optical signal processors, and solar cell applications. This naturally stems from their unusual chemical and physical properties such as high surface-bulk ratios, dangling-bond-free smooth surface1, interlayer coupling, and unique electronic and optical responses3. Since the successful demonstration of creating stable monolayer and few-layers van der Waals materials in 20044, substantial efforts have been dedicated in exploring their prospects in advancing technological innovations ranging from energy storage to electronic and optoelectronic devices8. Nevertheless, the collection of the explored 2D materials is primarily confined to mono- and binary-element materials11 such as black phosphorous, bismuth, tellurium, antimony, GeS, GeAs, ReS2, and transition metal dichalcogenides. However, to meet the requirement of future electronic and optoelectronic technologies, it is imperative to expand the landscape of the existing library of mono- and binary-element materials to multi-element 2D materials12. Moreover, the induction of novel complex nanomaterials would also allow the increased adaptability and versatility of the 2D materials world. In recent years, multi-element 2D materials13 with their unconventional physical properties such as linear dichroism transition14, exceptional charge carrier mobility16, favorable band structure17, and bandgap transition have gained significant attention in the context of ultrafast photonics applications19. However, research on complex multi-element 2D materials is still in the nascent phase, and the fundamental understanding of their structural and electronic properties and other microscopic processes which affect the linear and nonlinear optical responses in these materials is very limited.Two-dimensional (2D) materials have paved an effective way for driving nanophotonics beyond the subwavelength scalemBnCp, in which A represents metals such as lead, silver, copper, tin, iron, manganese, mercury or thallium, B is semimetals like arsenic, antimony or bismuth, and C is sulfur or selenium21. Gillulyite is a thallium arsenic sulfosalt with miner antimony, with the idealized chemical formula of Tl28S13, which was found in 1991 at the Mercur gold deposit in Oquirrh Mountains, Tooele County, Utah and named in honor of the geologist James C. Gilluly22. Gillulyite occurs primarily as cleavable masses in vuggy barite and has a Mohs scale hardness of 2.0 to 2.5. Gillulyite is translucent and has a deep red to maroon color. It is worth noting that the crystallographic and structural properties of bulk gillulyite crystal have been studied, but the light-matter interaction correlated with the structural parameters of the crystal are still unknown. In general, thallium containing compounds are recently identified as potential materials for several important applications ranging from energy storage to security purposes such as thermoelectrics, laser frequency modulators, radiation sensors, and photovoltaics25. Therefore, the insightful understanding of light-matter interaction associated with the structural properties of these materials will be valuable for their engagement in technological improvisation. To address these issues, here we explore the anisotropic linear and nonlinear optical responses of mechanically exfoliated gillulyite thin flakes. It is noted that although CVD-grown thin films have been developed to a level of centimeter-scale size, the CVD-based growth of large-size thin films of multi-element layered materials with rational and controllable chemical compositions is still an unaddressed issue. As an alternate, naturally occurring multi-element vdW layered minerals pave an interesting way to prepare ultrathin flakes via mechanical exfoliation. However, in general the mechanical exfoliation of these naturally occurring bulk crystals in the large-size range of tens of micrometers is difficult. Here, we demonstrate that it is relatively easy to mechanically exfoliate the naturally occurring bulk gillulyite crystal into large-area thin flakes with sizes of tens of micrometers down to deep-subwavelength scale thicknesses. We further characterize the gillulyite crystal using high-resolution transmission electron microscope (HRTEM) and energy dispersive X-ray spectroscopy (EDXS) techniques to determine the structural and chemical composition information. Subsequently, the anisotropic vibrational and linear optical properties due to the low in-plane lattice symmetry are probed using polarization-resolved Raman and optical absorption spectroscopy. Furthermore, the anisotropic THG response of gillulyite crystal with respect to the incident linear polarization of pump beam is investigated and the third-order nonlinear susceptibility is retrieved from the thickness-dependent THG emission. To obtain further intuitive understanding, the third-order nonlinear susceptibility tensor elements are also estimated by corroborating the measured THG signal with a theoretical nonlinear model. These results will facilitate the fundamental understanding of light-matter interaction in quaternary 2D materials and advance future technological innovations in photonics and optoelectronics such as photodetection, frequency conversion, nonlinear optical signal processing, and photonic circuits.Motivated by this, herein we introduce gillulyite as a new type of sulfosalt-based anisotropic 2D layered materials to further expand the currently existing 2D material library. In general, sulfosalts are complex mixed-metal chalcogenides with the general composition AP2/n and the unit cell dimensions of a = 9.584 Å, b = 5.679 Å, c = 21.501 Å, α = γ = 90° and β = 100.07°. Figure b-axis and a-axis. The crystal structure of gillulyite can be described by two alternating Tl-containing A layer and PbS-like B layer along the c-direction28. In the Tl-bearing A layer with partly zeolitic character, TlS5 and As2S5 groups alternate regularly along the b-direction. The B layer can be described as a substantially distorted PbS-like motif which is periodically twinned by insertion of another  polyhedron, and is filled with lone electron pairs and weak interactions. The order–disorder phenomena happen along the b-direction which is caused by ambiguity in the position of TlS5-As2S5 sequences. Complex loop-branched zigzag 4S7 double-chains of AsS3 pyramids are formed along the a-direction in the B layer of gillulyite. It is noted that the crystal structure of gillulyite is homeotypic with those of gerstleyite Na28S13⋅2H2O29 and ambrinoite 28S13·H2O30. The weak interactions in the B layer of gillulyite will lead to a small interlayer cohesive energy, indicating the suitability for mechanical exfoliation of the bulk mineral.Gillulyite belongs to the monoclinic crystal system with space group Figure 7.89As7.80Sb1.00S13.00. The accuracy of EDXS estimation method depends upon several important factors such as the nature of probed specimen, the overlap in X-ray emission peaks, and the detection efficiency. Noticeably, the overlap in X-ray emission peaks is a crucial factor under the same operating condition. In our measurements, the X-ray emission peak of thallium is observed at 2.27 keV, whereas the corresponding sulfur peak is detected at 2.31 keV. In the EDXS spectrum, the elemental yield is estimated as per area under the curve for the respective emission peak. Since these two peaks are significantly overlapping with each other, the estimated quantifications of thallium and sulfur with EDXS may not be precise. We anticipate that this is the major reason for the overestimation of thallium abundance and the underestimation of sulfur in the probed specimen. As a result, the empirical formula determined from the EDXS spectrum is not the excellent match with the generic gillulyite chemical formula of Tl28S1322. Besides, small deviation between these two formulas can be attributed to their geological origins and the presence of carbon (C) and oxygen (O) impurities in naturally occurring minerals. Moreover, such deviation between the empirical and generic formula have been observed in previous studies on naturally occurring 2D materials as well32.Next, the gillulyite crystal is characterized using HRTEM and EDXS techniques to investigate