The authors gratefully acknowledge Ms. Christine Stefani for performing the XRPD measurements. Marian Schu&#776;ch and Rebekka Kuiter (State Academy of Art and Design Stuttgart) are acknowledged for the pictures of the tile (Fig. 7).

1. Sample Preparation
<ol>
	<li>Collection of material
	<ol>
		<li>Carefully pick a small amount (less than 1 mg) of sample 1 under a digital microscope using a scalpel and tweezers from settings of opaque blue-green cabochons on a historic clasp, belonging to the collection of the Rosgartenmuseum Konstanz (RMK-1964.79) (Figure 6).</li>
		<li>Carefully scratch a few mg of sample 2 with a scalpel from the surface of a glazed ceramic tile, dating at early modern times, manufactured in Southern Germany, with size of 41 x 29 x 3.5 cm, and part of the collection of Landesmuseum W&#252;rttemberg (no. E 3004) (Figure 7). 
		Note: The tile was stored from the 1980s until 2004 in wooden cupboards. The backside heavily suffers thecotrichite efflorescence occurring as a phase-pure product (Figure 7b).</li>
	</ol>
	</li>
	<li>Preparation of the sample holders
	<ol>
		<li>Grind both samples carefully with a pestle in a small agate mortar.</li>
		<li>Distribute sample 1, which consists of few agglomerated grains (&#60;1 mg), between two thin X-ray transparent polyimide foils and mount them on a transmission sample holder with a central opening of 8 mm diameter. Fix the transmission sample holder on the &#952;-circle of the diffractometer.</li>
		<li>Fill sample 2 (approx. 5 mg) in a borosilicate glass capillary of 0.5 mm diameter.
		<ol>
			<li>To do so, place a small amount of powder into the funnel of the capillary using a spatula. Then move the powder down to the tip of the capillary with the help of an electric vibrator. Compact the powder by placing the capillary in a thick walled glass tube and tap it manually on the desk.</li>
			<li>Continue until a filling height of about 3 cm is reached. Cut the glass capillary carefully at a height of approximately 4 cm using a thin corundum blade and seal the open end using a lighter.</li>
			<li>Place a small amount of beeswax in the opening of a brass pin and melt it using a soldering iron. Then place the capillary in the molten wax and keep it upright until solidification. Mount the brass pin on a goniometer head and fix the goniometer head on the &#952;-circle of the diffractometer.</li>
			<li>Finally, center the mounted capillary by iteratively aligning the four degrees of freedom of the goniometer head (two rotations using bending slides and two translations using XY translation stages) manually with a wrench supported by a digital camera projection superimposed with a cross hair.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
2. Data Collection
<ol>
	<li>For the laboratory XRPD patterns of samples 1 (Figure 8) and 2 (Figure 9) at room temperature use a high-resolution powder diffractometer (with primary beam Johann-type Ge(111) monochromator for Cu-K&#945;1-radiation) which is equipped with a linear position sensitive silicon strip detector with an opening of approximately 12&#176; 2&#952;.
	<ol>
		<li>Measure sample 1 for 20 hr in the range from 5-85&#176; 2&#952; with a step width of 0.015&#176; 2&#952; in transmission mode (Scan mode: Transmission; Scan type: 2ThetaOmega; Omega mode: Moving; PSD Mode: Moving). Turn rotation on in order to achieve better particle statistics.</li>
		<li>Record sample 2 for a period of 6 hr covering the range 5-60&#176; in 2&#952; with a step size of 0.015&#176; in Debye-Scherrer mode (Scan mode: Debye Scherrer; Scan type: 2Theta; Omega mode: Stationary; PSD Mode: Moving). Turn rotation on in order to achieve better particle statistics.</li>
	</ol>
	</li>
</ol>
3. Crystal Structure Determination and Refinement
Note: For the determination and refinement of the crystal structures of samples 1 and 2, a complex computer program is used11. It is either run by a graphical user interface or by text based input files. The latter make use of a sophisticated scripting language. Sample input files of the different stages of the structural analysis using sample 1 are listed in Tables S1, S2, S4-S8. The general procedure is identical for sample 2.
<ol>
	<li>Peak search
	<ol>
		<li>Perform an automatic peak search using the first and second derivatives of Savitzky-Golay polynoms of low order (Figure 10) according to manufacturer&#8217;s protocol by setting the convolute range on the order of 1-1.5 times the full width at half maximum of the Bragg reflections (0.12&#176; 2 &#952; for sample 1), adjusting the noise threshold to 1.5-2 times the estimated standard deviation (1.74 for sample 1) and limiting the search for that part of the powder patterns which show clearly distinguishable peaks (5-66&#176; 2&#952; for sample 1) above the background.
		<ol>
			<li>Start the program by double clicking the icon. Click Load Scan Files. Pull down menu Select X-Y data files (*.xy). Double click on 1-GNM-4145-P4-Kapton.xy.</li>
			<li>Expand range 1-GNM-4145-P4-Kapton.xy. Click Emission profile | Load Emission profile | CuK1sharp.lam.</li>
			<li>Click button Automatically insert peaks. Unclick Remove K-Alpha 2 Peaks. Set Peak Width with slide bar to 0.12. Set Noise Threshold with slide bar to 1.74. Press button Add Peaks. Press Close.</li>
		</ol>
		</li>
		<li>Use the integrating property of the human eye and correct manually the automatically detected peaks by deleting non-Bragg peaks which obviously are due to counting statistics and adding peaks which are recognizable but hidden in the tails of other peaks. Set up indexing files with sets of 30 to 40 reflections for each sample using standard settings but allowing all crystal systems (Table S1).
		<ol>
