Excluding false positives: A perspective toward credible ammonia quantification in nitrogen reduction reaction

doi:10.1016/S1872-2067(22)64148-2

Chinese Journal of Catalysis ›› 2023, Vol. 44: 50-66.DOI: 10.1016/S1872-2067(22)64148-2

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Excluding false positives: A perspective toward credible ammonia quantification in nitrogen reduction reaction

Ya Li^a^,¹, Zhenkang Wang^c^,¹, Haoqing Ji^c^,¹, Lifang Zhang^b, Tao Qian^b^,^c, Chenglin Yan^c^,^d^,^*(), Jianmei Lu^a^,^*()

^aCollaborative Innovation Center of Suzhou Nano Science and Technology, College of Chemistry Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, Jiangsu, China
^bCollege of Chemistry and Chemical Engineering, Nantong University, Nantong 226019, Jiangsu, China
^cKey Laboratory of Core Technology of High Specific Energy Battery and Key Materials for Petroleum and Chemical Industry, College of Energy, Soochow University, Suzhou 215006, Jiangsu, China
^dLight Industry Institute of Electrochemical Power Sources, Suzhou 215600, Jiangsu, China

Received:2022-05-23 Accepted:2022-07-04 Online:2023-01-18 Published:2022-12-08
Contact: Chenglin Yan, Jianmei Lu
About author:Chenglin Yan (College of Energy at Soochow University) is a Professor and Dean of the College of Energy at Soochow University in Suzhou, China. He received his Ph.D. from Dalian University of Technology in 2008. In 2011, he became a staff scientist and a group leader at the Institute for Integrative Nanoscience at the Leibniz Institute in Dresden (Germany). His primary research interests focus on electrochemical energy storage.
Jianmei Lu (College of Chemistry, Chemical Engineering and Materials Science at Soochow University) is a Professor of the College of Chemistry, Chemical Engineering and Materials Science and Vice Chancellor of Soochow University. She received her PhD in polymer chemistry from Zhejiang University in 1999 and was appointed as professor of Soochow University in 2000. Her current research interests involve organic and polymer electronic memory functional materials synthesis, device design and mechanism research, adsorption performance and mechanism of adsorbent materials, treatment of industrial waste water and waste gas containing volatile organic compounds and synthesis of photocatalytic functional materials.
¹ Contributed equally to this work.
Supported by:
National Natural Science Foundations of China(52071226);National Natural Science Foundations of China(51872193);National Natural Science Foundations of China(U21A20332);Natural Science Foundations of Jiangsu Province(BK20181168);Natural Science Foundations of Jiangsu Province(BK20201171);Key R&D Project funded by Department of Science and Technology of Jiangsu Province(BE2020003-3);Natural Science Foundation of the Jiangsu Higher Education Institutions of China(19KJA210004);Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)

Abstract

Abstract:

As an essential raw material for fertilizer production and promising green fuels, ammonia is significant to the national economy and social development. Recently, nitrogen reduction reaction (NRR) towards ammonia under mild conditions has received intensive attention due to environmental friendliness and low energy consumption, compared to the rigorous and contaminative Haber-Bosch process. However, as current research deepens, some fatal challenges emerged in this field‒not only high volatility and low repeatability but false‒positive results, casting serious doubts about its prospects. In this review, we summarized and discussed some potential factors that possibly induce false-positive results for accurate ammonia quantification, including the aspects of catalyst materials, experimental process, and quantification methods. And corresponding methods to eliminate these effects are also summarized. Furthermore, a promising protocol and several control principles are proposed to eliminate potential errors during ammonia quantification. This review establishes a paradigm base in NRR research field toward more accurate ammonia quantification.

Key words: Nitrogen reduction reaction, Ammonia quantification, False positives, Contamination, Isotope

Ya Li, Zhenkang Wang, Haoqing Ji, Lifang Zhang, Tao Qian, Chenglin Yan, Jianmei Lu. Excluding false positives: A perspective toward credible ammonia quantification in nitrogen reduction reaction[J]. Chinese Journal of Catalysis, 2023, 44: 50-66.

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Figures/Tables 10

Fig. 1. Schematic illustrations of electrocatalytic (a) and photocatalytic (b) NRR. (c) The remarkable faradic efficiency and NH3 yield in the NRR field from 2018 to 2022. Data are adapted from representative papers in the four years, Ref. [19???????-27]. (d) Schematic illustration of potential factors causing final wrong ammonia quantification from a complete NRR test process. The influencing factors include pollution introduced into NRR reaction systems from different sources, as well as errors in the quantification methods.