the structural and chemical composition information. Figure -1 frequency range, which has evident spectral similarities to the Raman spectra from other thallium arsenic sulfosalts such as lorándite TlAsS2, fangite Tl3AsS4 and rebulite Tl5Sb5As8S22, as well as close to the Raman spectrum of orpiment As2S3, arising from the presence of AsS3 trigonal pyramids in the crystal structures34. The Raman bands between 400 and 220 cm-1 include the characteristic four vibrational modes from ν1 to ν4 of the isolated and interconnected AsS3 pyramids with band energies of ν1 > ν3 > ν2 > ν4. The modes in the 400–330 cm-1 region represent the symmetric and antisymmetric As-S stretching vibrations of ν1 and ν3, which might overlap to each other or are very close in energy. The modes in the 325–225 cm-1 region are the S-As-S bending vibrations of ν2 and ν4, where the out-of-plane bending vibrations occur above 290 cm-1 and the in-plane bending vibrations appear in the low energy range. The Raman bands below 220 cm-1 originate from the lattice vibrational modes.In order to understand the vibrational modes in gillulyite flakes, the polarization-resolved Raman spectroscopy is conducted on the 89 nm-thick flake in parallel polarization configuration. Figure g modes can be written as35a, b, c, and d are the amplitudes of Raman tensor elements, and g modes as follows35-1. The experimental data are denoted as black squares, whereas the theoretical fitting is shown with red solid lines, indicating a good agreement with each other. All the Ag modes show anisotropic two-lobe patterns with the Raman intensity maxima either at 0° and 180° or 90° and 270°. Moreover, the orientation of Ag modes in parallel polarization configuration indicates the crystal axis of the investigated gillulyite flake36. Here, the 0° and 90° directions are acknowledged as the a-axis  and b-axis  of gillulyite crystal, for further analyzing the anisotropic linear and nonlinear optical properties of the crystal. It is worth noting that the effects of glass substrate on the observed anisotropic Raman modes from gillulyite crystals are negligible , transmittance (T) and absorbance (A = 1 − R − T) spectra for these two gillulyite flakes, by keeping the incident linear polarization fixed along x-axis of the probed crystal. It is found that the reflectance is higher for the relatively thick flake (89 nm), whereas the transmittance is higher for the thinner flake (56 nm). Interestingly, the reflectance spectra from both flakes show a gradual decrement with a dip around 725 nm, whereas the transmittance increases monotonously within the range of 450 nm to 800 nm. The reflectance dip around 725 nm results in an absorbance peak shown in Fig. 37. To further investigate the anisotropic features of optical absorption and linear dichroism, polarization-resolved reflectance, transmittance, and absorbance spectra are systematically measured for the 89 nm-thick gillulyite flake, as shown in Fig. x-axis of the crystal. The polar plots of reflectance, transmittance, and absorbance spectra as a function of the linear polarization angle at two different wavelengths of 500 nm and 700 nm are further displayed in Fig. x-axis and y-axis. The obtained reflectance, transmittance, and absorbance anisotropy ratios at 500 nm (700 nm) are Rx/Ry = 1.25 (1.35), Tx/Ty = 0.82 (0.89), and Ax/Ay = 0.65 (0.86), respectively. It is indicated that the gillulyite crystal absorbs photons anisotropically along the directions of a-axis (x-axis) and b-axis (y-axis), exhibiting strong wavelength-dependent linear dichroism effects. It is noted that the effects of glass substrate on the reported transmittance, reflectance, absorbance values and the linear dichroism from gillulyite crystals are negligible  and perpendicular (90°) to the crystal’s a-axis.The reduced in-plane symmetry in gillulyite crystal also suggest the high anisotropic nonlinear optical response. The anisotropic THG emission in gillulyite flakes is probed using a 1560 nm pulsed laser with the beam waist of 1.5 µm. Figure a-axis (x-axis), while the secondary maxima is recorded at 90° and 270° along the crystal’s b-axis (y-axis). The measured x-component, y-component and total THG power data points are represented as red squares, blue dots and black upper triangles, respectively, which are further corroborated with the theoretical third-order nonlinear susceptibility model. The third-order nonlinear susceptibility tensor for a monoclinic crystal can be written as follows39x, y and z respectively and the second subscript refers to the combination of three components asFigure a-axis. Also, the incident pump beam resides only in the x–y plane, therefore the third-order nonlinear susceptibility tensor elements containing z-components can be neglected. Hence, the THG intensity components can then be written as 41Taken the experimental configuration into account, the incident linearly polarized pump beam can be expressed as Equation  and 5)  5) are u2 peak irradiance. The recorded THG emission power gradually increases up to 0.74 pW for the 133 nm-thick gillulyite flake and then decays exponentially. This thickness-dependent THG emission process can be explained in the context of two competitive phenomena of optical gain and loss. In case of the thin flakes, the collected THG emission is proportional to the square of the flake thickness, so that the THG emission power increases for the flake thickness up to around 149 nm. Afterwards, for the thick flakes greater than 149 nm, the optical absorption starts playing a dominant role in attenuating the THG signal propagation, which leads to the exponential decay. The exponentially decayed THG emission further enables us to extract the imaginary part of refractive index (k3) at A is a constant, d is the flake thickness. Figure k3 = 0.549. It is worth noting that the real parts of refractive indices of gillulyite correspond closely to those of fangite, in which n3 = 2.81 at 589 nm and n1 = 2.60 at 1553 nm42. Hence, by considering these refractive index values and other experimental parameters of average pump power τ = 90 fs, repetition rate W = 1.5 µm at the fundamental wavelength 43Additionally, the theoretical fittings enable us to retrieve the relative magnitudes of nonlinear susceptibility tensor elements –20 m2/V2.With the real parts of refractive indices of gillulyite crystal In summary, we have demonstrated the mechanical exfoliation of large-area thin gillulyite flakes of various thicknesses. The structural and chemical composition information of gillulyite crystal has been characterized using HRTEM and EDXS techniques. The anisotropic linear and nonlinear optical properties of gillulyite thin flakes due to the reduced in-plane crystal symmetry have been investigated. The anisotropic Raman modes and linear dichroism have been probed using polarization-resolved Raman and optical absorption spectroscopy. The anisotropic THG emission process in gillulyite crystal has also been explored with the extracted third-order nonlinear susceptibility. In the line of these findings, our presented discussion of gillulyite crystal in the context of anisotropic structural, vibrational, and optical properties will facilitate an insightful comprehension of the light-matter interaction in thallium-contained complex 2D materials as well as pave the way for its implications in photodetection, laser frequency conversion, nonlinear optical signal processing, encrypted optical communication, and photonic circuits.Finally, the uniqueness in gillulyite crystal structure facilitates an exceptional platform for the wide range tunability of vibrational, optical and electronic properties by comparing with its component binary sulfides via stoichiometric engineering and heteroatoms doping, which will advance many technological innovations. As one thallium-containing sulfosalt compound, gillulyite can be identified as a potential 2D material for realizing several unique applications ranging from thermoelectrics, frequency modulators, to spintronics and radiation sensors. The demonstrated mechanically exfoliated large-area thin gillulyite flakes offer a convenient platform for ultracompact multifunctional flatland optical, electronic