			<li>Zoom with mouse in the pattern, use mouse wheel to scroll. Open Peak Details window by pressing F3. Set peaks by pressing left mouse button. Delete peaks by pressing F9. Close Peak Details window.</li>
			<li>Click on Peaks Phase. Mark all peaks yellow by clicking on Position. Left click in the yellow marked column. Click Copy all/selection | Create Indexing range. Deselect range 1-GNM-4145-P4-Kapton.xy. Select range Indexing. Select all Bravais lattices (click Use to highlight the list and set a tick mark). 
			&#160;</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Indexing
	<ol>
		<li>For indexing apply the &#8220;iterative use of singular value decomposition&#8221; algorithm12 (Table S2) until finding a primitive tetragonal unit cell for sample 1 and a primitive monoclinic lattice for sample 2 (see Table 1 for unit cell parameters).
		<ol>
			<li>Press Run button (F6). Press Yes to keep indexing solutions. Press Solutions button. Highlight first solution by left clicking button 1. Right click on the highlighted (yellow) solution. Click Copy all/selection. Deselect range Indexing. Select range 1-GNM-4145-P4-Kapton.xy. 
			Note: Other unit cells showing a high figure of merit all have multiple volumes but higher numbers of unobserved reflections as compared to the ones listed in Table 1. The program automatically suggests the most probable space groups based on the observed reflection extinctions which is P42/n (86) for sample 1 and P21/a for sample 2 (Figure 11).</li>
		</ol>
		</li>
		<li>Confirm these findings manually by searching for extinctions using the International Tables of Crystallography Volume A13 (Table S3). Estimate the number of formula units per unit cell from average volume increments to Z = 8 for sample 1 and Z = 4 for sample 2.</li>
	</ol>
	</li>
	<li>Whole powder pattern fitting
	<ol>
		<li>Perform whole powder pattern fitting according to Pawley14 for both powder patterns. For the description of the peak profiles, use the fundamental parameter (FP) approach15 (Figure 12). Model the background by orthogonal Chebychev polynomials of higher order (typically 8) and an additional 1/X term describing the air scattering at low diffraction angles. Set the Lorenz-Polarization factor to 27.3 which is the Bragg angle for the Ge(111) monochromator using Cu-K&#945;1 radiation. Table S4 contains all relevant input parameters.
		<ol>
			<li>Press Add hkl Phase. Expand range 1-GNM-4145-P4-Kapton.xy. Expand hkl_Phase. Click Indexing Details | Paste Indexing details. Click Background. Change Order to 8 (refine). Tick 1/X Bkg (refine).</li>
			<li>Click Instrument. Set Primary radius (mm) to 217.5. Set Secondary radius (mm) to 217.5. Tick Point detector. Tick Receiving Slit Width, value of 0.1 (fix). Tick Full Axial Model. Set Source length (mm) to 6 (fix). Set Sample length (mm) to 6 (fix). Set RS length (mm) to 6 (fix).</li>
			<li>Click Corrections. Tick Zero error, value to 0 (refine). Tick LP factor, value to 27.3 (fix). Click Miscellaneous. Set Conv. Steps to 2. Tick Start X, value 8. Tick Finish X, value 75. Click Peaks Phase | Delete Peaks Phase | Yes.</li>
			<li>Click hkl_Phase | Microstructure. Tick Cry Size L, value to 200 (refine). Tick Cry Size G, value to 200 (refine). Tick Strain L, value to 0.1 (refine). Tick Strain G, value to 0.1 (refine). Press Run button (F6).</li>
		</ol>
		</li>
		<li>&#160;Create a list of Bragg peaks suitable for Charge Flipping6. Click hkl_Phase. Click Charge-Flipping output. Tick A file for CF, value CF.A. Tick hkl file for CF, value CF.hkl. Press Run button (F6). Pull down menu File | Export to INP file. File name, value Pawley.INP. Press Save. 
		Note: For the consecutive structure determination, keep all instrument, peak shape and lattice parameters fixed.</li>
	</ol>
	</li>
	<li>Crystal Structure determination 
	Note: A combination of three methods (used in an iterative manner) is used to determine the crystal structures of samples 1 and 2.
	<ol>
		<li>Firstly, use the method of Charge Flipping6 supported by the inclusion of the tangent formula16 (Figure 13) to find the positions of most of the heavier atoms. Delete observed reflections with a d-spacing smaller than 1.28 (for sample 1) and extend the calculated sphere to a d-spacing of 0.9. All necessary parameters are listed in Table S5. Pick atoms with recognizable electron density from the resulting list, correct falsely assigned atom types of similar scattering power like carbon, oxygen or nitrogen manually.
		<ol>
			<li>Pull down File File | Close All - Confirm by clicking Yes. Pull down Launch Launch | Launch Kernel.</li>
			<li>Pull down Launch Launch | Set INP File. Select CF.INP (prepared input text file, listed in Table S5). Confirm by clicking Open. Press Run button (F6). Press STOP button (F8) after approx. 20,000 cycles. Confirm Charge flipping finished by pressing Yes.</li>
			<li>Press Temporary output window displaying selected atoms in z-matrix format button. Press Cloud options dialog button. Set N to pick to 45. Tick With Symmetry. Press Pick button. Copy temporary output and save it to a text file called FirstGuess.str. Close the charge flipping graphics window.</li>
		</ol>
		</li>
		<li>Secondly, apply the global optimization method of simulated annealing7,17 (Figure 14) to find the positions of all missing non-hydrogen atoms (mainly the carbon atoms of the formate/acetate groups). Use the automatic annealing scheme provided by the software. Subject only the scale factor and the positional and/or occupational parameters of selected atoms to simulated annealing. For sample 1, merge sodium and oxygen atoms within a radius of 1.1 &#197; to detect special positions (Table S6).
		<ol>