Table 1 Summary of total-N amounts detected in commercial metal oxides and Fe samples. Total N in commercial metal oxides and metallic irons is based on NOx- contents by the HPLC analysis and the NH4+ contents after dissolving the samples in 0.1 mol L-1 H2SO4, respectively. Reprinted with permission from Ref. [36]. Copyright 2020, Springer Nature.

Metal oxides/Fe sample Sample		Vendor	Item number	Lot number	Total N (ppm)	Labelled assay
Metal oxides	Bi₂O₃	Alfa Aesar	45582	M22F015	1610 ± 48	+99.5%
	CeO₂	Alfa Aesar	46763	R22A020	1414 ± 21	25% in H₂O
	Al₂O₃	Alfa Aesar	44931	X24E065	690 ± 4	99.5%
	Fe₂O₃	Sigma-Aldrich	544884	MKCH7591	576 ± 20	70.0% (Fe basis)
	Fe₂O₃	Alfa Aesar	45007	W04E043	563 ± 21	≥98%
	Fe₂O₃	Alfa Aesar	44895	Y22D002	554 ± 24	≥98.0%
	Fe₂O₃	Alfa Aesar	44896	Y01C003	508 ± 24	≥98%
	ZnO	Alfa Aesar	45849	S05D048	188 ± 1	N/A
	Fe₂O₃	JTBaker	2024-01	0000235234	—	≥98.0%
	α-Fe₂O₃	USNano	US3180	N/A	—	+98%
	γ-Fe₂O₃	USNano	US3210	N/A	—	99%
	Fe₃O₄	USNano	US3220	N/A	—	+98%
	Fe₃O₄	Sigma-Aldrich	637106	MKCH8514	—	97%
Metallic irons	# Fe, 1-3 micron	Alfa Aesar	40337	R31E034	7183 7372 7337	+98%
	Fe	Sigma-Aldrich	255637	MKBL4538V	391	≥99.99%
	Fe, ~100 mesh	Alfa Aesar	43240	Q12C003	363	99.9%
	Fe, 6-10 micro	Alfa Aesar	10214	G19X048	332	99.5%
	Fe, ~200 mesh	Alfa Aesar	00737	M11E029	295	99+%

Fig. 2. Electrocatalytic NRR tests of Pd NSs and a pre-reduction strategy to remove residual or adsorbed NOx contaminants in catalysts. Reprinted with permission from Ref. [37]. Copyright 2020, Elsevier.

Fig. 3. (a) High-resolution N 1s XPS spectrum of the NPC@500, and its elemental composition by XPS technique after the NRR for 2 h in N2-saturated 0.005 mol L?1 H2SO4 electrolyte at ?0.4 V (vs. RHE). Reprinted with permission from Ref. [42]. Copyright 2019, American Chemical Society. (b) High-resolution N 1s XPS spectra of Co(Mo)-Nx/NPC@500, their LSV curves in the Ar- and N2-saturated 0.1 mol L?1 Na2SO4 electrolyte and continuous pick point experiments of at ?0.4 V (vs. RHE) in the Ar-saturated 0.1 mol L?1 Na2SO4 electrolyte. Reprinted with permission from Ref. [45]. Copyright 2021, Royal Society of Chemistry.

Table 2 Labeled NO3- content in various commercial lithium salts and detected NO3- concentration in their 0.5 mol L?1 solution. Reprinted with permission from Ref. [53]. Copyright 2019, American Chemical Society.

Chemical	Brand	Product code	Assay (%)	Labeled NO₃^- content ^a	[NO₃^-] in 0.5 mol L^‒1 solution^b (μg mL^-1)
Li₂SO₄·H₂O	Sigma-Aldrich	398152	≥99.0	≤0.001%	—
Li₂SO₄·H₂O	Sigma-Aldrich	62612	≥99.0	≤10 mg kg^-1	—
Li₂SO₄·H₂O	Sigma-Aldrich	62609	≥99.0	≤10 mg kg^-1	—
Li₂SO₄	Sigma-Aldrich	203653	≥99.99	n.a.	not detected
Li₂SO₄	Sigma-Aldrich	L6375	≥98.5	n.a.	11.19
Li₂SO₄	Sigma-Aldrich	62613	≥98.0	n.a.	1.02
Li₂SO₄	Alfa Aesar	13404	≥99.7	n.a.	2.82
Li₂SO₄	Aladdin	L130839	≥98.5	n.a.	not detected
LiClO₄	Sigma-Aldrich	431567	≥99.99	n.a.	1.39
LiClO₄	Sigma-Aldrich	205281	≥95.0	n.a.	2.38
Li₂CO₃	Sigma-Aldrich	431559	≥99.99	≤5 mg kg^‒1	—
Li₂CO₃	Sigma-Aldrich	62470	≥99.0	≤5 mg kg^‒1	—