and optoelectronic integrated devices, because rational and controllable synthesis of such complex 2D materials remains a challenge till date. Besides, the demonstrated polarization-sensitive vibrational and optical responses in gillulyite crystals indicate that the input polarization can be harnessed as an optical switch in applications such as phonon-based frequency modulation, polarized photodetection, encrypted data transfer, and nonlinear signal processing. With this hindsight, we anticipate that vdW layered sulfosalt mineral gillulyite truly has the potentials to be applied into future integrated photonic, electronic and optoelectronic technologies.2 gas. This pretreatment of the glass substrate is repeated several times to ensure the removal of undesired residues on the glass substrate. Further, the glass substrate is heat treated at 150 – 170 °C for 5 min to remove any remnant solvent on the glass surface. In the second step, gillulyite flakes are mechanically exfoliated using Nitto tape (SPV 224) from naturally occurring bulk gillulyite mineral . As the mechanical exfoliation process is a top-down method, it requires multiple efforts to attain the flake thickness of sub-hundred nanometer scale. After completing the exfoliation process, the gillulyite thin flakes are transferred to the pretreated glass substrate followed by heat treatment at 120–130 °C for 2 min. Then, the exfoliated flakes are examined using optical reflection and transmission microscope, and atomic force microscope for estimating the flake thickness. This procedure is repeated multiple times till the desired flake thickness range is obtained. In the view of this, the mechanical exfoliation process can certainly control the thickness range of the prepared flake.The sample preparation process involves two steps. In the first step, the glass substrate with 1 cm × 1 cm is treated with deionized water, acetone and isopropanol, followed by ultra-sonication and dried with NThe sample is illuminated with a 632.8 nm He–Ne laser using a 40 × objective lens (NA = 0.65) and the back-reflected signal is collected to a spectrometer  with a beam splitter. The polarization of incident beam is controlled by introducing a linear polarizer and a rotating half-wave plate in the excitation path. The elastic scattered light is filtered out by engaging an edge filter  in the collection path. The collected signal is further passed through a linear polarization analyzer to record the parallel polarization component of the Raman signal.R) and transmittance (T) spectra, so that the absorbance (A) spectrum is obtained with A = 1 − R − T.A broadband white light source  is passed through a linear polarizer and focused on the sample with an 80 × objective lens (NA = 0.5). To record the reflection spectra, the back‐reflected light is routed to the spectrometer using a beam splitter, whereas in the case of the transmission spectra, the transmitted light through the sample is collected using another 100 × objective lens (NA = 0.7). The reflection and transmission spectra are normalized with respect to the light source spectrum to obtain the reflectance  using a 40 × objective lens (NA = 0.65). The transmitted THG signal through the sample is collected by a 100 × objective lens (NA = 0.7). The pump beam is rejected by introducing a shortpass filter in the collection path. The THG signal is then routed to a spectrometer  and an imaging camera for recording the spectra and corresponding image.Supplementary Information.


Moreover, a comparison with theisostructural and more stable decaniobate(V)  was carried out. Fourbinding sites were identified, named α, β, γ, andδ, the site α being the catalytic nucleotide site locatedin the cleft of the enzyme at the interface of the subdomains II andIV. It was observed that the site α is preferred by V10, whereas Nb10 is more stable at the site β; thisindicates that, differently from other proteins, G-actin could contemporaneouslybind the two POMs, whose action would be synergistic. Both decavanadateand decaniobate induce conformational rearrangements in G-actin, largerfor V10 than Nb10. Moreover, the binding modeof oxidovanadium(IV) ion, VIVO2+, formed uponthe reduction of decavanadate(V) by the –SH groups of accessiblecysteine residues, is also found in the catalytic site α with coordination; this adduct overlaps significantlywith the region where ATP is bound, accounting for the competitionbetween V10 and its reduction product VIVO2+ with ATP, as previously observed by EPR spectroscopy. Finally,the competition with ATP was rationalized: since decavanadate prefersthe nucleotide site α, Ca2+-ATP displaces V10 from this site, while the competition is less importantfor Nb10 because this POM shows a higher affinityfor β than for site α. A relevant consequence of this paper is that other metallodrug–proteinsystems, in the absence or presence of eventual inhibitors and/orcompetition with molecules of the organism,could be studied with the same approach,suggesting important elements for an explanationof the biological data and a rational drug design.The experimental data collected overthe past 15 years on the interactionof decavanadate(V) (V 10) and decaniobate(V) (Nb10). Among the binding sites,V10 prefers the catalytic nucleotide site(site α), while Nb10 prefers the site β.ATP prevents mostly the binding of V10 than Nb10, competing with decavanadate for the site α.Four putative binding sites in globular G-actin were identified for two biologicallyactive polyoxometalates (POMs): decavanadate(V) (V Potential antitumor drugs basedon Pt, Ru, and Cu, antimicrobial and antiparasitic agents based onSb, Ag, As, and Fe, antiarthritis on Au, antiulcers on Bi, and antiviralsbased on Co and Hg were proposed. In addition, diagnostic metallodrugsof Gd, Tc, and In were also developed.4 Instrumentalmethods often give only information about the biological effects ofa metallodrug after the binding with a target protein but presentsevere limitations to unveil the type of interaction and the bindingmodes and sites or to ascertain the competition between the metallospeciesand other biomolecules of the organism.Interaction with proteins plays a crucial role in the transportand activity of metallodrugs in the organism, both for their highaffinity toward the metals or high concentration in the bloodstreamand cellular environment. Unfortunately, in most of cases, the experimentaldata cannot be rationalized through a description at the molecularlevel of this interaction.10O286–;V10) and decaniobate  are members of a large family ofpolyanionic clusters formed by group V and VI metals that are knownas polyoxometalates (POMs). POMs have been found to have a wide rangeof biological activities such as antidiabetic, antibacterial, antiprotozoal,antiviral, and anticancer, which have sparked interest in their useas bioinorganic drugs.5 Recently, it hasbeen demonstrated that POMs function as indirect activators of a Gprotein-coupled receptor.6 Moreover, POMshave also seen applications in other fields of research such as aerobicoxidation of starch, smart glasses, solar-driven photocatalysis, proteincrystallography, and synthesis of metal–organic frameworks(MOFs);7 for example, Nb10 canbe used as building block to prepare 1D, 2D, and 3D frameworks.8Decavanadate (VHelicobacter pylori and Streptococcus pneumoniae.5e The activity of POMs are found to be bacteria-dependent:for Streptococcus pneumoniae the mostactive POMs were polyoxovanadates (POVs), especially V10, while for Helicobacter pylori mostof POMs are effective.5eBased on an analysis of the antibacterialactivity and POM structures,putative mode of actions toward potential targets were suggested anda structure–activity relationship was determined for a seriesof POMs against 9 In many cases, these POM-associatedbiological activities are the result of POM–protein/enzymeinteractions, which are mainly of electrostatic nature as evidencedby crystallographic studies showing that the negatively charged metalclusters are generally found within or at positively charged regionsof proteins.10 However, also covalent interactionsbetween biomacromolecules and POMs are possible.11 In this scenario, the inhibition of certain enzymes