			<li>Pull down Launch Launch | Set INP File. Select SA.INP (prepared input text file, listed in Table S6). Confirm by clicking Open. Press Run button (F6). Press STOP button (F8) after several thousand cycles. Confirm Update input file by pressing Yes.</li>
		</ol>
		</li>
		<li>Thirdly, turn off simulated annealing and switch to Rietveld5 refinement mode by commenting out the command Auto_T(0.1). Fix all confirmed positional parameters. Include the calculation of a difference-Fourier map (Fobs-Fcalc) (Figure 15, Table S7) to check for unaccounted electron density. Include the additionally found atoms in the atom list and refine the atomic positions and occupancies.
		<ol>
			<li>Pull down Launch Launch | Set INP File. Select Fourier_search_for_C.INP (prepared input text file, listed in Table S7). Confirm by clicking Open. Press Run button (F6). Inspect the two graphical output windows displaying the almost complete crystal structure and the difference Fourier map. 
			Note: Cycle the three structure solving methods iteratively in case of failure. If necessary, apply anti bumping constraints to light atoms (carbon and oxygen atoms) (see Table S7).</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Rietveld refinement
	<ol>
		<li>For the final crystal structure refinements of samples 1 and 2, use the Rietveld whole-pattern refinement method5 (Figure 16). In order to avoid meaningless atomic shifts of atoms in the acetic acid and nitrate groups of sample 2, employ so called soft constraints (also called restraints) based on idealized bond lengths and angles. Calculate idealized positions of the missing hydrogen atoms using standard software18 (Table S8).</li>
		<li>Refine isotropic atomic displacement parameters for the non-hydrogen atoms of each crystal structure. In case of sample two, model the apparent anisotropy of the width of the Bragg reflections caused by microstrain by including symmetry adapted spherical harmonics of second order.</li>
		<li>Finally create plots of projections of the crystal structures of sample 1 (Figure 17) and sample 2 (Figure 18) and the two crystallographic information files (CIFs) which from now on can be used for full quantitative phase analysis. An example of such a full quantitative analysis is given in Figure 19 using the crystal structure of sample 1.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Bradley, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The interface between science and conservation, Occacional Paper 116. , (1997).</li><li>Dinnebier, R. E., Billinge, S. J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Powder Diffraction:Theory and Practice. , (2008).</li><li>Debye, P., Scherrer, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interferenzen+an+regellos+orientierten+Teilchen+im+Roentgenlicht.">Interferenzen an regellos orientierten Teilchen im Roentgenlicht.</a> Phys. Zeit. 17, 277-283 (1916).</li><li>Hull, A. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+New+Method+of+X-Ray+Crystal+Analysis.">A New Method of X-Ray Crystal Analysis.</a> Phys. Rev. 10 (6), 661-696 (1917).</li><li>Rietveld, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+profile+refinement+method+for+nuclear+and+magnetic+structures.">A profile refinement method for nuclear and magnetic structures.</a> J. Appl. Cryst. 2, 65-71 (1969).</li><li>Oszlanyi, G., Suto, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ab+initio+structure+solution+by+charge+flipping.">Ab initio structure solution by charge flipping.</a> Acta Crystallogr. Sect. A. 60 (2), 134-141 (2004).</li><li>Newsam, J. M., Deem, M. W., Freeman, C. M., Prince, E., Stalick, J. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Direct+Space+Methods+of+Structure+Solution+from+Powder+Diffraction+Data.">Direct Space Methods of Structure Solution from Powder Diffraction Data.</a> NIST Special Publication 864: Accuracy in Powder Diffraction II: Proceedings of the International Conference May 26-29, 1992. , 80-91 (1992).</li><li>Dinnebier, R. E., Run&#269;evski, T., Fischer, A., Eggert, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Solid-State+Structure+of+a+Degradation+Product+Frequently+Observed+on+Historic+Metal+Objects.">Solid-State Structure of a Degradation Product Frequently Observed on Historic Metal Objects.</a> Inorg. Chem. 54 (6), 2638-2642 (2015).</li><li>Wahlberg, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Crystal+Structure+of+Thecotrichite,+an+Efflorescent+Salt+on+Calcareous+Objects+Stored+in+Wooden+Cabinets.">Crystal Structure of Thecotrichite, an Efflorescent Salt on Calcareous Objects Stored in Wooden Cabinets.</a> Cryst. Growth Des. 15 (6), 2795-2800 (2015).</li><li>Eggert, G., Fischer, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gef&#228;hrliche+Nachbarschaft:+Durch+Glas+induzierte+Metallkorrosion+an+Museums-Exponaten+-+Das+GIMME-Projekt.">Gef&#228;hrliche Nachbarschaft: Durch Glas induzierte Metallkorrosion an Museums-Exponaten - Das GIMME-Projekt.</a> Restauro. 1, 38-43 (2012).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> TOPAS (current version 5.0). , (2015).</li><li>Coelho, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Indexing+of+powder+diffraction+patterns+by+iterative+use+of+singular+value+decomposition.">Indexing of powder diffraction patterns by iterative use of singular value decomposition.</a> J. Appl. Crystallogr. 36 (1), 86-95 (2003).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> International Tables for Crystallography Volume A: Space-group symmetry. , (2006).</li><li>Pawley, G. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unit-cell+refinement+from+powder+diffraction+scans.">Unit-cell refinement from powder diffraction scans.</a> J. Appl. Crystallogr. 14, 357-361 (1981).</li><li>Cheary, R. W., Coelho, A. A., Cline, J. 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The authors have nothing to disclose.