Fig. 4. (a) Evolution of the total amounts of N-containing ions (left-hand side axis) accumulated in the 0.35 mol L?1 [nBu4N][PF6] (CH3CN) electrolyte solution and 1 mmol L?1 H2SO4 acid trap solution, as well as of the H2O concentration (right-hand side axis) in the electrolyte solution during tests of the iron-modified stainless steel electrodes under Ar and then 14N2 atmosphere. Reprinted with permission from Ref. [65]. Copyright 2021, John Wiley and Sons. (b) Ammonia pollution of various membranes. (Left) ammonia release from new Nafion 115 membrane (black line) and the Nafion 115 membranes reused for many times (red line) without sample and applied potential; Absorption (Middle) and release (Right) of ammonia by Nafion 211 (N211), Nafion 115 (N115), Nafion 117 (N117), Celgard 2400 (C2400) and Celgard 3501 (C3501) membranes. Reprinted with permission from Ref. [37]. (c) Detected ammonia concentrations of experimental consumables. 100 mg of samples were immersed in 20 mL of 0.1 mol L?1 Na2SO4, and stirred for 6 h at 1000 rpm. Reprinted with permission from Ref. [50]. Copyright 2020, Elsevier.

Table 3 Amount of N2 and potential NOx contaminants supplied in 4-h NRR experiments undertaken at different N2 purity and gas supply rates, as well as simple calculations of the maximal possible ammonia formation yield rates through the reduction of NOx (assuming all contaminants are NOx and are selectively reduced to NH3). Reprinted with permission from Ref. [3]. Copyright 2020, Springer Nature.

Flow rate (mL min^‒1)	N₂ purity	Purging time (min)	Moles N₂ (nmol)	Moles NO_x^a (nmol)	NH₃ from NO_x (nmol s^‒1)
100	99.999% (10 ppm NO_x) ^b	240	9.82 × 10⁸	9.82 × 10³	0.68
	99.99% (100 ppm NO_x)			9.82 × 10⁴	6.8
	99.9% (1000 ppm NO_x)			9.82 × 10⁵	68
20	99.999% (10 ppm NO_x)	240	1.96 × 10⁸	1.96 × 10³	0.14
	99.99% (100 ppm NO_x)			1.96 × 10⁴	1.4
	99.9% (1000 ppm NO_x)			1.96 × 10⁵	14
0	99.999% (10 ppm NO_x)	15 (prior to experiment at 20 mL min^‒1)	1.23 × 10⁷	1.23 × 10²	0.009
	99.99% (100 ppm NO_x)			1.23 × 10³	0.09
	99.9% (1000 ppm NO_x)			1.23 × 10⁴	0.9

Fig. 5. (a) Comparison of Nessler's reagent method and Indophenol blue method. Their reaction mechanisms, UV-Vis spectra and experimental phenomena are all listed in the form of table. (b) Standard curves for NH3 quantitation (lower than 0.2 × 10-6 g mL-1) using NR (up) and IB (down) methods under acid, neutral and alkaline electrolyte systems. Reprinted with permission from Ref. [83]. Copyright 2021, John Wiley and Sons. (c) 1H NMR spectra of concentrated ammonium chloride standard solutions were prepared in different deuterated solvents (DMSO-d6: red; acetone-d6: blue; water-d2: green), and analyzed after 24 h to emphasize deuterium exchange. Reprinted with permission from Ref. [90]. Copyright 2020, American Chemical Society. (d) 1H NMR spectra of 14NH4+-14N and 15NH4+-15N. Reprinted with permission from Ref. [102], Copyright 2020, National Academy of Sciences.

Ammonia quantification method				IB	NR	IC	NMR
Concentration		Method	pH	IB	NR	IC	NMR
	< 0.2 × 10^-6 g mL^-1	Electrocatalysis	Acid	☺	—	☺	☺
			Neutral	☺	☺	—	☺
			Alkaline	☺	—	—	—
		Photocatalysis		—	—	☺	☺
	≥ 0.2 × 10^-6 g mL^-1	—	—	Routine quantification

Fig. 6. A strict protocol for accurate ammonia quantification in NRR system.

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Excluding false positives: A perspective toward credible ammonia quantification in nitrogen reduction reaction

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