by POMs cantrigger the impairment of vital cell functions.11The groupof Aureliano extensively studied the influence of POMs,especially POVs and polyoxotungstates (POTs), on diverse biochemicalmechanisms.12 Globularactin , the actin monomer, is one of the most abundantproteins in cells, being involved in numerous cellular processes.Previously, it was shown that V10–G-actin interactionaffects the protein structure and dynamics and also influences itstransformation to filamentous actin .11 Combining our experience regardingV10–G-actin system15 and our expertizes in computational characterization of metallospecies–proteinbinding,16 we further pursue the interactionbetween decavanadate and G-actin to deduce potential targets and providepossible modes of the biological activity of POMs.Among the possible cellular targets for POMs, actins are worthbeing considered. Actins are found in all life kingdoms and are responsiblefor many biologically essential processes, such as muscle contraction,cell adhesion, division, and migration, thus assigning them importantroles in health and diseases.10 and Nb10 being isoelectronicand isostructural isopolyoxoanions, V10 is redox-activeand labile in aqueous solution, while Nb10 is kineticallyinert and redox stable.17 Although therehas been growing interest in niobium chemistry in the past decade,research on decaniobate and its interplay with biomolecules and/orbiological effects is still scarce.19 In the systems with Ca2+-ATPase, Nb10 prevents the binding of V10, suggesting the sametarget(s) in the protein structure;18 moreover,both of them cause comparable conformational changes.19 In addition, Nb10 constitutes an excellent model to explorethe interplay between its V10 analogue and biologicallyvital proteins such as actin.Despite V10–G-actin interactions and the possibleinvolvement in protein polymerization is lacking. In fact, the exactmechanism of action of POMs is still elusive and thus also the POM’starget enzymes, which are responsible for the observed biologicaleffects. Molecular modeling could represent a valid tool to fill thisgap and help to understand cellular processes providing valuable cluesfor the rational design of new metal-substituted POMs with specificinteraction properties, pushing forward the comprehension of the molecularevents governing POMs–protein binding. Even though the computationaltechniques have been largely applied to study the chemistry of POMs,20 only few examples of molecular modeling applicationto POM–protein interaction have been published so far.21Even though some studies wereperformed on the systems containingPOMs and actin, up to now the detailed knowledge of the molecularbasis of V10–G-actin systems, collected over the past yearsin the literature, and compare the findings with the isostructuralNb10. In particular, the aims of this study are (i) toattain an understanding, at the molecular level, of the interactionof V10 and Nb10 with G-actin starting from theavailable results already obtained by several spectroscopic techniques;15 (ii) to fully characterize the binding sites of G-actinfor V10 and Nb10, determine the number and typeof neighbor atoms around POMs, and evaluate their stabilization throughsecondary interactions; (iii) to compare the behavior of V10 and Nb10; (iv) to predict the binding site(s)of the reduction product of V10, the oxidovanadium(IV)ion, VIVO2+; and (v) to study the V10/Nb10–G-actin system in the presence of ATP to obtain amore accurate description of the mechanisms involved and possible competition/inhibitioneffects.On the basis of these premises, in thispaper we tried to rationalize—usingseveral computational approaches—the experimental data on theV10O286– and Nb10O286– geometry and harmonic frequencieswere computed through Gaussian09 (revision D.01)22 by using the B3LYPfunctional including Grimme’s empirical correction for dispersion.23 V and Nb atoms were described with the scalar-relativisticStuttgart–Dresden SDD double-ζ basis set complementedwith f polarization functions and its associated pseudopotential.24 The 6-31g basis set was used for the oxygenatoms. The structures of POMs were optimized in water described bythe SMD continuum model.25 Point chargesof the complete POMs were derived with the RESP26  model. The DFT levelof theory and RESP model to assign the atomic charges were selectedfollowing the protocol proposed to derive AMBER and TIP3P force fieldsfor molecular dynamics (MD).27VIVO2+ ion and neighboring interactingamino acid side chains and freezing the backbone atoms as reportedby Siegbahn and Himo.28 The geometry relaxationand ΔE calculations were performed by usingthe doublet state in unrestricted simulations at the B3P86/6-311++g level of theory and describing water within the framework of theSMD model25 which gave excellent resultsfor other VIV–protein systems.29 For the geometry optimizationof VIV complexes, it was shown that B3P86 works betterthan other functionals like B3LYP.30 Frequencycalculations were computed to ensure that the structures were a minimumin the potential energy surface.Therefinement of the oxidovanadium(IV) adducts at the nucleotide site(site α), found by dockings, was performed by cutting out theregion with the V51V hyperfine coupling tensor A was performedon the optimized structures with Gaussian0922 by using BHandHLYP functional and6-311+g(d) basis set.31 The spin contaminationwas negligible, and the eigenvalue of the spin operator ⟨S2⟩ was 0.76 for all the calculations,very close to the exact value of 0.75. This is in agreement with theresults obtained for hybrid functionals.32 The theory background can be found in refs . The AMBER14SB force field37 wasused for the protein, while V- and Nb-bonding force constants andequilibrium parameters were obtained through the Seminario methodwith the MCPB.py.38 Ca2+-ATPparameters from Meagher et al.39 and Bradbrooket al.40 have been used.The apo form of monomeric actin,G-actin, was built by removing CaPDB: 3hbt). In the41 throughOMMProtocol.42During MDs,the solvent and the whole system were sequentially submitted to 3000energy minimization steps. Then, thermalization of water moleculesand side chains was achieved by increasing the temperature from 100up to 300 K. MDs under periodic boundary conditions were performedduring 200 ns with OpenMM engine36 The MD trajectorywas considered converged when a stable exploration of the conformationalspace was achieved; in particular, a stable conformation or a poolof relative stable conformations visited for a statistically consistentnumber of times were considered as convergence indicators.43 Considering the α carbons of the G-actinbackbone, the root-mean-square deviation (RMSD) from the minimizedstructure, all-to-all frames RMSD,44 andcluster counting45 analysis were performed.Moreover, to ensure that dynamic transitions occur between differentconformations, a principal component analysis (PCA) was performedplotting the two principal modes relative to each other.44 The quality threshold (QT) clustering algorithmwas used to generate representative clusters taking the RMSD betweenframes as distance metric.46 The representativestructure of the most populated cluster was used in the further structuralanalysis.Analysis of the trajectorieswas performed by means of cpptrajimplemented in ambertools16.47 on the most sampled structure coming from MD trajectories. G-actinwas docked with V10 and Nb10 optimized structuresconsidering the whole rigid protein.Docking calculations to the G-actinwere performed through GOLD 5.8 softwareIVO2+ moiety were performed through GOLD 5.847 on the regions selected in the preliminary analysisby BioMetAll,48 instructed to find latentbinding motifs with a minimum of two coordinating residues consideringHis, Asp, and Glu as potential donors. G-actin was docked with VIVO2+, VIVO(H2O)2+, and VIVO(H2O)22+ moieties,obtained from the optimization of the oxidovanadium(IV) aquaion, [VIVO(H2O)4]2+. The equatorialpositions were activated by replacing the equatorial water(s) withdummy hydrogen atoms according to what was recently established.16h All dockings were computed considering both the protonation statesat δ and ε nitrogens of the His imidazole ring. Geneticalgorithm (GA) parameters