XRPD is a suitable technique for conservation research as it is non-destructive, fast and easy-to-use. XRPD data can be used in routine qualitative analysis, owing to the fact that the powder pattern is a fingerprint signature to the corresponding crystal structure. The biggest advantage of XRPD over other analytic techniques is the ability of performing simultaneous qualitative and quantitative analysis of crystalline constituents in mixtures by using the Rietveld refinement method5. Moreover, the presence of...

Conservation science applies scientific (often chemical) methods in the conservation of artifacts. This includes investigations of the production of artifacts (&#39;technical art history&#39;: How was it made at that time?) and their decay pathways as a prerequisite to develop proper conservation treatments. Oftentimes these studies deal with metal organic salts like carbonates, formates and acetates. Some of them have been deliberately manufactured using suitable compounds (e.g., vinegar), others derive from deterioration reactions with the atmosphere (carbon dioxide or carbonyl compounds from indoor air pollution)1. As a matter of fact, the crystal structures of many of these corrosion materials are still unknown. This is an unfortunate fact, since the knowledge of the geometrical structure helps conservation science to better understand production and decay reactions and to allow for full quantitative analysis in the case of mixtures.
Under the condition that the material of interest forms single crystals of sufficient size and quality, single crystal diffraction is the method of choice for the determination of the crystal structure. If these boundary conditions are not fulfilled, powder diffraction is the closest alternative. The biggest drawback of powder diffraction as compared to single crystal diffraction lies in the loss of the orientational information of the reciprocal d-vector d* (scattering vector). In other words, the intensity of a single diffraction spot is smeared over the surface of a sphere. This can be considered a projection of the three-dimensional diffraction (= reciprocal) space onto the one dimensional 2&#952;-axis of the powder pattern. As a consequence, scattering vectors of different direction but equal or similar length, overlap systematically or accidentally making it difficult or even impossible to separate these reflections2 (Figure 1). This is also the main reason why powder diffraction, despite its early invention just four years after the first single crystal experiment3,4, was mainly used for phase identification and quantification for more than half a century. Nevertheless, the information content of a powder pattern is huge as can be easily deduced from Figure 2. The real challenge, however, is to reveal as much information as possible in a routine way.
A crucial step towards this goal, without any doubt, was the idea from Hugo Rietveld in 19695 who invented a local optimization technique for crystal structure refinement from powder diffraction data. The method does not refine single intensities but the entire powder pattern against a model of increasing complexity, thus taking the peak overlap intrinsically into account. From that time on, scientists using powder diffraction techniques were no longer limited to data analysis by methods developed for single crystal investigation. Several years after the invention of the Rietveld method, the power of the powder diffraction method for ab-initio structure determinations was recognized. Nowadays, almost all branches of natural sciences and engineering use powder diffraction to determine more and more complex crystal structures, although the method can still not be regarded as routine. Within the last decade, a new generation of powder diffractometers in the laboratory was designed providing high resolution, high energy and high intensity. Better resolution immediately leads to better peak separation while higher energies fight absorption. The benefit of a better peak profile description based on fundamental physical parameters (Figure 3) are more accurate intensities of Bragg reflection allowing for more detailed structural investigations. With modern equipment and software even microstructural parameters like domain sizes and microstrain are routinely deduced from powder diffraction data.
All algorithms for crystal structure determination from powder diffraction data use single peak intensities, the entire powder pattern or a combination of both. The conventional single crystal reciprocal space techniques often fail due to an unfavorable ratio between available observations and structural parameters. This situation changed dramatically with the introduction of the &#34;charge flipping&#34; technique6 (Figure 4) and the development of global optimization methods in direct space, of which the simulated annealing technique7 (Figure 5) is the most prominent representative. In particular, the introduction of chemical knowledge into the structure determination process using rigid bodies or the known connectivity of molecular compounds concerning bond lengths and angles strongly reduces the number of necessary parameters. In other words, instead of three positional parameters for every single atom, only the external (and few internal) degrees of freedom of groups of atoms need to be determined. It is this reduction of structural complexity which makes the powder method a real alternative to single crystal analysis.
Two pioneering case studies of the authors8,9 proved that it is possible to solve complicated crystal structures of complex corrosion products using powder diffraction data. The superiority of the crystallographic studies compared to other approaches was demonstrated among others by the fact that in both cases the reported formulas had to be corrected after considering the solved crystal structures.
The occurrence of both materials under investigation in museums is related to their storage in wooden cabinets or exposed to other sources of carbonyl pollutants. The first material under investigation was sodium copper formate hydroxide oxide hydrate, Cu4Na4O(HCOO)8(OH)2&#8729;4H2O (sample 1), which forms on soda glass/copper alloy composite historic objects (e.g., enamels) in museum collections, exposed to formaldehyde and formic acid from wooden storage cabinets, adhesives, etc. This degradation phenomenon has recently been characterized as &#34;glass induced metal corrosion&#34;10. For the second case study, thecotrichite, Ca3(CH3COO)3Cl(NO3)2&#8729;6H2O (sample 2), was chosen. Thecotrichite is a frequently observed efflorescent salt forming needlelike crystallites on tiles and limestone museum objects, which are stored in oak cabinets and display cases. In this case, the wood acts as source for acetic acid which reacts with soluble chloride and nitrate salts from the artifact.
In the following part of the text, the individual steps of the structure determination process using powder diffraction data applied to corrosion products from conservation science are presented in detail.