have been set to perform a minimum of 100000operations during 50 GA runs for covalent dockings and 100 GA runsfor non-covalent dockings. The other parameters of GA were set todefault. The scoring  was evaluated by applying the modified versions of GoldScorescoring function, which was validated in previous published papers.16e The best solutions (bindingposes) were evaluated through three main criteria: (i) the mean (Fmean) and the highest value (Fmax) of the scoring associated with each pose, (ii) thepopulation of the cluster containing the best pose, and (iii) theposition in the Fitness ranking of the computed cluster.Dockings of VGbind quantifiedby molecular mechanics-generalized Born surface area (MM-GBSA) includingquasi-harmonic correction for entropy.49 Average values have been obtained from 100 homogeneously distributedframes of the whole MD trajectories. The following parameters wereused: igb = 5 and saltcon = 0.100.The POMs docking solutions were refined sending for each best proposala 200 ns of MD and Δ10) interacts strongly with G-actin.50 However, up to now,even if the biological effects are clear, the binding site(s) werenot determined, and this datum is lacking in the literature. Nevertheless,this information could be important and related to the subsequentreduction process to the oxidovanadium(IV) cation, VIVO2+,13 and could be very useful togain insight for the rational design of new metal-substituted POMs with specific interactionwith proteins.Experimental datareported so far pointed out that decavanadate anion , where the hydrolysis ofATP occurs,51 located in the cleft of theenzyme at the interface of subdomains II and IV; the site βat the interface of subdomains I and II; the site γ at the surfaceof subdomain III; and the site δ at the C-terminus in the smallcleft between subdomains I and III (Fmax) rangingfrom 24.8 to 36.4 Gold Score Fitness units. For thesite α, the pose (solution) with the best scoring is stabilizedby hydrogen bonds (H-bonds) with Arg207, Arg211, Arg62, Thr204, Gln59,and Tyr69 residues. The site β, with similar scoring, presentsH-bond with Lys68, Arg37, Lys50, and Lys84. The sites γ andδ show lower scorings and H-bonds with Arg147, Lys329, Thr148,and Asn297 or Arg113, Lys374, and Tyr170, respectively . However, since only slight differences in the behavior of V10 and Nb10 were observed, because of thesimilarity between the two structures, dockings can be useful at mostfor defining the possible binding regions but do not allow for ascertainingtheir relative affinities for the four sites. To move beyond dockingand obtain reliable values for ΔGbind for the two POMs, MDs were performed and residence time analysisand MM-GBSA calculations carried out.To throw light on the unknown aspects, in thefirst step a blind docking screening was performed on the equilibratedapo structure of G-actin, searching for putative binding sites forV and III 1a. Afterectively 1a. CompaFigure S2) indicated that V10 binding induced an openingof the G-actin cleft.13 Subsequently, in2011, the 1H NMR spectra of G-actin treated with V10 suggested that the latter causes major alterations in theprotein structure ;52 in contrast, no significant changes in the 51V NMR signalswere observed for other vanadates, such as monomeric  and tetrameric species.13 More recently, EXAFS and XANES experimentsestablished that the interaction  V10–G-actin triggers a protein conformational reorientationthat causes an oxidation of Cys residues and formation of the VIVO2+ cation  in the protein melting temperature could probably be dueto actin conformational changes and/or partial protein unfolding inducedby V10.53The change of actin conformationwas further confirmed by circulardichroism (CD) spectroscopy.10 and Nb10 bound to each of the four possible sites and compared withthe unbound state of G-actin. Concerning the site α, adductsare highly stable both for V10 and Nb10 duringthe whole explored trajectory (200 ns), and the folding of the proteinis generally retained. It must be noted that a slight opening of thenucleotide binding site is observed after the interaction with V10 and Nb10. Subdomain IV moves from subdomain IIto accommodate the POMs. This movement can be described with the angleφ, defined as C(α)Lys67–C(α)Val339–C(α)Thr203, which varies from28.6° (apo form) to 30.5° (Nb10–G-actin)and 35.6° (V10–G-actin)  3a. Thesepal axes3b,c.10 leaves the surface of subdomain III at 75ns and after 170 ns moves to the site β where it is stabilized,Nb10 forms a stable adduct during the whole trajectory.The H-bond network highlighted by docking is retained with the replacementof Thr148 with the positive side chain of Lys327 , the affinityof Nb10 for the sites α and β is comparable; this demonstrates a clear protection effect exerted byG-actin toward V10. The best binding site proposed by simulations,the nucleotide site α, shows characteristics compatible witha protective environment being buried into the catalytic cleft ofthe proteins, and able to form a H-bond network, beside electrostaticinteractions. Such interactions are strong enough to stabilize V10 into the pocket, preventing its exposition to the solventand putative decomposition, as previously suggested.11These results can rationalize the kinetic measurements of V10 with G-actin, a rigid-limit EPR spectrum is revealedwith eight resonances in the parallel region and eighth in the perpendicularone  to VIVO , probably through the reaction of decavanadate(V) withthe accessible −SH groups of cysteine residues. The most plausiblecandidates involved in the redox reaction are Cys272 and Cys374.55 The spin-Hamiltonian parameters for the adductformed upon the binding of VIVO2+ to G-actinare gz = 1.940 and |Az| = 177.1 × 10–4 cm–1;14 these valueswould indicate weak donors or—in agreement with the “additivityrelationship”, the empirical rule verified for a lot of VIVO complexes which allows to determine the 51Vhyperfine coupling constant along the z-axis, |Az|estmtd, from thesum of the equatorial donor contributions within ca. 3 × 10–4 cm–1 from the experimental value57—coordination of His residues with the aromatic plane perpendicularto the VIV=O bond.56 Atthe moment, the binding site and the residues interacting with VIVO2+ ion are not known; however, the effect ofthe addition of an excess of ATP  and , both ofthem displaying the ability to coordinate VIVO2+ in a square pyramidal arrangement ; Od Arg177 6a. The m28 and the QM binding energy was computed; finally, EPR spin-Hamiltonianparameters were calculated for the predicted sites. From an energeticpoint of view, both sites show negative ΔEbinding values, but that with  is favored bymore than 15 kcal mol–1. Its |Az|calcd (178.6 × 10–4 cm–1) matches well the experimentalvalue of 177.1 × 10–4 cm–1 measured by Ramos et al.14 Moreover,|Az|estmtd, estimated with the “additivity relationship”,57 is 178.4 × 10–4 cm–1, closerto the experimental one than that expected for  mode;the contributions of 45.1 × 10–4 cm–1 for His-N , 42.1 × 10–4 cm–1 for Asp-COO–, and 45.6 × 10–4 cm–1 forwater-O were used to determine |Az|estmtd.58The predicted structureswere refined at the full DFT level followingthe cluster method proposed by Siegbahn and Himo,IVO2+ and Ca2+-ATP results hindered for the steric clashes and electrostatic repulsioninto the enzymatic cleft , in the internal region of the site α, is the best candidateto explain the experimental EPR data collected so far. In fact, thesimultaneous binding of Vic cleft 6c.10 in solution,the addition of ATP to the medium has the opposite effect, decreasingits half-life from 27 to 10 h .11 This insight suggested, for the firsttime, that V10 and ATP could compete for the same bindingsite, ATP being more affine to its natural site and able to partiallydisplace V10 to a less protective and exposed binding region.Some years ago Aurelianoet al. showedthat, while G-actin increases the stability of V10 with ATP for thenucleotide site was further evidenced in 2009 by EPR and 51V NMR spectroscopy.13 The EPR spectrarecorded on frozen aqueous solution containing increasing ATP/V10 ratios in the presence and absence of G-actin indicated that V10 induces actin cysteine oxidation and formation of the paramagneticoxidovanadium(IV) ion, and both the processes are prevented by theaddition of ATP in solution , which are not or hardly visible inthe system with ATP, confirmed the competition between nucleotideand decavanadate in the critical binding site.50The possible competition between VTm, of 44.8 °C) than in thepresence of ATP , whose interaction results in two melting points which were extractedfrom recorded melting curves. Finally, recent EXAFS and XANES experimentsestablished that the interaction of V10 with G-actin triggersa protein conformational reorientation that causes an oxidation ofCys residues and formation of VIVO2+. The variationsinduced in V10’s EXAFS profile in the presence ofATP suggest that the nucleotide and V10 compete for thesame binding site , additional MD simulations were carriedout. ATP is found at the enzymatic cleft of G-actin in correspondenceof the site α and, in principle, could compete with V10 for this region. From a first MD of 200 ns, the binding of Ca2+-ATP to the site α is highly stable along the wholetrajectory. The ΔGbind of Ca2+-ATP to its biological site α is the lowest of theseries and is more favorable by 14.1 kcal mol–1 thanV10.Todeduce whether the native actin substrate (ATP) interferes withV1H NMR spectra ofG-actin recorded in the presence and absence of V10. Majoralteration patterns attributable to a protein conformational changeare negligible upon addition of ATP .52 Therefore, ATP could displace V10 from the site α, causing the closure of the cleftto its natural conformation and giving the normal pattern observedin 1H NMR experiments.It must be highlighted that the catalytic cleftis more closedthan the apo or POMs loaded forms with an angle φ of 22.0° cation, VIVO2+, and the aggregation of G-actin to form F-actin observedin recent EXAFS and XANES study.15As discussed above, the site β is found at the interfaceof subdomains I and II in the surface region of G-actin 1a. There10, being its affinity for the sites βand α comparable, the competition with ATP is less important;in fact, Nb10 can be hosted at preferred site β inthe presence of the nucleotide. Based on these consideration, no competitionbetween the two POMs and G-actin is expected  or V10 and Nb10 modes of action.Summarizing the obtained results, it was elucidated and compared atthe molecular level the behavior of Nb10 and V10 in the G-actin conformational rearrangements. Two putative V10/Nb10–actin binding sites were fully characterized:V10 prefers the catalytic nucleotide site (site α),whereas Nb10 is more stable at the site β. Therefore,in contrast with other proteins such as Ca2+-ATPase, theycould contemporaneously bind to G-actin, and their biological and/orpharmacological action could be synergistic. These findings shouldbe considered for other studies in inorganic medicinal chemistry,administering POMs or other potential metallodrugs compatible withthe same target protein, that is, with affinity for different sites,to amplify their action. Concerning the presence of the native actinligand ATP, it prevents the V10 binding to the site α,whereas it does not affect Nb10–actin interaction,since β is the primary site for decaniobate.For a careful application of POMs in biology and medicinethereis a great need for understanding which cellular proteins representthe potential targets, and often POMs–proteins interactiondid not get the attention it deserves. Specifically, regarding POMs–actinsystems described in this study, the computational approach has provento be an excellent tool to determine the binding sites and understandthe different VWe believethat the present paper will facilitate a deeper understandingof the role POMs in various applications, giving valuable insightfor a rational design of new metal-substituted POMs with specificinteraction properties toward the putative target proteins. In addition,it could be used as a “guide” for the study of the interactions–(cellular proteins) and of the phenomenaof inhibition and competition with the biomolecules at physiologicalconditions.Finally, an important outcome of this paper is thatother metallodrug–proteinsystems, in the absence or presence of eventual inhibitors and/orcompetition with molecules of the organism, could be studied withthe same approach, suggesting important elements to explain the biologicaldata and design more active and specific potential drugs.


The unprecedented sea ice loss of 2018 in the northern Bering Sea led to the export of a large bloom dominated by the exclusively pelagic diatoms Chaetoceros spp. at DBO2. Despite this intense bloom, early sea ice breakup resulted in shorter periods of enhanced chl a and diatom fluxes at all DBO sites, suggesting a weaker biological pump under reduced ice cover in the Pacific Arctic region, while the coincident increase or decrease in TPM and POC fluxes likely reflected variations in resuspension events. Meanwhile, the highest transport of warm Pacific waters during 2017–2018 led to a dominance of the small copepods Pseudocalanus at all sites. Whereas the export of ice-associated diatoms during 2019 suggested a return to more typical conditions in the northern Bering Sea, the impact on copepods persisted under the continuously enhanced transport of warm Pacific waters. Regardless, the biological pump remained strong on the shallow Pacific Arctic shelves.Unusually warm conditions recently observed in the Pacific Arctic region included a dramatic loss of sea ice cover and an enhanced inflow of warmer Pacific-derived waters. Moored sediment traps deployed at three biological hotspots of the Distributed Biological Observatory (DBO) during this anomalously warm period collected sinking particles nearly continuously from June 2017 to July 2019 in the northern Bering Sea (DBO2) and in the southern Chukchi Sea (DBO3), and from August 2018 to July 2019 in the northern Chukchi Sea (DBO4). Fluxes of living algal cells, chlorophyll  The Pacific Arctic marine ecosystem is extremely productive due to the persistent flow of nutrient-rich waters fueling high primary production on the shallow northern Bering Sea and Chukchi Sea shelves . Recentla (chl a), total particulate matter (TPM), particulate organic carbon (POC), and zooplankton fecal pellets were measured to monitor carbon export and the seasonal development of the algal bloom in relation to the drastic changes observed during the warm anomaly period. Zooplankton and meroplankton collected in the sediment traps were also identified to track spatial and temporal variations in the composition and development of these communities. The deployment of moored sediment traps represents an invaluable contribution to the DBO as they provided time-series integrative measurements of biological and biochemical parameters at a high temporal resolution during a period of rapid changes in the Pacific Arctic. As warm events are likely to increase in frequency under the current global warming scenario, time-series export fluxes measurements obtained during the 2017–2019 warm period contribute to a better understanding of conditions to expect for the highly productive marine ecosystems of the northern Bering Sea and Chukchi Sea.While results from several snapshot studies clearly indicated that a sudden shift of the Pacific Arctic ecosystem occurred during the anomalously warm 2017–2019 period, most biological measurements were limited to summer months . Fluxes http://cersat.ifremer.fr/). Daily sea-ice concentrations were averaged for a 44 x 44 km region above each mooring site (Daily averaged sea-ice concentrations above each mooring site were retrieved at a 12.5-km resolution from the Centre ERS d’Archivage et de Traitement (CERSAT) service of the French Research Institute for Exploitation of the Sea  to preserve samples during deployment and after recovery. The carousel holding the sample cups rotated at pre-programmed intervals ranging from one week to one month. As the mooring was recovered before the last rotation of the carousel at DBO2 in June 2018, the sample cup that was open upon recovery was excluded from analysis. Seabird SBE 16plus units were deployed to measure water temperature at three depths at DBO2 and DBO3 and at one depth at DBO4. The unit deployed at the