<table border="0" cellpadding="0" cellspacing="0" width="573">
	<tbody>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Stadi-P&#160;</td>
			<td style="width:71px;">Stoe &#38; Cie GmbH</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Powder Diffractometer</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Mythen 1-K (450 &#956;m)</td>
			<td style="width:71px;">Dectris Ltd.</td>
			<td style="width:119px;"></td>
			<td>Position Sensitive Detector</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Mark tube borosilicate glass No. 50, 0.5 mm diameter</td>
			<td style="width:71px;">Hilgenberg GmbH</td>
			<td align="right">4007605</td>
			<td>Low absorbing capillaries</td>
		</tr>
		<tr height="126">
			<td height="126" style="height:126px;width:216px;">Topas 5.0</td>
			<td style="width:71px;">Bruker AXS Advanced X-ray Solutions GmbH</td>
			<td style="width:119px;"></td>
			<td>Powder Diffraction Evaluation Software</td>
		</tr>
	</tbody>
</table>

x-ray powder diffraction in conservation science: towards routine crystal structure determination of corrosion products on heritage art objects

The crystal structure determination and refinement process of corrosion products on historic art objects using laboratory high-resolution X-ray powder diffraction (XRPD) is presented in detail via two case studies.
The first material under investigation was sodium copper formate hydroxide oxide hydrate, Cu4Na4O(HCOO)8(OH)2&#8729;4H2O (sample 1) which forms on soda glass/copper alloy composite historic objects (e.g., enamels) in museum collections, exposed to formaldehyde and formic acid emitted from wooden storage cabinets, adhesives, etc. This degradation phenomenon has recently been characterized as &#34;glass induced metal corrosion&#34;.
For the second case study, thecotrichite, Ca3(CH3COO)3Cl(NO3)2&#8729;6H2O (sample 2), was chosen, which is an efflorescent salt forming needlelike crystallites on tiles and limestone objects which are stored in wooden cabinets and display cases. In this case, the wood acts as source for acetic acid which reacts with soluble chloride and nitrate salts from the artifact or its environment.
The knowledge of the geometrical structure helps conservation science to better understand production and decay reactions and to allow for full quantitative analysis in the frequent case of mixtures.

High resolution XRPD was used to determine the previously unknown crystal structures of two long-known corrosion products on historic objects. The samples were taken from two museum objects and carefully grinded before they were sealed in transmission and capillary sample holders (Figures 6, 7). Standard measurements using a state of the art laboratory high resolution powder diffractometer in transmission and Debye-Scherrer geometry using monochromatic X-rays were perform...

Watch this Scientific Journal Video about X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects at JoVE.com

X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects

Modern high resolution X-ray powder diffraction (XRPD) in the laboratory is used as an efficient tool to determine crystal structures of long-known corrosion products on historic objects.

The crystal structure determination and refinement process of corrosion products on historic art objects using laboratory high-resolution X-ray powder ...

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15.8K Views.  Max-Planck-Institute for Solid State Research. Modern high resolution X-ray powder diffraction (XRPD) in the laboratory is used as an efficient tool to determine crystal structures of long-known corrosion products on historic objects.

Video: X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects

Preparing Adherent Cells for X-ray Fluorescence Imaging by Chemical Fixation

X-ray fluorescence imaging allows us to non-destructively measure the spatial distribution and concentration of multiple elements simultaneously over large or small sample areas. It has been applied in many areas of science, including materials science, geoscience, studying works of cultural heritage, and in chemical biology. In the case of chemical biology, for example, visualizing the metal distributions within cells allows us to study both naturally-occurring metal ions in the cells, as well as exogenously-introduced metals such as drugs and nanoparticles. Due to the fully hydrated nature of nearly all biological samples, cryo-fixation followed by imaging under cryogenic temperature represents the ideal imaging modality currently available. However, under the circumstances that such a combination is not easily accessible or practical, aldehyde based chemical fixation remains useful and sometimes inevitable. This article describes in as much detail as possible in the preparation of adherent mammalian cells by chemical fixation for X-ray fluorescent imaging.

Here, we present a protocol on how to determine the quantity and distribution of metals in a sample using synchrotron X-ray fluorescence. We focus on adherent cells, and describe the chemical fixation method to prepare this sample. We then describe how to mount and image the sample using synchrotron X-rays.

X-ray fluorescence imaging allows us to non-destructively measure the spatial distribution and concentration of multiple elements simultaneously over ...

From Constructs to Crystals &#8211; Towards Structure Determination of &#946;-barrel Outer Membrane Proteins

Membrane proteins serve important functions in cells such as nutrient transport, motility, signaling, survival and virulence, yet constitute only ~1% percent of known structures. There are two types of membrane proteins, &#945;-helical and &#946;-barrel. While &#945;-helical membrane proteins can be found in nearly all cellular membranes, &#946;-barrel membrane proteins can only be found in the outer membranes of mitochondria, chloroplasts, and Gram-negative bacteria. One common bottleneck in structural studies of membrane proteins in general is getting enough pure sample for analysis. In hopes of assisting those interested in solving the structure of their favorite &#946;-barrel outer membrane protein (OMP), general protocols are presented for the production of target &#946;-barrel OMPs at levels useful for structure determination by either X-ray crystallography and/or NMR spectroscopy. Here, we outline construct design for both native expression and for expression into inclusion bodies, purification using an affinity tag, and crystallization using detergent screening, bicelle, and lipidic cubic phase techniques. These protocols have been tested and found to work for most OMPs from Gram-negative bacteria; however, there are some targets, particularly for mitochondria and chloroplasts that may require other methods for expression and purification. As such, the methods here should be applicable for most projects that involve OMPs from Gram-negative bacteria, yet the expression levels and amount of purified sample will vary depending on the target OMP.

&#946;-barrel outer membrane proteins (OMPs) serve many functions within the outer membranes of Gram-negative bacteria, mitochondria, and chloroplasts. Here, we hope to alleviate a known bottleneck in structural studies by presenting protocols for the production of &#946;-barrel OMPs in sufficient quantities for structure determination by X-ray crystallography or NMR spectroscopy.

Membrane proteins serve important functions in cells such as nutrient transport, motility, signaling, survival and virulence, yet constitute only ~1% ...

High Pressure Single Crystal Diffraction at PX^2

In this report we describe detailed procedures for carrying out single crystal X-ray diffraction experiments with a diamond anvil cell (DAC) at the GSECARS 13-BM-C beamline at the Advanced Photon Source. The DAC program at 13-BM-C is part of the Partnership for Extreme Xtallography (PX^2) project. BX-90 type DACs with conical-type diamond anvils and backing plates are recommended for these experiments. The sample chamber should be loaded with noble gas to maintain a hydrostatic pressure environment. The sample is aligned to the rotation center of the diffraction goniometer. The MARCCD area detector is calibrated with a powder diffraction pattern from LaB6. The sample diffraction peaks are analyzed with the ATREX software program, and are then indexed with the RSV software program. RSV is used to refine the UB matrix of the single crystal, and with this information and the peak prediction function, more diffraction peaks can be located. Representative single crystal diffraction data from an omphacite (Ca0.51Na0.48)(Mg0.44Al0.44Fe2+0.14Fe3+0.02)Si2O6 sample were collected. Analysis of the data gave a monoclinic lattice with P2/n space group at 0.35 GPa, and the lattice parameters were found to be: a = 9.496 &#177;0.006 &#197;, b = 8.761 &#177;0.004 &#197;, c = 5.248 &#177;0.001 &#197;, &#946; = 105.06 &#177;0.03&#186;, &#945; = &#947; = 90&#186;.

In this report, we describe detailed procedures for carrying out single crystal X-ray diffraction experiments with a diamond anvil cell at the GSECARS 13-BM-C beamline at the Advanced Photon Source. ATREX and RSV programs are used to analyze the data.

In this report we describe detailed procedures for carrying out single crystal X-ray diffraction experiments with a diamond anvil cell (DAC) at the ...

Extraction and Purification of Polyphenols from Freeze-dried Berry Powder for the Treatment of Vascular Smooth Muscle Cells In Vitro

Epidemiological studies indicate that increased flavonoid intake correlates with decreased mortality due to cardiovascular diseases (CVD) in the United States (US) and Europe. Berries are widely consumed in the US and have a high polyphenolic content. Polyphenols have been shown to interact with many molecular targets and to exert numerous positive biological functions, including antioxidant, anti-inflammatory, and cardioprotective effects. Polyphenols isolated from blackberry (BL), raspberry (RB), and black raspberry (BRB) reduce oxidative stress and cellular senescence in response to angiotensin II (Ang II). This work provides a detailed description of the protocol used to prepare the polyphenol extracts from freeze-dried berries. Polyphenol extractions from freeze-dried berry powder were performed using 80% aqueous ethanol and an ultrasonic-assisted extraction method. The crude extract was further purified and fractionated using chloroform and ethyl acetate, respectively. The effects of both crude and purified extracts were tested on Vascular Smooth Muscle Cells (VSMCs) in culture.