upper depth on each mooring was coupled with a WETStar fluorometer or WET Labs ECO triplet fluorometer to measure fluorescence  were deployed at the DBO2 (N4) and DBO3 (N6) sites from June 2017 to July 2019 and at the DBO4  site from August 2018 to July 2019 . No natirescence .a, algal cells, fecal pellets, TPM, and POC. Subsamples for chl a measurements were filtered onto GF/F filters (0.7 μm), extracted in acetone for 24 h at -20°C and measured on a Turner Design fluorometer following the methods outlined in Welschmeyer [a measurements, but may have experienced some degradation. For the enumeration of algal cells, subsample volumes were adjusted to 3 ml with filtered seawater before being placed in an Utermöhl chamber. A minimum of 300 algal cells were counted and identified by inverted microscopy at 100X, 200X or 400X depending on cell size according to the Utermöhl method [-3 for copepod pellets and 0.042 mg C mm-3 for appendicularian pellets [In the laboratory, zooplankton and meroplankton were removed from subsamples with forceps and identified to the lowest taxonomic level possible using a dissecting microscope. Sample cups were gently mixed before subsamples (0.1–3 ml) were taken with a modified micropipette to enable the collection of large particles for measurements of chl schmeyer . Samplesl method . Using al method . Fecal p pellets . SubsampWhile sea ice was first detected in December 2017 at DBO2 and DBO3, a lasting sea ice cover only formed in January 2018 and sea ice concentrations temporarily decreased in February 2018 at both sites . At DBO2Mooring-derived water temperatures were above 2°C from June to November at all depths sampled at DBO2 and DBO3 . Water ta fluxes often coincided with increased suspended chl a concentrations recorded by the fluorometer 6 to 10 m above the traps, there were also notable differences between the two measurements  were sustained during approximately five weeks in 2018 and 2019 at DBO2, and during two weeks in 2018 and nine weeks in 2019 at DBO3. At DBO4, relatively low chl a fluxes peaked in early June 2019 (4.3 mg m-2 d-1) and remained above >1 mg m-2 d-1 until the end of the deployment in late July 2019.While enhanced chl urements . Peak cha fluxes, with peak diatom fluxes observed at the end of May and/or early June for every deployment cycle , with the exception of N. cristatus that is recognizable due to its large size compared to its congeners [Neocalanus was observed at DBO2 and DBO3 from June to August 2017  were observed in early June 2018 and from May to July 2019, except for a week at the end of May 2019. At DBO4, peak POC (~1 g m-2 d-1) and TPM fluxes (>50 g m-2 d-1) were recorded during the second half of May 2019. High POC and TPM fluxes were also observed during autumn and winter at all sites, often in November and/or December. FPC fluxes contributed most to POC fluxes between June and November at all sites, and sporadically contributed to the complete POC flux between August and October 2017 at DBO3  at the DBO sites, with POC fluxes consistently contributing to <7% of the TPM fluxes. Whereas enhanced fluxes in April or May most likely resulted from the release of particulate matter from the melting ice [A combination of downward export, lateral advection, and resuspension of particles contributed to the fluxes recorded at the three mooring sites of the shallow Pacific Arctic region. As typically observed on Arctic shelves , 30, TPMting ice , algal eting ice –34 and tting ice , 36. Diating ice .-1 during autumn 2017 at DBO2 and DBO3 [a concentrations, chl a fluxes, and diatom fluxes sporadically observed during late summer and autumn further support wind-induced resuspension and dispersion of sediments containing diatoms and chl a at the DBO sites. These observations are in agreement with enhanced near-bottom chl a concentrations observed during wind-induced high turbidity events during autumn near Bering Strait [25 and of diatoms containing chloroplasts throughout the polar night on the northeast Chukchi shelf [Zooplankton continuously collected at fixed depths indicated a strikingly similar composition of the dominant copepods at the three DBO sites, consistent with the large influence of advection on seasonal zooplankton dynamics in the Pacific Arctic , 38. Copand DBO3 . Short-lg Strait , 40, andhi shelf , 41. In a concentrations revealing the occurrence of a spring bloom during May 2017 at a nearby mooring site in the southern Chukchi Sea [Chaetoceros spp. and Thalassiosira spp. indicated that a pelagic bloom occurred in the DBO3 region during late June and July 2017. The subsequent frequent collection of the boreal diatoms Proboscia spp., cosmopolitan diatom T. nitzschioides, and endemic North Pacific diatom Neodenticula seminae [An earlier onset of warming and later onset of cooling in recent years lengthened the warm (≥0°C) water duration to more than 6 months in the Pacific Arctic region . In 2017kchi Sea . However seminae , 42, 43 Neocalanus during late June and early July 2017 highlighted an enhanced transport of warm Pacific waters, in agreement with concurrent observations of high abundance of Pacific copepods associated to the inflow of Anadyr Water during June and July 2017 in the northern Bering Sea [Calanus copepodites and nauplii indicated their decline under warm conditions, as supported by the report of a remarkably low abundance of Calanus in the Pacific Arctic during 2017 [Although zooplankton community composition and distribution have been shown to vary with water properties and the volume of Pacific water transported to the northern Bering Sea and Chukchi Sea , 44–47, a and diatom fluxes dominated by the exclusively pelagic diatoms Chaetoceros spp. and Thalassiosira spp. in late May clearly indicated the occurrence of a large open water bloom following the early sea ice breakup in the northern Bering Sea. While biofouling may explain the concurrent low chl a concentrations recorded at DBO2 at the end of May, high chl a and diatom fluxes at that time were in agreement with the peak near-bottom chl a concentrations recorded at a nearby mooring on May 20 2018 [Fragilariopsis spp., F. arctica, and Navicula spp. during the sea ice breakup period (sea ice concentration <50%) hinted at a limited ice algae production while ice still drifted in the region in April, inhibiting the seeding of the spring bloom [a and diatom fluxes composed of ice-associated and pelagic diatoms during early June, indicating that colder water temperatures, later sea ice melt, and stronger stratification led to an ice-edge bloom in the southern Chukchi Sea in contrast to the northern Bering Sea. The highest near-bottom chl a concentrations recorded in late May and early June 2018 at a nearby mooring in the DBO3 region [Residual heat from the elevated summer water temperatures delayed sea ice formation to December 2017 at both sites . At DBO2ng bloom  and likeng bloom , 50. At a and diatom fluxes mostly composed of Chaetoceros spp. and Thalassiosira spp. when sampling was resumed during June 2018 at DBO2 and DBO3 indicated a declining pelagic bloom at both sites. From July to September, the centric diatoms Thalassiosira spp. dominated the low diatom fluxes, a sharp contrast with fluxes composed of pennate diatoms Pseudo-nitzschia/Nitzschia spp., C. closterium, Fragilariopsis spp., F. arctica, and centric diatoms Chaetoceros spp. collected during the previous summer. This shift in flux composition concurs with a lower abundance of Chaetoceros spp. observed during July 2018 than during July 2017 in the Bering Strait region [Thalassiosira spp. in the low diatom fluxes during July 2018 possibly reflected a rapid depletion of nutrients during the large open water bloom taking place in the northern Bering Sea weeks earlier.Low chl t region . The larPseudocalanus while the abundance of Neocalanus and Calanus remained relatively low at both sites. As Pseudocalanus copepods are approximately three times smaller than Neocalanus and Calanus, their dominance supports observations of a zooplankton community dominated by small copepods during 2018 [Pseudocalanus, Acartia, and Oithona similis often dominate copepod abundance, large Calanus copepods often dominate biomass in late summer in the southern Chukchi Sea [C. glacialis females exploit ice algae to fuel their maturation and egg production [C. glacialis usually increase under colder conditions in the Bering and Chukchi Seas [C. glacialis under warmer conditions. The presence of the Pacific copepods Neocalanus, Eucalanus bungii and Metridia pacifica [Peaks in copepod abundance during late June at DBO2 and early July at DBO3 probably contributed to the low diatom fluxes observed in early summer through grazing pressure. Most of the copepods collected during June and July 2018 consisted of ing 2018 . While skchi Sea . As C. goduction , 52, thechi Seas , 54. Thepacifica , 44–46 fFragilariopsis spp., C. closterium, Pseudo-nitzschia/Nitzschia spp., Navicula spp., Thalassiosira spp., and Chaetoceros spp. at the onset of sampling in August 2018 corresponded to the ice-associated and pelagic diatom groups reported to dominate phytoplankton biomass during summer in the northern Chukchi Sea [C. closterium from August to October 2015 during a period of strong winds with frequent direction reversals [C. closterium and Leptocylindrus danicus [C. closterium fluxes remained low during autumn 2018 when sunlight was sufficient to induce primary production in the region. Peaks in copepod abundance recorded during late August and late September 2018 at DBO4 were dominated by small Pseudocalanus, similar to DBO2 and DBO3. The dominance of small copepods in the northern Chukchi Sea also resulted from a low abundance of C. glacialis under warmer conditions, as confirmed by Calanus that were ~5 times more abundant at DBO4 during August 2015 than during August 2018 while the abundance of Pseudocalanus was similar during both years [E. bungii and M. pacifica during August and September further illustrated the transport of warm Pacific waters into the Chukchi Sea. Most meroplankton collected during summer and autumn 2018 consisted of barnacle larvae, in agreement with observations of barnacle larvae contributing to the largest meroplankton biomass from 2008 to 2010 in the northeastern Chukchi Sea [At DBO4, low diatom fluxes composed of kchi Sea , 55–59, eversals . Similar danicus , 61. Howth years . The colkchi Sea .Fragilariopsis spp. were first collected simultaneously to sea ice breakup at the end of April at DBO2 and DBO3 and during mid-May at DBO4, indicative of the latitudinal delay in sea ice breakup. Peak diatom fluxes were consistently observed approximately three weeks after sea ice breakup, resulting in a 2-week delay between the diatom bloom in the northern Bering Sea (DBO2) and in the northern Chukchi Sea (DBO4). Regardless of the delay in the onset of the bloom, the composition of the diatom fluxes was strikingly similar at the three sites during 2019, with Fragilariopsis spp., F. arctica, Navicula spp., Pseudo-nitzschia/Nitzschia spp., Thalassiosira spp., and Chaetoceros spp. composing most of the fluxes. These observations indicate that algal production was likely back to normal in the northern Bering Sea.Despite higher water temperatures during summer and autumn 2018, coinciding with record high surface seawater temperatures in the Pacific Arctic [Calanus at DBO2 and DBO3 during June and July 2019. While the majority of Calanus copepods present in the Chukchi Sea are believed to originate from the Bering Sea [Calanus on the northern Chukchi shelf during summer 2019 [Whereas Pacific copepods were not collected in 2019 despite the enhanced transport of Pacific waters observed until September 2019 across Bering Strait , the susring Sea , their imer 2019 . No cleamer 2019 . By conta, and diatom fluxes during the June 2017-June 2018 cycle than during the June 2018-July 2019 cycle, despite the export of a large pelagic bloom at the end of May and early June 2018, indicated that elevated fluxes were sustained over a longer period when ice breakup occurred a few weeks later during 2019. It is reasonable to assume that annual fluxes would have been higher for the 2017–2018 cycle without the interruption in sampling during June 2018. However, it is unlikely that these annual fluxes would have been higher than during 2018–2019 as decreasing near-bottom chl a concentrations recorded at a close-by mooring indicated a declining bloom during June 2018 [a fluxes during 2017–2018 may have also partly arisen from the dominance of the generally small-sized Chaetoceros cells with lower chl a content during the 2018 spring bloom. The large abundance of copepodites and nauplii during summer 2018, together with the larger annual FPC flux during 2018–2019, suggest that the massive pelagic bloom enhanced secondary production and grazing pressure in the northern Bering Sea, supporting the hypothesis of a transition to a pelagic-dominated ecosystem under warmer conditions [A comparison of annual fluxes obtained for each deployment cycle highlights the large-scale impact of an early sea ice breakup on export in the Pacific Arctic region. In the northern Bering Sea, lower annual TPM, POC, chl nditions . The domnditions . These oa and diatom fluxes collected at DBO3 during 2017–2018, despite sea ice breakup actually occurring later during 2018 than during 2019, highlighted the influence of advected waters from the northern Bering Sea. Indeed, a shorter period of lower diatom fluxes at DBO3 during May 2018 possibly resulted from a reduced inflow of nutrients into the southern Chukchi Sea following the massive pelagic bloom that occurred during the prior weeks in the northern Bering Sea. Whereas higher annual FPC flux during 2017–2018 may be the result of larger fecal pellets produced by larger copepods during summer 2017, the highest copepod abundance during summer 2018 also contributed to relatively high FPC fluxes at DBO3 during the 2018–2019 cycle, further supporting a transition to a pelagic-dominated ecosystem under warmer conditions [In the southern Chukchi Sea, annual fluxes were also lower during the 2017–2018 cycle than during the 2018–2019 cycle, except for a slightly higher annual FPC flux. The lower chl nditions . Althouga and intact diatom fluxes during 2018–2019 than under longer lasting sea ice cover during 2015–2016 [a and diatom fluxes recorded during 2018–2019. However, the lower annual chl a and diatom fluxes observed near Hanna Shoal also resulted from the short-lived and smaller peak in diatom fluxes recorded after sea ice melt during spring 2019, while elevated diatom fluxes were sustained during several weeks in the presence of ice cover during spring and summer 2016 [a and diatom fluxes during summer 2019 suggest that enhanced resuspension under reduced ice cover likely contributed to these fluxes.By contrast to the DBO2 site where sea ice conditions were heavier during 2018–2019 than during 2017–2018, sea ice breakup at the DBO4 site took place more than two months earlier during 2019 than when the same site was previously sampled during 2016 . Conside015–2016 . While W015–2016  reportedmer 2016 . Therefomer 2016 , principa and diatom fluxes following sea ice melt at the three DBO sites on the shallow Pacific Arctic shelves. While POC fluxes represent diverse sources of particles, such as material released from the ice, resuspension events, and lateral advection, chl a and intact diatom fluxes more reliably reflect the impact of reduced sea ice conditions on the biological pump. Chl a and diatom fluxes obtained during the two-year sediment trap time-series therefore suggest that the recent loss of sea ice and ensuing weaker stratification reduced the strength of the biological pump in the Pacific Arctic region. In addition, the sustained transport of warm Pacific waters [Calanus copepods at the three DBO sites during the study period. The abundance of smaller Pseudocalanus copepods instead either increased or decreased FPC fluxes and the efficiency of the biological pump at the DBO sites, highlighting the need for additional export flux measurements to determine long-term trends. As warming of the Arctic and sub-Arctic continues, major ecosystem changes are expected to occur more frequently in the Pacific Arctic region [Overall, earlier sea ice breakup resulted in shorter periods of elevated chl c waters  led to tc region . In this