Extraction and Purification of Polyphenols from Freeze-dried Berry Powder for the Treatment of Vascular Smooth Muscle Cells In Vitro

This work details a step-by-step method to prepare polyphenol-rich extracts from freeze-dried berry powder. In addition, it provides a thorough description of how to use these polyphenol-rich extracts in cell culture in the presence of the peptide hormone angiotensin II (Ang II) using Vascular Smooth Muscle Cells (VSMCs).

Epidemiological studies indicate that increased flavonoid intake correlates with decreased mortality due to cardiovascular diseases (CVD) in the United ...

Quantifying X-Ray Fluorescence Data Using MAPS

The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical composition and elemental distribution within a material. Synchrotron-based XRF has become an integral characterization technique for a variety of research topics, particularly due to its non-destructive nature and its high sensitivity. Today, synchrotrons can acquire fluorescence data at spatial resolutions well below a micron, allowing for the evaluation of compositional variations at the nanoscale. Through proper quantification, it is then possible to obtain an in-depth, high-resolution understanding of elemental segregation, stoichiometric relationships, and clustering behavior.
This article explains how to use the MAPS fitting software developed by Argonne National Laboratory for the quantification of full 2-D XRF maps. We use as an example results from a Cu(In,Ga)Se2 solar cell, taken at the Advanced Photon Source beamline 2-ID-D at Argonne National Laboratory. We show the standard procedure for fitting raw data, demonstrate how to evaluate the quality of a fit and present the typical outputs generated by the program. In addition, we discuss in this manuscript certain software limitations and offer suggestions for how to further correct the data to be numerically accurate and representative of spatially resolved, elemental concentrations.

Here, we demonstrate the use of the X-ray fluorescence fitting software, MAPS, created by Argonne National Laboratory for the quantification of fluorescence microscopy data. The quantified data that results is useful for understanding the elemental distribution and stoichiometric ratios within a sample of interest.

The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical ...

Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the results of femtosecond X-ray free electron laser (XFEL) experiments. An increasing number of experimental observations have shown that although nuclear motion can be negligible, given a short enough incident pulse duration, electronic motion cannot be ignored. The current and widely accepted models assume that although electrons undergo dynamics driven by interaction with the pulse, their motion could largely be considered &#39;random&#39;. This would then allow the supposedly incoherent contribution from the electronic motion to be treated as a continuous background signal and thus ignored. The original aim of our experiment was to precisely measure the change in intensity of individual Bragg peaks, due to X-ray induced electronic damage in a model system, crystalline C60. Contrary to this expectation, we observed that at the highest X-ray intensities, the electron dynamics in C60 were in fact highly correlated, and over sufficiently long distances that the positions of the Bragg reflections are significantly altered. This paper describes in detail the methods and protocols used for these experiments, which were conducted both at the Linac Coherent Light Source (LCLS) and the Australian Synchrotron (AS) as well as the crystallographic approaches used to analyse the data.

We describe an experiment designed to probe the electronic damage induced in nanocrystals of Buckminsterfullerene (C60) by intense, femtosecond pulses of X-rays. The experiment found that, surprisingly, rather than being stochastic, the X-ray induced electron dynamics in C60 are highly correlated, extending over hundreds of unit cells within the crystals1.

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the ...

Nanothermite with Meringue-like Morphology: From Loose Powder to Ultra-porous Objects

The goal of the protocol described in this article is to prepare aluminothermic compositions (nanothermites) in the form of porous, monolithic objects. Nanothermites are combustible materials made up of inorganic fuel and an oxidizer. In nanothermite foams, aluminum is the fuel and aluminum phosphate and tungsten trioxide are the oxidizing moieties. The highest flame propagation velocities (FPVs) in nanothermites are observed in loose powders and FPVs are strongly decreased by pelletizing nanothermite powders. From a physical standpoint, nanothermite loose powders are metastable systems. Their properties can be altered by unintentional compaction induced by shocks or vibrations or by the segregation of particles over time by settling phenomena, which originates from the density differences of their components. Moving from a powder to an object is the challenge that must be overcome to integrate nanothermites in pyrotechnic systems. Nanothermite objects must have both a high open porosity and good mechanical strength. Nanothermite foams meet both of these criteria, and they are prepared by dispersing a nano-sized aluminothermic mixture (Al/WO3) in orthophosphoric acid. The reaction of aluminum with the acid solution gives the AlPO4 &#34;cement&#34; in which Al and WO3 nanoparticles are embedded. In nanothermite foams, aluminum phosphate plays the dual role of binder and oxidizer. This method can be used with tungsten trioxide, which is not altered by the preparation process. It could probably be extended to some oxides, which are commonly used for the preparation of high performance nanothermites. The WO3-based nanothermite foams described in this article are particularly insensitive to impact and friction, which makes them far safer to handle than loose Al/WO3 powder. The fast combustion of these materials has interesting applications in pyrotechnic igniters. Their use in detonators as primers would require the incorporation of a secondary explosive in their composition.

This manuscript describes the synthesis of combustible aluminophosphate matrices by the reaction of orthophosphoric acid (H3PO4) with aluminum nanopowder. When this reaction is carried out with excess aluminum in the presence of tungsten trioxide nanopowder, it leads to a solid, porous nanothermite foam.

The goal of the protocol described in this article is to prepare aluminothermic compositions (nanothermites) in the form of porous, monolithic objects. ...

Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography

This protocol describes fabricating microfluidic devices with low X-ray background optimized for goniometer based fixed target serial crystallography. The devices are patterned from epoxy glue using soft lithography and are suitable for in situ X-ray diffraction experiments at room temperature. The sample wells are lidded on both sides with polymeric polyimide foil windows that allow diffraction data collection with low X-ray background. This fabrication method is undemanding and inexpensive. After the sourcing of a SU-8 master wafer, all fabrication can be completed outside of a cleanroom in a typical research lab environment. The chip design and fabrication protocol utilize capillary valving to microfluidically split an aqueous reaction into defined nanoliter sized droplets. This loading mechanism avoids the sample loss from channel dead-volume and can easily be performed manually without using pumps or other equipment for fluid actuation. We describe how isolated nanoliter sized drops of protein solution can be monitored in situ by dynamic light scattering to control protein crystal nucleation and growth. After suitable crystals are grown, complete X-ray diffraction datasets can be collected using goniometer based in situ fixed target serial X-ray crystallography at room temperature. The protocol provides custom scripts to process diffraction datasets using a suite of software tools to solve and refine the protein crystal structure. This approach avoids the artefacts possibly induced during cryo-preservation or manual crystal handling in conventional crystallography experiments. We present and compare three protein structures that were solved using small crystals with dimensions of approximately 10-20 &#181;m grown in chip. By crystallizing and diffracting in situ, handling and hence mechanical disturbances of fragile crystals is minimized. The protocol details how to fabricate a custom X-ray transparent microfluidic chip suitable for in situ serial crystallography. As almost every crystal can be used for diffraction data collection, these microfluidic chips are a very efficient crystal delivery method.

Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography

This protocol describes in detail how to fabricate and operate microfluidic devices for X-ray diffraction data collection at room temperature. Additionally, it describes how to monitor protein crystallization by dynamic light scattering and how to process and analyze obtained diffraction data.

This protocol describes fabricating microfluidic devices with low X-ray background optimized for goniometer based fixed target serial crystallography. The ...

Essential Metal Uptake in Gram-negative Bacteria: X-ray Fluorescence, Radioisotopes, and Cell Fractionation

We demonstrate a scalable method for the separation of the bacterial periplasm from the cytoplasm. This method is used to purify periplasmic protein for the purpose of biophysical characterization, and measure substrate transfer between periplasmic and cytoplasmic compartments. By carefully limiting the time that the periplasm is separated from the cytoplasm, the experimenter can extract the protein of interest and assay each compartment individually for substrate without carry-over contamination between compartments. The extracted protein from fractionation can then be further analyzed for three-dimensional structure determination or substrate-binding profiles. Alternatively, this method can be performed after incubation with a radiotracer to determine total percent uptake, as well as distribution of the tracer (and hence metal transport) across different bacterial compartments. Experimentation with a radiotracer can help differentiate between a physiological substrate and artefactual substrate, such as those caused by mismetallation.
X-ray fluorescence can be used to discover the presence or absence of metal incorporation in a sample, as well as measure changes that may occur in metal incorporation as a product of growth conditions, purification conditions, and/or crystallization conditions. X-ray fluorescence also provides a relative measure of abundance for each metal, which can be used to determine the best metal energy absorption peak to use for anomalous X-ray scattering data collection. Radiometal uptake can be used as a method to validate the physiological nature of a substrate detected by X-ray fluorescence, as well as support the discovery of novel substrates.

A protocol for the extraction of a periplasmic transition metal chaperone in the context of its native binding partners, and biophysical characterization of its substrate contents by X-ray fluorescence and radiometal uptake is presented.

We demonstrate a scalable method for the separation of the bacterial periplasm from the cytoplasm. This method is used to purify periplasmic protein for ...

Elemental-sensitive Detection of the Chemistry in Batteries through Soft X-ray Absorption Spectroscopy and Resonant Inelastic X-ray Scattering

Energy storage has become more and more a limiting factor of today's sustainable energy applications, including electric vehicles and green electric grid based on volatile solar and wind sources. The pressing demand of developing high-performance electrochemical energy storage solutions, i.e., batteries, relies on both fundamental understanding and practical developments from both the academy and industry. The formidable challenge of developing successful battery technology stems from the different requirements for different energy-storage applications. Energy density, power, stability, safety, and cost parameters all have to be balanced in batteries to meet the requirements of different applications. Therefore, multiple battery technologies based on different materials and mechanisms need to be developed and optimized. Incisive tools that could directly probe the chemical reactions in various battery materials are becoming critical to advance the field beyond its conventional trial-and-error approach. Here, we present detailed protocols for soft X-ray absorption spectroscopy (sXAS), soft X-ray emission spectroscopy (sXES), and resonant inelastic X-ray scattering (RIXS) experiments, which are inherently elemental-sensitive probes of the transition-metal 3d and anion 2p states in battery compounds. We provide the details on the experimental techniques and demonstrations revealing the key chemical states in battery materials through these soft X-ray spectroscopy techniques.

Here, we present a protocol for typical experiments of soft X-ray absorption spectroscopy (sXAS) and resonant inelastic X-ray scattering (RIXS) with applications in battery material studies.

Energy storage has become more and more a limiting factor of today's sustainable energy applications, including electric vehicles and green electric grid ...